# Prediction Models for Bronchopulmonary Dysplasia in Preterm Infants: A Systematic Review and Meta-Analysis

Michelle Romijn, Paula Dhiman, Martijn J J Finken, Anton H van Kaam, Trixie A Katz, Joost Rotteveel, Ewoud Schuit, Gary S Collins, Wes Onland, Héloïse Torchin

► To cite this version:

Michelle Romijn, Paula Dhiman, Martijn J J Finken, Anton H van Kaam, Trixie A Katz, et al. Prediction Models for Bronchopulmonary Dysplasia in Preterm Infants: A Systematic Review and Meta-Analysis. The Journal of Pediatrics, 2023, 258, pp.113370. 10.1016/j.jpeds.2023.01.024. inserm-04535012

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# Prediction Models for Bronchopulmonary Dysplasia in Preterm Infants: A Systematic Review and Meta-Analysis

Michelle Romijn, Paula Dhiman, Martijn J J Finken, Anton H van Kaam, Trixie A Katz, Joost Rotteveel, Ewoud Schuit, Gary S Collins, Wes Onland, Héloïse Torchin

<figure><img src="image_1.png" /></figure>

## To cite this version:

Michelle Romijn, Paula Dhiman, Martijn J J Finken, Anton H van Kaam, Trixie A Katz, et al. Prediction Models for Bronchopulmonary Dysplasia in Preterm Infants: A Systematic Review and Meta-Analysis. The Journal of Pediatrics, 2023, 258, pp.113370. 10.1016/j.jpeds.2023.01.024. inserm-04535012

HAL Id: inserm-04535012

https://inserm.hal.science/inserm-04535012v1

Submitted on 5 Apr 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

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Distributed under a Creative Commons Attribution 4.0 International License
# Prediction Models for Bronchopulmonary Dysplasia in Preterm Infants: A Systematic Review and Meta-Analysis

Michelle Romijn, MD<sup>1,2,3</sup>, Paula Dhiman, PhD<sup>4,5</sup>, Martijn J. J. Finken, MD, PhD<sup>2,3</sup>, Anton H. van Kaam, MD, PhD<sup>1,3</sup>, Trixie A. Katz, MD<sup>1,3</sup>, Joost Rotteveel, MD, PhD<sup>2,3</sup>, Ewoud Schuit, PhD<sup>6,7</sup>, Gary S. Collins, PhD<sup>4,5</sup>, Wes Onland, MD, PhD<sup>1,3</sup>, and Heloise Torchin, MD, PhD<sup>8,9</sup>

**Objective** To review systematically and assess the accuracy of prediction models for bronchopulmonary dysplasia (BPD) at 36 weeks of postmenstrual age.

**Study design** Searches were conducted in MEDLINE and EMBASE. Studies published between 1990 and 2022 were included if they developed or validated a prediction model for BPD or the combined outcome death/BPD at 36 weeks in the first 14 days of life in infants born preterm. Data were extracted independently by 2 authors following the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (ie, CHARMS) and PRISMA guidelines. Risk of bias was assessed using the Prediction model Risk Of Bias ASsessment Tool (ie, PROBAST).

**Results** Sixty-five studies were reviewed, including 158 development and 108 externally validated models. Median c-statistic of 0.84 (range 0.43-1.00) was reported at model development, and 0.77 (range 0.41-0.97) at external validation. All models were rated at high risk of bias, due to limitations in the analysis part. Meta-analysis of the validated models revealed increased c-statistics after the first week of life for both the BPD and death/BPD outcome.

**Conclusions** Although BPD prediction models perform satisfactorily, they were all at high risk of bias. Methodologic improvement and complete reporting are needed before they can be considered for use in clinical practice. Future research should aim to validate and update existing models. (J Pediatr 2023; ■:113370).

Despite recent advances in perinatal care, bronchopulmonary dysplasia (BPD) remains a frequent complication of very preterm birth.¹ It is associated with greater odds of mortality, respiratory morbidity, adverse neurologic development, and increased health care-related costs.²⁻⁴

Identifying the development of BPD at an early stage is important to improve treatment of high-risk infants and provide sufficient long-term prognostic information to parents.⁵ A systematic review published in 2013 identified BPD prediction models developed using routinely collected clinical data during the first week of life.⁶ Most of the publications reported the model discrimination, which is a key performance measure recommended in the TRIPOD (ie, Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis) Statement.⁷ However, none reported calibration, and external validation was rarely performed. Finally, no standardized tool to evaluate the risk of bias (RoB) in prediction models was available at the time of that review, and thus their quality has not been evaluated formally. Several new prediction models have since been published, including models investigating potential biomarkers. Furthermore, the Prediction model Risk Of Bias ASsessment Tool (ie, PROBAST) now provides a formal RoB assessment for studies aiming to develop or validate a prediction model.⁸ Thus, our objective was to provide a systematic review of multivariable prediction models for BPD at 36 weeks of postmenstrual age (PMA) in infants born preterm and assess their RoB.

95% PI 95% prediction interval
BPD Bronchopulmonary dysplasia

PMA Postmenstrual age

PROBAST Prediction model Risk Of Bias ASsessment Tool

RoB Risk of bias

From the ¹Department of Neonatology, University of Amsterdam, and ²Department of Pediatric Endocrinology, Vrije Universiteit Amsterdam, Amsterdam UMC Location, Amsterdam, The Netherlands; ³Amsterdam Reproduction & Development Research Institute, Amsterdam, The Netherlands:

⁴Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Centre for Statistics in Medicine, University of Oxford, Oxford, United Kingdom;

⁵National Institute for Health and Care Research (NIHR) Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; ⁶Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, and ⁷Cochrane Netherlands, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands; ⁸Epidemiology and Statistics Research Center/CRESS, Université Paris Cite, INSERM, INRAE, Paris, France; and ⁵Department of Neonatal Medicine, Cochin-Port Royal Hospital, APHP, Paris, France

M.R. was supported by the Amsterdam Reproduction & Development Research Institute. P.D. was supported by the National Institute for Health and Care Research (NIHR) Biomedical Research Centre, Oxford. G.C. was supported by the NIHR Biomedical Research Centre, Oxford, and Cancer Research UK (program grant: C49297/A27294). H.T. received grants from the French Society of Neonatology and from the French Society of Pediatrics. The authors declare no conflicts of interest.

0022-3476/© 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

https://doi.org/10.1016/j.jpeds.2023.01.024
# Prediction Models for Bronchopulmonary Dysplasia in Preterm Infants: A Systematic Review and Meta-Analysis

Michelle Romijn, MD<sup>1,2,3</sup>, Paula Dhiman, PhD<sup>4,5</sup>, Martijn J. J. Finken, MD, PhD<sup>2,3</sup>, Anton H. van Kaam, MD, PhD<sup>1,3</sup>, Trixie A. Katz, MD<sup>1,3</sup>, Joost Rotteveel, MD, PhD<sup>2,3</sup>, Ewoud Schuit, PhD<sup>6,7</sup>, Gary S. Collins, PhD<sup>4,5</sup>, Wes Onland, MD, PhD<sup>1,3</sup>, and Heloise Torchin, MD, PhD<sup>8,9</sup>

**Objective** To review systematically and assess the accuracy of prediction models for bronchopulmonary dysplasia (BPD) at 36 weeks of postmenstrual age.

**Study design** Searches were conducted in MEDLINE and EMBASE. Studies published between 1990 and 2022 were included if they developed or validated a prediction model for BPD or the combined outcome death/BPD at 36 weeks in the first 14 days of life in infants born preterm. Data were extracted independently by 2 authors following the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (ie, CHARMS) and PRISMA guidelines. Risk of bias was assessed using the Prediction model Risk Of Bias ASsessment Tool (ie, PROBAST).

**Results** Sixty-five studies were reviewed, including 158 development and 108 externally validated models. Median c-statistic of 0.84 (range 0.43-1.00) was reported at model development, and 0.77 (range 0.41-0.97) at external validation. All models were rated at high risk of bias, due to limitations in the analysis part. Meta-analysis of the validated models revealed increased c-statistics after the first week of life for both the BPD and death/BPD outcome.

**Conclusions** Although BPD prediction models perform satisfactorily, they were all at high risk of bias. Methodologic improvement and complete reporting are needed before they can be considered for use in clinical practice. Future research should aim to validate and update existing models. (J Pediatr 2023; ■:113370).

Despite recent advances in perinatal care, bronchopulmonary dysplasia (BPD) remains a frequent complication of very preterm birth.¹ It is associated with greater odds of mortality, respiratory morbidity, adverse neurologic development, and increased health care-related costs.²⁻⁴

Identifying the development of BPD at an early stage is important to improve treatment of high-risk infants and provide sufficient long-term prognostic information to parents.⁵ A systematic review published in 2013 identified BPD prediction models developed using routinely collected clinical data during the first week of life.⁶ Most of the publications reported the model discrimination, which is a key performance measure recommended in the TRIPOD (ie, Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis) Statement.⁷ However, none reported calibration, and external validation was rarely performed. Finally, no standardized tool to evaluate the risk of bias (RoB) in prediction models was available at the time of that review, and thus their quality has not been evaluated formally. Several new prediction models have since been published, including models investigating potential biomarkers. Furthermore, the Prediction model Risk Of Bias ASsessment Tool (ie, PROBAST) now provides a formal RoB assessment for studies aiming to develop or validate a prediction model.⁸ Thus, our objective was to provide a systematic review of multivariable prediction models for BPD at 36 weeks of postmenstrual age (PMA) in infants born preterm and assess their RoB.

95% PI 95% prediction interval
BPD Bronchopulmonary dysplasia

PMA Postmenstrual age

PROBAST Prediction model Risk Of Bias ASsessment Tool

RoB Risk of bias

From the ¹Department of Neonatology, University of Amsterdam, and ²Department of Pediatric Endocrinology, Vrije Universiteit Amsterdam, Amsterdam UMC Location, Amsterdam, The Netherlands; ³Amsterdam Reproduction & Development Research Institute, Amsterdam, The Netherlands:

⁴Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Centre for Statistics in Medicine, University of Oxford, Oxford, United Kingdom;

⁵National Institute for Health and Care Research (NIHR) Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; ⁶Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, and ⁷Cochrane Netherlands, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands; ⁸Epidemiology and Statistics Research Center/CRESS, Université Paris Cite, INSERM, INRAE, Paris, France; and ⁵Department of Neonatal Medicine, Cochin-Port Royal Hospital, APHP, Paris, France

M.R. was supported by the Amsterdam Reproduction & Development Research Institute. P.D. was supported by the National Institute for Health and Care Research (NIHR) Biomedical Research Centre, Oxford. G.C. was supported by the NIHR Biomedical Research Centre, Oxford, and Cancer Research UK (program grant: C49297/A27294). H.T. received grants from the French Society of Neonatology and from the French Society of Pediatrics. The authors declare no conflicts of interest.

0022-3476/© 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

https://doi.org/10.1016/j.jpeds.2023.01.024
## Methods

This systematic review was performed and reported according to the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies (CHARMS) and the PRISMA guidelines (Appendix 2; available at www.jpeds.com).⁹,¹⁰ Identification of eligible studies for inclusion was performed by using the MEDLINE and EMBASE electronic databases restricted to articles published between January 1, 1990, and July 31, 2022. The search strategy consisted of key words and medical subject headings terms under the topic of prediction model, BPD, and newborn (eMethods in the Appendix 1; available at www.jpeds.com). No language restrictions were applied. The protocol was registered on the International Prospective Register of Systematic Reviews (PROSPERO, registration number: CRD42021249437).

All studies that aimed to develop or validate a multivariable prediction model for BPD or the combined outcome death or BPD (death/BPD) in the first 14 days of life after preterm birth were eligible for inclusion. Additional eligibility criteria were that BPD assessment had to be performed at 36 weeks of PMA; studies with earlier BPD definitions were excluded. Studies had to use data from infants born after 1990, as antenatal steroids and surfactant treatment were not widely implemented in infants born before 1990. Finally, reviews, guidelines, conference abstracts, and animal studies were excluded. There was no restriction on the predictors considered for inclusion in the models, including clinical data, biomarkers, imaging results, or other information.

## Data Extraction and Analysis

Screening and identification of the studies were independently performed by 2 authors. Titles and abstracts were screened to determine eligibility. A full-text review was performed for all potentially eligible studies to determine inclusion or exclusion. Data from the included studies were independently extracted in duplicate by 2 authors in accordance with the CHARMS checklist⁹ (eMethods in Appendix 1). Disagreement or differences were resolved by consensus or by a third reviewer. Authors of the included studies were not contacted to obtain additional data.

Characteristics of the included studies, development models, and externally validated models were described. For models that were both developed and validated in the same study, information on development and validation was extracted separately. Participants and predictors data were summarized with medians and ranges. The number of events per variable was calculated for each development model by dividing the number of outcome events—or the number of infants without the outcome if such was lower—by the number of candidate predictors. The median c-statistic and range were calculated separately for development models (apparent c-statistic when it was the only available information and c-statistic corrected for optimism when reported) and for externally validated models.

Externally validated prediction models were analyzed quantitatively by using random effects meta-analyses for the outcomes BPD and death/BPD separately in order to quantify an overall performance, including a prediction interval and heterogeneity of these models over time. Only discrimination performances, ie, c-statistics, were meta-analyzed, as calibration performances were poorly reported. If researchers performed external validation of several models very similar to each other (eg, one variable coded as continuous in the first model and dichotomized in the second model) at the same time point, only the best c-statistic was included. Meta-analysis was performed using the actual reported c-statistic including SE and/or 95% CI reported in the included study. These values were logit transformed, which resulted in a pooled c-statistic with corresponding 95% CI.¹¹ In addition, 95% prediction intervals (PIs) were calculated to provide boundaries on the likely performance in future model validation studies that are comparable with the studies included in the meta-analysis.¹² We then stratified the meta-analysis by timing assessment (birth to 24 hours of life, day 1 to day 7, and day 8 to day 14). The prespecified minimum number of models to perform meta-analysis was 3, this number was met for each outcome and each time point.

## RoB and Applicability Assessment

The RoB and applicability assessment was evaluated independently by 2 authors using the PROBAST guidelines.⁸ The RoB and applicability for each domain was scored as low, high, or unclear. If any of the signaling questions in a domain was answered with “no,” the risk of bias of that domain was scored as high, and eventually, the overall judgment was scored as high risk of bias.

## Results

The search resulted in 11 260 references (Figure 1; available at www.jpeds.com). Duplicates (n = 3298), reviews, editorial papers, and irrelevant studies based on their title (n = 5239) were excluded. Of the remaining 2723 abstracts, 683 full texts were retained for review. Of these, 618 references were excluded for various reasons (Figure 1). Finally, 65 studies met the inclusion criteria.¹³⁻⁷⁵ One study that performed external validation and reported calibration plots for several BPD prediction models was excluded because data was used from infants born before 1990.⁶

Forty-nine studies described the development of at least 1 model, accounting for 158 developed models in total. Thirty-two studies externally validated at least 1 model accounting for 108 models. From those 32 studies, 9 externally validated a model that had been developed in the same
## Methods

This systematic review was performed and reported according to the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies (CHARMS) and the PRISMA guidelines (Appendix 2; available at www.jpeds.com).⁹,¹⁰ Identification of eligible studies for inclusion was performed by using the MEDLINE and EMBASE electronic databases restricted to articles published between January 1, 1990, and July 31, 2022. The search strategy consisted of key words and medical subject headings terms under the topic of prediction model, BPD, and newborn (eMethods in the Appendix 1; available at www.jpeds.com). No language restrictions were applied. The protocol was registered on the International Prospective Register of Systematic Reviews (PROSPERO, registration number: CRD42021249437).

All studies that aimed to develop or validate a multivariable prediction model for BPD or the combined outcome death or BPD (death/BPD) in the first 14 days of life after preterm birth were eligible for inclusion. Additional eligibility criteria were that BPD assessment had to be performed at 36 weeks of PMA; studies with earlier BPD definitions were excluded. Studies had to use data from infants born after 1990, as antenatal steroids and surfactant treatment were not widely implemented in infants born before 1990. Finally, reviews, guidelines, conference abstracts, and animal studies were excluded. There was no restriction on the predictors considered for inclusion in the models, including clinical data, biomarkers, imaging results, or other information.

## Data Extraction and Analysis

Screening and identification of the studies were independently performed by 2 authors. Titles and abstracts were screened to determine eligibility. A full-text review was performed for all potentially eligible studies to determine inclusion or exclusion. Data from the included studies were independently extracted in duplicate by 2 authors in accordance with the CHARMS checklist⁹ (eMethods in Appendix 1). Disagreement or differences were resolved by consensus or by a third reviewer. Authors of the included studies were not contacted to obtain additional data.

Characteristics of the included studies, development models, and externally validated models were described. For models that were both developed and validated in the same study, information on development and validation was extracted separately. Participants and predictors data were summarized with medians and ranges. The number of events per variable was calculated for each development model by dividing the number of outcome events—or the number of infants without the outcome if such was lower—by the number of candidate predictors. The median c-statistic and range were calculated separately for development models (apparent c-statistic when it was the only available information and c-statistic corrected for optimism when reported) and for externally validated models.

Externally validated prediction models were analyzed quantitatively by using random effects meta-analyses for the outcomes BPD and death/BPD separately in order to quantify an overall performance, including a prediction interval and heterogeneity of these models over time. Only discrimination performances, ie, c-statistics, were meta-analyzed, as calibration performances were poorly reported. If researchers performed external validation of several models very similar to each other (eg, one variable coded as continuous in the first model and dichotomized in the second model) at the same time point, only the best c-statistic was included. Meta-analysis was performed using the actual reported c-statistic including SE and/or 95% CI reported in the included study. These values were logit transformed, which resulted in a pooled c-statistic with corresponding 95% CI.¹¹ In addition, 95% prediction intervals (PIs) were calculated to provide boundaries on the likely performance in future model validation studies that are comparable with the studies included in the meta-analysis.¹² We then stratified the meta-analysis by timing assessment (birth to 24 hours of life, day 1 to day 7, and day 8 to day 14). The prespecified minimum number of models to perform meta-analysis was 3, this number was met for each outcome and each time point.

## RoB and Applicability Assessment

The RoB and applicability assessment was evaluated independently by 2 authors using the PROBAST guidelines.⁸ The RoB and applicability for each domain was scored as low, high, or unclear. If any of the signaling questions in a domain was answered with “no,” the risk of bias of that domain was scored as high, and eventually, the overall judgment was scored as high risk of bias.

## Results

The search resulted in 11 260 references (Figure 1; available at www.jpeds.com). Duplicates (n = 3298), reviews, editorial papers, and irrelevant studies based on their title (n = 5239) were excluded. Of the remaining 2723 abstracts, 683 full texts were retained for review. Of these, 618 references were excluded for various reasons (Figure 1). Finally, 65 studies met the inclusion criteria.¹³⁻⁷⁵ One study that performed external validation and reported calibration plots for several BPD prediction models was excluded because data was used from infants born before 1990.⁶

Forty-nine studies described the development of at least 1 model, accounting for 158 developed models in total. Thirty-two studies externally validated at least 1 model accounting for 108 models. From those 32 studies, 9 externally validated a model that had been developed in the same
paper.<sup>13,14,16,21,22,28,30,64,67</sup> Finally, 12 studies developed at least 1 model and externally validated existing models.<sup>16,18,21,50,52,57,58,60,62,63,68,71</sup>

The study characteristics of the 65 included studies are described in **Table I** (available at www.jpeds.com). The included studies were published between 1996 and 2022, and the number of publications increased over time. Almost one-half of the included studies were performed in North America, followed by Europe. Most of the studies included data from single centers. Participants included in development and validation samples were similar for median gestational age (27.2 and 28.0 weeks, respectively), and median birth weight (911 and 938 g, respectively).

## Development of BPD Prediction Models

**Model Development.** The total number of eligible infants was reported in most models (99.4%) (Table II). However, the total number of analyzed infants was less frequently reported (89.2%) and ranged from 43.8% to 100% of eligible infants. Some of the studies with high numbers of eligible infants did not report how many infants were finally analyzed in the models,<sup>28,30,43,46</sup> which explains the discrepancy between the median number of the analyzed infants and of outcome events. The proportion of infants with BPD from the total number of analyzed infants ranged from 14.8% to 68.2% across the studies and with death/BPD from 31.3% to 77.0%. The median number of predictors considered for inclusion in the models was 15 (range 1-50). The number of events per variable was less than 10 in 33.6%, and more than 20 in 40.9% of the models. The final prediction models included a median of 6 predictors (range 2-21). The predicted outcome was either BPD (43.7%) or death/BPD (56.3%) 36 weeks of PMA (Table I). Infants that died before 36 weeks of PMA were either excluded from analyses (39.2%), included in the no-BPD group (0.6%),<sup>13</sup> or included in the death/BPD group (52.5%). The most frequent timing of model assessment was day 7 (31.0%).

As shown in Table II, most models used all candidate predictors before multivariable modeling (56.3%). Logistic regression with all predictors forced in the model was the most frequently used modeling method. Five models (3.2%) used Classification and Regression Tree analysis. In 55 models (34.8%), eligible participants with missing data were excluded from the analysis, and 52 models (32.9%) performed single or multiple imputation for imputation of missing data. For all other models, insufficient or no information was reported to determine how much missing data there was, and how it was handled. In some models, continuous predictors were converted into categories (7.6%).

**Model Validation and Performance.** Internal validation was performed in 78 models (49.4%) with single random split-sample of participant data (9.5%), cross-validation (35.4%), or resampling of same data set (4.4%) (Table II). For 17 models (10.8%), both development and external validation were described in the same

article.<sup>13,14,16,21,22,28,30,64,67</sup> C-statistic was reported for most models (91.8%) with a median apparent c-statistic of 0.84 (range 0.43-1.00) (Table II). C-statistics after internal validation were reported in most models (94.9%) with a median c-statistic of 0.86 (range 0.67-0.91). Calibration was reported in 13 models (7.5%) with Hosmer-Lemeshow tests,<sup>18,22,26</sup> and 4 models (2.5%) showed a calibration plot.

Seventeen models (10.8%) were reported fully, including the intercept and all the final predictor weights from logistic regression modeling or the final classification tree from Classification and Regression Tree analysis. Two studies developed an online prediction tool that provides individual prediction of death/BPD risk at day 1, 3, 7, and 14 of life.<sup>28,72</sup>

**Predictors in the Final Developed Models.** Mostoftheprediction models (70.3%) included routinely collected data (Table II). Among those, gestational age, birth weight, sex, and information about early respiratory status were most often included (Figure 2). Other frequently used predictors were blood biomarkers,<sup>19,35,40,51</sup> tracheal samples,<sup>23,32,34</sup> lung mechanics/imaging,<sup>17,45,52,57,62,63,68,71</sup> and echocardiographic data.<sup>14,36,51,74</sup> Finally, a few models included illness severity scores,<sup>19,26,51</sup> urinary biomarkers,<sup>70</sup> genetic biomarkers,<sup>59</sup> and vitalorventilatorparameters.<sup>41,49</sup>

## External Validation of BPD Prediction Models

The total number of analyzed infants was reported for most of the externally validated models (87.0%) as well as the number of infants with the outcome (92.6%) (Table II). Most of the models (81%) were validated in data that included fewer than 100 outcome events. Fifty-five models (50.9%) were validated with complete-case analysis, and 5 (4.6%) reported no missing data. Validated models were mainly assessed at day 7 after birth (21.3%), at day 3 (13.9%) or up to 12 hours after admission (13.9%), using mostly predictors from lung mechanics/imaging (43.5%) or routinely collected data (37.3%) (Table II). Fifteen studies performed external validation of existing prediction models, illness severity scores.<sup>15,18,28,29,33,38,39,42,47,48,50,53,56,60</sup>

**Predictive Performances of Externally Validated Models.** C-statistics were reported in almost all models (97.2%) with a median c-statistic of 0.77 (range 0.41-0.97). Calibration was reported in 3 models (2.8%) with Hosmer-Lemeshow tests<sup>18,22,29</sup> or a table of predicted and observed probabilities (1.9%).<sup>42</sup>

In the 7 studies that reported both the development and external validation,<sup>13,16,21,22,28,30,67</sup> discrimination were very similar between model development and validation (median c-statistic 0.83 [range 0.76-0.96] and 0.84 [range 0.70-0.97]), respectively. The Hosmer-Lemeshow test was used in one study.<sup>22</sup>

In total, 57 externally validated models predicting BPD were included in the meta-analysis and the pooled c-statistic was 0.78 (95% CI 0.74-0.82, 95% PI 0.48-0.93) (Figure 3, A) and increased after the first week of life, but with overlapping
paper.<sup>13,14,16,21,22,28,30,64,67</sup> Finally, 12 studies developed at least 1 model and externally validated existing models.<sup>16,18,21,50,52,57,58,60,62,63,68,71</sup>

The study characteristics of the 65 included studies are described in **Table I** (available at www.jpeds.com). The included studies were published between 1996 and 2022, and the number of publications increased over time. Almost one-half of the included studies were performed in North America, followed by Europe. Most of the studies included data from single centers. Participants included in development and validation samples were similar for median gestational age (27.2 and 28.0 weeks, respectively), and median birth weight (911 and 938 g, respectively).

## Development of BPD Prediction Models

**Model Development.** The total number of eligible infants was reported in most models (99.4%) (Table II). However, the total number of analyzed infants was less frequently reported (89.2%) and ranged from 43.8% to 100% of eligible infants. Some of the studies with high numbers of eligible infants did not report how many infants were finally analyzed in the models,<sup>28,30,43,46</sup> which explains the discrepancy between the median number of the analyzed infants and of outcome events. The proportion of infants with BPD from the total number of analyzed infants ranged from 14.8% to 68.2% across the studies and with death/BPD from 31.3% to 77.0%. The median number of predictors considered for inclusion in the models was 15 (range 1-50). The number of events per variable was less than 10 in 33.6%, and more than 20 in 40.9% of the models. The final prediction models included a median of 6 predictors (range 2-21). The predicted outcome was either BPD (43.7%) or death/BPD (56.3%) 36 weeks of PMA (Table I). Infants that died before 36 weeks of PMA were either excluded from analyses (39.2%), included in the no-BPD group (0.6%),<sup>13</sup> or included in the death/BPD group (52.5%). The most frequent timing of model assessment was day 7 (31.0%).

As shown in Table II, most models used all candidate predictors before multivariable modeling (56.3%). Logistic regression with all predictors forced in the model was the most frequently used modeling method. Five models (3.2%) used Classification and Regression Tree analysis. In 55 models (34.8%), eligible participants with missing data were excluded from the analysis, and 52 models (32.9%) performed single or multiple imputation for imputation of missing data. For all other models, insufficient or no information was reported to determine how much missing data there was, and how it was handled. In some models, continuous predictors were converted into categories (7.6%).

**Model Validation and Performance.** Internal validation was performed in 78 models (49.4%) with single random split-sample of participant data (9.5%), cross-validation (35.4%), or resampling of same data set (4.4%) (Table II). For 17 models (10.8%), both development and external validation were described in the same

article.<sup>13,14,16,21,22,28,30,64,67</sup> C-statistic was reported for most models (91.8%) with a median apparent c-statistic of 0.84 (range 0.43-1.00) (Table II). C-statistics after internal validation were reported in most models (94.9%) with a median c-statistic of 0.86 (range 0.67-0.91). Calibration was reported in 13 models (7.5%) with Hosmer-Lemeshow tests,<sup>18,22,26</sup> and 4 models (2.5%) showed a calibration plot.

Seventeen models (10.8%) were reported fully, including the intercept and all the final predictor weights from logistic regression modeling or the final classification tree from Classification and Regression Tree analysis. Two studies developed an online prediction tool that provides individual prediction of death/BPD risk at day 1, 3, 7, and 14 of life.<sup>28,72</sup>

**Predictors in the Final Developed Models.** Mostoftheprediction models (70.3%) included routinely collected data (Table II). Among those, gestational age, birth weight, sex, and information about early respiratory status were most often included (Figure 2). Other frequently used predictors were blood biomarkers,<sup>19,35,40,51</sup> tracheal samples,<sup>23,32,34</sup> lung mechanics/imaging,<sup>17,45,52,57,62,63,68,71</sup> and echocardiographic data.<sup>14,36,51,74</sup> Finally, a few models included illness severity scores,<sup>19,26,51</sup> urinary biomarkers,<sup>70</sup> genetic biomarkers,<sup>59</sup> and vitalorventilatorparameters.<sup>41,49</sup>

## External Validation of BPD Prediction Models

The total number of analyzed infants was reported for most of the externally validated models (87.0%) as well as the number of infants with the outcome (92.6%) (Table II). Most of the models (81%) were validated in data that included fewer than 100 outcome events. Fifty-five models (50.9%) were validated with complete-case analysis, and 5 (4.6%) reported no missing data. Validated models were mainly assessed at day 7 after birth (21.3%), at day 3 (13.9%) or up to 12 hours after admission (13.9%), using mostly predictors from lung mechanics/imaging (43.5%) or routinely collected data (37.3%) (Table II). Fifteen studies performed external validation of existing prediction models, illness severity scores.<sup>15,18,28,29,33,38,39,42,47,48,50,53,56,60</sup>

**Predictive Performances of Externally Validated Models.**

C-statistics were reported in almost all models (97.2%) with a median c-statistic of 0.77 (range 0.41-0.97). Calibration was reported in 3 models (2.8%) with Hosmer-Lemeshow tests<sup>18,22,29</sup> or a table of predicted and observed probabilities (1.9%).<sup>42</sup>

In the 7 studies that reported both the development and external validation,<sup>13,16,21,22,28,30,67</sup> discrimination were very similar between model development and validation (median c-statistic 0.83 [range 0.76-0.96] and 0.84 [range 0.70-0.97]), respectively. The Hosmer-Lemeshow test was used in one study.<sup>22</sup>

In total, 57 externally validated models predicting BPD were included in the meta-analysis and the pooled c-statistic was 0.78 (95% CI 0.74-0.82, 95% PI 0.48-0.93) (Figure 3, A) and increased after the first week of life, but with overlapping
<table><caption>Table II. Characteristics of the included models</caption><thead><tr><th>Characteristics</th><th colspan="2">Developed models, n = 158*</th><th colspan="2">Validated models, n = 108*</th></tr><tr><th></th><th>No. (%)</th><th>Median [min-max]</th><th>No. (%)</th><th>Median [min-max]</th></tr></thead><tbody><tr><td><strong>Participants and predictors</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Total sample size—eligible</td><td>157 (99.4)</td><td>778 [27-156 587]</td><td>107 (99.1)</td><td>158 [28-9240]</td></tr><tr><td>Total sample size—analyzed</td><td>141 (89.2)</td><td>474 [22-20 771]</td><td>94 (87.0)</td><td>130 [28-7975]</td></tr><tr><td>Number of outcome events</td><td>155 (98.1)</td><td>232 [11-6121]</td><td>100 (92.6)</td><td>50 [8-2959]</td></tr><tr><td>Number of candidate predictors</td><td>150 (94.9)</td><td>15 [1-50]</td><td>NA</td><td>NA</td></tr><tr><td>Events per predictor for model development</td><td>149 (94.3)</td><td>102.9 [0.33-986.3]</td><td>NA</td><td>NA</td></tr><tr><td>Number of predictors in the final model</td><td>158 (100.0)</td><td>6 [2-21]</td><td>NA</td><td>NA</td></tr><tr><td><strong>Type of predictors in final model</strong></td><td><strong>No. (%)</strong></td><td></td><td><strong>No. (%)</strong></td><td></td></tr><tr><td>Routinely collected data only†</td><td>111 (70.3)</td><td></td><td>59 (37.3)</td><td></td></tr><tr><td>Echocardiographic data</td><td>4 (2.5)</td><td></td><td>2 (1.9)</td><td></td></tr><tr><td>Lung mechanics/imaging</td><td>20 (12.7)</td><td></td><td>47 (43.5)</td><td></td></tr><tr><td>Blood biomarkers</td><td>11 (7.0)</td><td></td><td>0 (0.0)</td><td></td></tr><tr><td>Tracheal biomarkers</td><td>3 (1.9)</td><td></td><td>0 (0.0)</td><td></td></tr><tr><td>Urinary biomarkers</td><td>2 (1.3)</td><td></td><td>0 (0.0)</td><td></td></tr><tr><td>Genetic biomarkers</td><td>2 (1.3)</td><td></td><td>0 (0.0)</td><td></td></tr><tr><td>Combination of above</td><td>5 (3.2)</td><td></td><td>0 (0.0)</td><td></td></tr><tr><td><strong>Timing of model assessment</strong></td><td><strong>No. (%)</strong></td><td></td><td><strong>No. (%)</strong></td><td></td></tr><tr><td>At birth</td><td>7 (4.4)</td><td></td><td>5 (1.5)</td><td></td></tr><tr><td>At admission</td><td>1 (0.6)</td><td></td><td>2 (1.9)</td><td></td></tr><tr><td>1 hour after admission</td><td>0 (0.0)</td><td></td><td>3 (2.8)</td><td></td></tr><tr><td>12 hours after admission</td><td>6 (3.8)</td><td></td><td>15 (13.9)</td><td></td></tr><tr><td>Day 1</td><td>28 (17.7)</td><td></td><td>13 (12.0)</td><td></td></tr><tr><td>Day 2</td><td>2 (1.3)</td><td></td><td>5 (4.6)</td><td></td></tr><tr><td>Day 3</td><td>15 (9.5)</td><td></td><td>15 (13.9)</td><td></td></tr><tr><td>Day 4</td><td>2 (1.3)</td><td></td><td>3 (2.8)</td><td></td></tr><tr><td>Day 6</td><td>4 (2.5)</td><td></td><td>3 (2.8)</td><td></td></tr><tr><td>Day 7</td><td>49 (31.0)</td><td></td><td>23 (21.3)</td><td></td></tr><tr><td>Day 9</td><td>3 (1.9)</td><td></td><td>3 (2.8)</td><td></td></tr><tr><td>Day 10</td><td>2 (1.3)</td><td></td><td>4 (3.7)</td><td></td></tr><tr><td>Day 12</td><td>0 (0.0)</td><td></td><td>3 (2.8)</td><td></td></tr><tr><td>Day 14</td><td>28 (17.7)</td><td></td><td>9 (8.3)</td><td></td></tr><tr><td>Unclear</td><td>11 (7.0)</td><td></td><td>2 (1.9)</td><td></td></tr><tr><td><strong>Methodologic aspects of model development</strong></td><td><strong>No. (%)</strong></td><td></td><td></td><td></td></tr><tr><td><em>Handling of missing data</em></td><td></td><td></td><td></td><td></td></tr><tr><td>Complete-case analysis</td><td>55 (34.8)</td><td></td><td></td><td></td></tr><tr><td>Single/multiple imputation</td><td>52 (32.9)</td><td></td><td></td><td></td></tr><tr><td>Unclear or no information</td><td>51 (32.3)</td><td></td><td></td><td></td></tr><tr><td><em>Handling of linear predictors</em></td><td></td><td></td><td></td><td></td></tr><tr><td>Appropriately</td><td>19 (12.0)</td><td></td><td></td><td></td></tr><tr><td>Not appropriately</td><td>12 (7.6)</td><td></td><td></td><td></td></tr><tr><td>No information</td><td>100 (63.3)</td><td></td><td></td><td></td></tr><tr><td><em>Modeling method</em></td><td></td><td></td><td></td><td></td></tr><tr><td>Logistic regression</td><td>110 (69.6)</td><td></td><td></td><td></td></tr><tr><td>CART analysis</td><td>5 (3.2)</td><td></td><td></td><td></td></tr><tr><td>Other</td><td>97 (61.4)</td><td></td><td></td><td></td></tr><tr><td><em>Selection of predictors in multivariable model</em></td><td></td><td></td><td></td><td></td></tr><tr><td>Preselection based on univariable analysis</td><td>40 (25.3)</td><td></td><td></td><td></td></tr><tr><td>All candidate predictors</td><td>89 (56.3)</td><td></td><td></td><td></td></tr><tr><td>Exclusion of variables from previous model</td><td>1 (0.6)</td><td></td><td></td><td></td></tr><tr><td>Addition of variables to previous model</td><td>3 (1.9)</td><td></td><td></td><td></td></tr><tr><td>LASSO</td><td>1 (0.6)</td><td></td><td></td><td></td></tr><tr><td>Best goodness-of-fit parameters</td><td>2 (1.3)</td><td></td><td></td><td></td></tr><tr><td>Unclear</td><td>22 (13.9)</td><td></td><td></td><td></td></tr><tr><td><em>Selection of predictors in final model</em></td><td></td><td></td><td></td><td></td></tr><tr><td>All predictors forced in model</td><td>72 (45.6)</td><td></td><td></td><td></td></tr><tr><td>All candidate predictors</td><td>3 (1.9)</td><td></td><td></td><td></td></tr><tr><td>Backwards stepwise selection</td><td>17 (10.8)</td><td></td><td></td><td></td></tr><tr><td>Forwards stepwise selection</td><td>21 (13.3)</td><td></td><td></td><td></td></tr><tr><td>Both FW and BW stepwise selection</td><td>9 (5.7)</td><td></td><td></td><td></td></tr><tr><td>Stepwise selection</td><td>8 (5.1)</td><td></td><td></td><td></td></tr><tr><td>Same variables used as in stepwise logistic regression model</td><td>1 (0.6)</td><td></td><td></td><td></td></tr><tr><td>All possible combinations</td><td>1 (0.6)</td><td></td><td></td><td></td></tr><tr><td>Best performance of model</td><td>1 (0.6)</td><td></td><td></td><td></td></tr><tr><td>LASSO</td><td>2 (1.3)</td><td></td><td></td><td></td></tr><tr><td>Tree pruning</td><td>1 (0.6)</td><td></td><td></td><td></td></tr><tr><td>Chosen by authors</td><td>2 (1.3)</td><td></td><td></td><td></td></tr><tr><td>Unclear</td><td>20 (12.7)</td><td></td><td></td><td></td></tr></tbody></table>

(continued)
<table><caption>Table II. Characteristics of the included models</caption><thead><tr><th>Characteristics</th><th colspan="2">Developed models, n = 158*</th><th colspan="2">Validated models, n = 108*</th></tr></thead><tbody><tr><td><strong>Participants and predictors</strong></td><td><strong>No. (%)</strong></td><td><strong>Median [min-max]</strong></td><td><strong>No. (%)</strong></td><td><strong>Median [min-max]</strong></td></tr><tr><td>Total sample size—eligible</td><td>157 (99.4)</td><td>778 [27-156 587]</td><td>107 (99.1)</td><td>158 [28-9240]</td></tr><tr><td>Total sample size—analyzed</td><td>141 (89.2)</td><td>474 [22-20 771]</td><td>94 (87.0)</td><td>130 [28-7975]</td></tr><tr><td>Number of outcome events</td><td>155 (98.1)</td><td>232 [11-6121]</td><td>100 (92.6)</td><td>50 [8-2959]</td></tr><tr><td>Number of candidate predictors</td><td>150 (94.9)</td><td>15 [1-50]</td><td>NA</td><td>NA</td></tr><tr><td>Events per predictor for model development</td><td>149 (94.3)</td><td>102.9 [0.33-986.3]</td><td>NA</td><td>NA</td></tr><tr><td>Number of predictors in the final model</td><td>158 (100.0)</td><td>6 [2-21]</td><td>NA</td><td>NA</td></tr><tr><td><strong>Type of predictors in final model</strong></td><td><strong>No. (%)</strong></td><td></td><td><strong>No. (%)</strong></td><td></td></tr><tr><td>Routinely collected data only†</td><td>111 (70.3)</td><td></td><td>59 (37.3)</td><td></td></tr><tr><td>Echocardiographic data</td><td>4 (2.5)</td><td></td><td>2 (1.9)</td><td></td></tr><tr><td>Lung mechanics/imaging</td><td>20 (12.7)</td><td></td><td>47 (43.5)</td><td></td></tr><tr><td>Blood biomarkers</td><td>11 (7.0)</td><td></td><td>0 (0.0)</td><td></td></tr><tr><td>Tracheal biomarkers</td><td>3 (1.9)</td><td></td><td>0 (0.0)</td><td></td></tr><tr><td>Urinary biomarkers</td><td>2 (1.3)</td><td></td><td>0 (0.0)</td><td></td></tr><tr><td>Genetic biomarkers</td><td>2 (1.3)</td><td></td><td>0 (0.0)</td><td></td></tr><tr><td>Combination of above</td><td>5 (3.2)</td><td></td><td>0 (0.0)</td><td></td></tr><tr><td><strong>Timing of model assessment</strong></td><td><strong>No. (%)</strong></td><td></td><td><strong>No. (%)</strong></td><td></td></tr><tr><td>At birth</td><td>7 (4.4)</td><td></td><td>5 (1.5)</td><td></td></tr><tr><td>At admission</td><td>1 (0.6)</td><td></td><td>2 (1.9)</td><td></td></tr><tr><td>1 hour after admission</td><td>0 (0.0)</td><td></td><td>3 (2.8)</td><td></td></tr><tr><td>12 hours after admission</td><td>6 (3.8)</td><td></td><td>15 (13.9)</td><td></td></tr><tr><td>Day 1</td><td>28 (17.7)</td><td></td><td>13 (12.0)</td><td></td></tr><tr><td>Day 2</td><td>2 (1.3)</td><td></td><td>5 (4.6)</td><td></td></tr><tr><td>Day 3</td><td>15 (9.5)</td><td></td><td>15 (13.9)</td><td></td></tr><tr><td>Day 4</td><td>2 (1.3)</td><td></td><td>3 (2.8)</td><td></td></tr><tr><td>Day 6</td><td>4 (2.5)</td><td></td><td>3 (2.8)</td><td></td></tr><tr><td>Day 7</td><td>49 (31.0)</td><td></td><td>23 (21.3)</td><td></td></tr><tr><td>Day 9</td><td>3 (1.9)</td><td></td><td>3 (2.8)</td><td></td></tr><tr><td>Day 10</td><td>2 (1.3)</td><td></td><td>4 (3.7)</td><td></td></tr><tr><td>Day 12</td><td>0 (0.0)</td><td></td><td>3 (2.8)</td><td></td></tr><tr><td>Day 14</td><td>28 (17.7)</td><td></td><td>9 (8.3)</td><td></td></tr><tr><td>Unclear</td><td>11 (7.0)</td><td></td><td>2 (1.9)</td><td></td></tr><tr><td><strong>Methodologic aspects of model development</strong></td><td><strong>No. (%)</strong></td><td></td><td></td><td></td></tr><tr><td><em>Handling of missing data</em></td><td></td><td></td><td></td><td></td></tr><tr><td>Complete-case analysis</td><td>55 (34.8)</td><td></td><td></td><td></td></tr><tr><td>Single/multiple imputation</td><td>52 (32.9)</td><td></td><td></td><td></td></tr><tr><td>Unclear or no information</td><td>51 (32.3)</td><td></td><td></td><td></td></tr><tr><td><em>Handling of linear predictors</em></td><td></td><td></td><td></td><td></td></tr><tr><td>Appropriately</td><td>19 (12.0)</td><td></td><td></td><td></td></tr><tr><td>Not appropriately</td><td>12 (7.6)</td><td></td><td></td><td></td></tr><tr><td>No information</td><td>100 (63.3)</td><td></td><td></td><td></td></tr><tr><td><em>Modeling method</em></td><td></td><td></td><td></td><td></td></tr><tr><td>Logistic regression</td><td>110 (69.6)</td><td></td><td></td><td></td></tr><tr><td>CART analysis</td><td>5 (3.2)</td><td></td><td></td><td></td></tr><tr><td>Other</td><td>97 (61.4)</td><td></td><td></td><td></td></tr><tr><td><em>Selection of predictors in multivariable model</em></td><td></td><td></td><td></td><td></td></tr><tr><td>Preselection based on univariable analysis</td><td>40 (25.3)</td><td></td><td></td><td></td></tr><tr><td>All candidate predictors</td><td>89 (56.3)</td><td></td><td></td><td></td></tr><tr><td>Exclusion of variables from previous model</td><td>1 (0.6)</td><td></td><td></td><td></td></tr><tr><td>Addition of variables to previous model</td><td>3 (1.9)</td><td></td><td></td><td></td></tr><tr><td>LASSO</td><td>1 (0.6)</td><td></td><td></td><td></td></tr><tr><td>Best goodness-of-fit parameters</td><td>2 (1.3)</td><td></td><td></td><td></td></tr><tr><td>Unclear</td><td>22 (13.9)</td><td></td><td></td><td></td></tr><tr><td><em>Selection of predictors in final model</em></td><td></td><td></td><td></td><td></td></tr><tr><td>All predictors forced in model</td><td>72 (45.6)</td><td></td><td></td><td></td></tr><tr><td>All candidate predictors</td><td>3 (1.9)</td><td></td><td></td><td></td></tr><tr><td>Backwards stepwise selection</td><td>17 (10.8)</td><td></td><td></td><td></td></tr><tr><td>Forwards stepwise selection</td><td>21 (13.3)</td><td></td><td></td><td></td></tr><tr><td>Both FW and BW stepwise selection</td><td>9 (5.7)</td><td></td><td></td><td></td></tr><tr><td>Stepwise selection</td><td>8 (5.1)</td><td></td><td></td><td></td></tr><tr><td>Same variables used as in stepwise logistic regression model</td><td>1 (0.6)</td><td></td><td></td><td></td></tr><tr><td>All possible combinations</td><td>1 (0.6)</td><td></td><td></td><td></td></tr><tr><td>Best performance of model</td><td>1 (0.6)</td><td></td><td></td><td></td></tr><tr><td>LASSO</td><td>2 (1.3)</td><td></td><td></td><td></td></tr><tr><td>Tree pruning</td><td>1 (0.6)</td><td></td><td></td><td></td></tr><tr><td>Chosen by authors</td><td>2 (1.3)</td><td></td><td></td><td></td></tr><tr><td>Unclear</td><td>20 (12.7)</td><td></td><td></td><td></td></tr></tbody></table>

(continued)
<table><caption>Table II. Continued</caption><thead><tr><th>Characteristics</th><th>Developed models, n = 158*</th><th>Validated models, n = 108*</th></tr></thead><tbody><tr><td>Internal validation</td><td>78 (49.4)</td><td></td></tr><tr><td><strong>Method of validation</strong></td><td></td><td></td></tr><tr><td>Random split of data</td><td>15 (9.5)</td><td></td></tr><tr><td>Cross-validation</td><td>56 (35.4)</td><td></td></tr><tr><td>Resampling of same data set</td><td>7 (4.4)</td><td></td></tr><tr><td>Unclear</td><td>3 (1.9)</td><td></td></tr><tr><td>External validation in same paper</td><td>16 (10.1)</td><td></td></tr><tr><td><strong>Model presentation</strong></td><td></td><td></td></tr><tr><td>Final full model presented, including intercept</td><td>17 (10.8)</td><td></td></tr><tr><td>Online tool</td><td>5 (3.2)</td><td></td></tr><tr><td>Probability chart</td><td>1 (0.6)</td><td></td></tr><tr><td>Sum score</td><td>5 (3.2)</td><td></td></tr><tr><td>Nomograms</td><td>2 (1.3)</td><td></td></tr><tr><td><strong>Discrimination and calibration of model performances</strong></td><td><strong>No. (%)</strong></td><td><strong>Median [min-max]</strong></td><td><strong>No. (%)</strong></td><td><strong>Median [min-max]</strong></td></tr><tr><td><em>Discrimination</em></td><td></td><td></td><td></td><td></td></tr><tr><td>C-statistic, apparent</td><td>145 (91.8)</td><td>0.84 [0.43-1.00]</td><td>105 (97.2)</td><td>0.77 [0.41-0.97]</td></tr><tr><td>C-statistic after internal validation</td><td>74 (46.8)</td><td>0.86 [0.67-0.91]</td><td></td><td></td></tr><tr><td><em>Calibration apparent</em></td><td></td><td></td><td></td><td></td></tr><tr><td>Hosmer-Lemeshow, No. (%)</td><td>13 (7.5)</td><td></td><td>3 (2.8)</td><td></td></tr><tr><td>Calibration plot, No. (%)</td><td>4 (2.5)</td><td></td><td>0 (0.0)</td><td></td></tr><tr><td>Predicted and observed probabilities, No. (%)</td><td>48 (30.4)</td><td></td><td>2 (1.9)</td><td></td></tr></tbody></table>

BW, backward; CART, Classification and Regression Tree; FW, forward; LASSO, least absolute shrinkage and selection operator; NA, not available.

*The 158 developed models include 141 developed only models and 17 developed models with external validation. The 108 validated models include 87 only validated models and 21 developed models with external validation.

†Routinely collected data including sociodemographic characteristics, pregnancy and neonatal events, and standard laboratory finding.

CIs at the different time points (Figure 4; available at www.jpeds.com). Finally, the pooled c-statistic from the 21 externally validated models predicting death/BPD was 0.82 (95% CI 0.79-0.85, 95% PI 0.66-0.92) (Figure 3, B) and was quite similar at the different time points (Figure 4).

## RoB and Applicability Assessment

All developed models were rated at high RoB in the analysis domain (Figure 5). This was due to issues with small sample size (events per variable <10), inadequate handling of missing data by omitting participant with missing data

<figure><img src="image_2.png" /><figcaption>**Figure 2.** Frequency of variables used in the development models. Labels indicate the number of occurrences of each variable out of the 158 models. The categories indicate how often one of the predictors mentioned below were included in one of the development models.</figcaption></figure>
<table><caption>Table II. Continued</caption><thead><tr><th>Characteristics</th><th>Developed models, n = 158*</th><th>Validated models, n = 108*</th></tr></thead><tbody><tr><td>Internal validation</td><td>78 (49.4)</td><td></td></tr><tr><td><strong>Method of validation</strong></td><td></td><td></td></tr><tr><td>Random split of data</td><td>15 (9.5)</td><td></td></tr><tr><td>Cross-validation</td><td>56 (35.4)</td><td></td></tr><tr><td>Resampling of same data set</td><td>7 (4.4)</td><td></td></tr><tr><td>Unclear</td><td>3 (1.9)</td><td></td></tr><tr><td>External validation in same paper</td><td>16 (10.1)</td><td></td></tr><tr><td><strong>Model presentation</strong></td><td></td><td></td></tr><tr><td>Final full model presented, including intercept</td><td>17 (10.8)</td><td></td></tr><tr><td>Online tool</td><td>5 (3.2)</td><td></td></tr><tr><td>Probability chart</td><td>1 (0.6)</td><td></td></tr><tr><td>Sum score</td><td>5 (3.2)</td><td></td></tr><tr><td>Nomograms</td><td>2 (1.3)</td><td></td></tr><tr><td><strong>Discrimination and calibration of model performances</strong></td><td><strong>No. (%)</strong></td><td><strong>Median [min-max]</strong></td><td><strong>No. (%)</strong></td><td><strong>Median [min-max]</strong></td></tr><tr><td><em>Discrimination</em></td><td></td><td></td><td></td><td></td></tr><tr><td>C-statistic, apparent</td><td>145 (91.8)</td><td>0.84 [0.43-1.00]</td><td>105 (97.2)</td><td>0.77 [0.41-0.97]</td></tr><tr><td>C-statistic after internal validation</td><td>74 (46.8)</td><td>0.86 [0.67-0.91]</td><td></td><td></td></tr><tr><td><em>Calibration apparent</em></td><td></td><td></td><td></td><td></td></tr><tr><td>Hosmer-Lemeshow, No. (%)</td><td>13 (7.5)</td><td></td><td>3 (2.8)</td><td></td></tr><tr><td>Calibration plot, No. (%)</td><td>4 (2.5)</td><td></td><td>0 (0.0)</td><td></td></tr><tr><td>Predicted and observed probabilities, No. (%)</td><td>48 (30.4)</td><td></td><td>2 (1.9)</td><td></td></tr></tbody></table>

BW, backward; CART, Classification and Regression Tree; FW, forward; LASSO, least absolute shrinkage and selection operator; NA, not available.

*The 158 developed models include 141 developed only models and 17 developed models with external validation. The 108 validated models include 87 only validated models and 21 developed models with external validation.

†Routinely collected data including sociodemographic characteristics, pregnancy and neonatal events, and standard laboratory finding.

CIs at the different time points (Figure 4; available at www.jpeds.com). Finally, the pooled c-statistic from the 21 externally validated models predicting death/BPD was 0.82 (95% CI 0.79-0.85, 95% PI 0.66-0.92) (Figure 3, B) and was quite similar at the different time points (Figure 4).

## RoB and Applicability Assessment

All developed models were rated at high RoB in the analysis domain (Figure 5). This was due to issues with small sample size (events per variable <10), inadequate handling of missing data by omitting participant with missing data

<figure><img src="image_3.png" /><figcaption>**Figure 2.** Frequency of variables used in the development models. Labels indicate the number of occurrences of each variable out of the 158 models. The categories indicate how often one of the predictors mentioned below were included in one of the development models.</figcaption></figure>
<figure><img src="image_3.png" /><figcaption>**Figure 3.** Meta-analysis of externally validated models predicting **A**, BPD or **B**, death/BPD at 36 weeks of PMA. \*Prediction model externally validated on outcome moderate or severe BPD. \*\*Prediction model externally validated on outcome grade II or III BPD. (Continues)</figcaption></figure>
<figure><img src="image_4.png" /><figcaption>**Figure 3.** Meta-analysis of externally validated models predicting **A**, BPD or **B**, death/BPD at 36 weeks of PMA. \*Prediction model externally validated on outcome moderate or severe BPD. \*\*Prediction model externally validated on outcome grade II or III BPD. (Continues)</figcaption></figure>
B

<figure><img src="image_4.png" /><figcaption>**Figure 3. Continued.**</figcaption></figure>
B

<figure><img src="image_5.png" /><figcaption>**Figure 3. Continued.**</figcaption></figure>
<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /></figure>

<figure><img src="image_8.png" /><figcaption>**Figure 5.** RoB and applicability assessment for the 158 development and the 108 externally validated model.</figcaption></figure>

from the analysis, and subsequently using complete case analysis instead of using multiple imputation, selection of predictors based on univariable analysis before multivariable modeling, competing risk by death not accounted for, and absence of internal validation as part of model development. In addition, most studies only reported a c-statistic as performance measure of model performances; however, calibration was mostly not or inadequately reported (eg, reporting Hosmer–Lemeshow instead of calibration plot). These items resulted in a high RoB rate for the analysis domain for all developed models. Most of the models scored a low RoB in the participants and predictor domains. In one study, the eligible population could not be determined at the time of model assessment at day 7, because one of the inclusion criteria was ventilation during the first four weeks of life.⁴⁸ Inclusion or exclusion criteria were unclear in 3 studies.³⁰,³⁴,⁷⁰ Four studies considered predictors¹⁹,²³,²⁶,⁵⁹ that were not available at the time of BPD risk assessment. Others did not assess predictors at the same time for all infants³⁴,⁵⁴ or gave unclear definitions for predictors.¹³,⁵⁷ Some models also scored high (11.3%) or unclear (5.7%) RoB on the outcome domain, mainly due to BPD assessment occurring earlier than 36 weeks in infants transferred or discharged before 36 weeks of PMA (Table I). Because all models scored high RoB in one of the domains, the overall RoB was rated as high.

Most of the models had low concern on overall applicability. Concerns on applicability were often due to highly selected populations, when only infants with mechanical

ventilation or with severe respiratory disease were included. Some studies considered radiographic results to define BPD,¹³,¹⁶,²³ which is not recommended anymore. A complete overview of the RoB and applicability assessment per model is shown in Table III (available at www.jpeds.com).

**Model Validation.** All validated models but one were rated at high RoB in the analysis domain (Figure 5), mostly due to a small sample size (<100 outcome events). In 2 studies, external validation was performed on 9 and 28 events, respectively.¹⁴,²¹ Other issues were inadequate handling of missing data, competing risk by death not accounted for, and lack of assessment of calibration. Most of the validated models scored low RoB for participants, predictor, and outcome domains; however, because all models but one scored high RoB in the analysis domain, the overall RoB was rated as high. Most models had also low concerns on applicability (Figure 5, Table III).

## Discussion

This systematic review identified 65 studies that developed or validated a multivariable prediction model for BPD or death/ BPD at 36 weeks of PMA during the 14 first days of life. In total, 158 development and 108 validated models were reviewed. These models included mainly routinely collected data, such as clinical information and routine laboratory findings.

Although discrimination was satisfactory with a median c-statistic of 0.84 in the development models, and 0.77 in the
<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /></figure>

<figure><img src="image_8.png" /></figure>

<figure><img src="image_9.png" /><figcaption>**Figure 5.** RoB and applicability assessment for the 158 development and the 108 externally validated model.</figcaption></figure>

from the analysis, and subsequently using complete case analysis instead of using multiple imputation, selection of predictors based on univariable analysis before multivariable modeling, competing risk by death not accounted for, and absence of internal validation as part of model development. In addition, most studies only reported a c-statistic as performance measure of model performances; however, calibration was mostly not or inadequately reported (eg, reporting Hosmer–Lemeshow instead of calibration plot). These items resulted in a high RoB rate for the analysis domain for all developed models. Most of the models scored a low RoB in the participants and predictor domains. In one study, the eligible population could not be determined at the time of model assessment at day 7, because one of the inclusion criteria was ventilation during the first four weeks of life.⁴⁸ Inclusion or exclusion criteria were unclear in 3 studies.³⁰,³⁴,⁷⁰ Four studies considered predictors¹⁹,²³,²⁶,⁵⁹ that were not available at the time of BPD risk assessment. Others did not assess predictors at the same time for all infants³⁴,⁵⁴ or gave unclear definitions for predictors.¹³,⁵⁷ Some models also scored high (11.3%) or unclear (5.7%) RoB on the outcome domain, mainly due to BPD assessment occurring earlier than 36 weeks in infants transferred or discharged before 36 weeks of PMA (Table I). Because all models scored high RoB in one of the domains, the overall RoB was rated as high.

Most of the models had low concern on overall applicability. Concerns on applicability were often due to highly selected populations, when only infants with mechanical

ventilation or with severe respiratory disease were included. Some studies considered radiographic results to define BPD,¹³,¹⁶,²³ which is not recommended anymore. A complete overview of the RoB and applicability assessment per model is shown in Table III (available at www.jpeds.com).

**Model Validation.** All validated models but one were rated at high RoB in the analysis domain (Figure 5), mostly due to a small sample size (<100 outcome events). In 2 studies, external validation was performed on 9 and 28 events, respectively.¹⁴,²¹ Other issues were inadequate handling of missing data, competing risk by death not accounted for, and lack of assessment of calibration. Most of the validated models scored low RoB for participants, predictor, and outcome domains; however, because all models but one scored high RoB in the analysis domain, the overall RoB was rated as high. Most models had also low concerns on applicability (Figure 5, Table III).

Discussion

This systematic review identified 65 studies that developed or validated a multivariable prediction model for BPD or death/ BPD at 36 weeks of PMA during the 14 first days of life. In total, 158 development and 108 validated models were reviewed. These models included mainly routinely collected data, such as clinical information and routine laboratory findings.

Although discrimination was satisfactory with a median c-statistic of 0.84 in the development models, and 0.77 in the
validated models, these results must be interpreted with caution as all models scored high for RoB or had applicability concerns. The main bias issues were found in the analysis domain of the PROBAST guidelines, with small sample sizes, inappropriate handling of missing data, absence of internal or external validation, and inappropriate report or absence of calibration measures. Applicability issues were mainly due to highly selected populations that were particularly at risk of developing BPD.

In 2013, a systematic review included clinical BPD prediction models published up to 2011.⁶ In contrast with that review, the current review only included studies that defined BPD at 36 weeks of PMA, because this time point has an improved association with long term respiratory and neurological outcomes than the 28 days definition.⁷⁶,⁷⁷ Although most studies used the *Eunice Kennedy Shriver National Institute of Child Health and Human Development 2001 definition* (80%), variability in the BPD definitions used throughout the studies might have contributed to some variability in the c-statistics. A second difference with the 2013 review and a strength of the current review is that all models were assessed with a formal RoB assessment tool, PROBAST.⁸ We noted that all studies had a high RoB, and most studies had a high RoB in the analysis domain. One of the main general flaws in this domain of all existing prediction models is that calibration was rarely assessed or reported. Only 4 studies reported the results of the Hosmer-Lemeshow goodness-of-fit test,¹⁸,²²,²⁶,²⁹ which has been recognized as inadequate, as it is influenced by sample size and gives no indication of direction or magnitude of miscalibration.⁷⁸ A calibration plot is the preferred method to report calibration performance of a prediction model; this finding was also highlighted in the recent systematic review about mortality prediction models in infants born preterm.⁷⁹ Assessing the accuracy of absolute risk estimates is a key element that provides useful information for clinical decision-making and should be evaluated before considering using a prediction model in clinical practice.⁸⁰ Another main flaw in this domain that caused high RoB was the small sample size, with events per variable <10, which increases the risk of overfitting for which correction with internal validation is necessary. Most models did not perform internal validation or performed an inadequate method using random split of data. Only a few models used cross-validation, which is, next to bootstrapping, recommended to account for overfitting and optimism in a developed prediction model. Finally, most models scored high RoB in the analysis domain due to inappropriate or unclear handling of missing data. Some studies excluded those participants with missing data and performed complete case analysis, which leads to biased model performances. Instead, multiple imputation is recommended to reduce the risk of bias.

Research in BPD prediction has shifted toward the identification of early biomarkers or imaging tools. Many reports of univariate associations between biomarkers and BPD have shown promising data.⁸¹,⁸² Very few multivariable

models using blood, tracheal biomarkers, or lung ultrasound have been developed, and none have undergone external validation.⁵²,⁵⁵ Aside from the potential difficulties in assessing these variables in daily clinical practice, the highlighted pitfalls prevent conclusions about the potential usefulness of prediction models using biomarkers or lung ultrasound data in daily care. In addition, most studies used a single center, which limits the generalizability of the developed and/or validated prediction model. The prediction models with the best 3 discriminating performances showed a c-statistic between 0.97 and 1.00, although there is a risk that these models are overfit. These models included predictors regarding lung mechanics, lung imaging and echocardiographic data, and used logistic regression analysis for model development with timing of model assessment in the first week of life. All models had a low sample size with low events per variable, which probably influence the high c-statistic, and 2 models reported the final model including intercept and predictor weights.⁶³,⁷⁴ However, none of these models were internally or externally validated, and although one model presented the calibration performance with pseudo-R², none reported a calibration plot.⁴⁵ Given these flaws, these models have an increased risk of bias, despite their promising discrimination performances. The best three discriminating externally validated models reported c-statistics between 0.96 and 0.97, which also indicates good discrimination.¹³,²¹,⁶³ However, all models had insufficient sample sizes to perform adequate external validation, and no calibration performances were reported. Although these 3 studies showed promising discriminating performances, none of these models can be recommended for implementation in clinical care due to methodologic flaws.

A strength of this review is our meta-analysis provided a quantification of the overall performances, including a PI and heterogeneity of the models. Meta-analysis of the c-statistic of all validated models for the outcome BPD and death/BPD revealed good performance (0.77 and 0.82, respectively). Subsequently, meta-analysis combining models per time point showed an increase in the pooled c-statistic from the validated models for the outcome BPD and death/BPD after the first week of life. This finding is in line with the pathophysiological understanding that BPD is a developing disease during the neonatal period, and future research should investigate whether dynamic models using different predictors over time improve BPD prediction. The calculated PIs indicate that the validated models in the second week of life can perform very differently in a new set of infants, indicating that updating is necessary.⁸³

This review has some limitations. We were unable to perform external validation of the identified prediction models due to frequent inadequate reporting of final prediction model. In addition, we found no dataset that fulfilled all the requirements to perform validation. The ideal dataset should have a sufficient sample size, with a population-based recruitment of infants born very preterm to limit the risk of selection bias, and contain all the predictors needed
validated models, these results must be interpreted with caution as all models scored high for RoB or had applicability concerns. The main bias issues were found in the analysis domain of the PROBAST guidelines, with small sample sizes, inappropriate handling of missing data, absence of internal or external validation, and inappropriate report or absence of calibration measures. Applicability issues were mainly due to highly selected populations that were particularly at risk of developing BPD.

In 2013, a systematic review included clinical BPD prediction models published up to 2011.⁶ In contrast with that review, the current review only included studies that defined BPD at 36 weeks of PMA, because this time point has an improved association with long term respiratory and neurological outcomes than the 28 days definition.⁷⁶,⁷⁷ Although most studies used the *Eunice Kennedy Shriver National Institute of Child Health and Human Development 2001 definition* (80%), variability in the BPD definitions used throughout the studies might have contributed to some variability in the c-statistics. A second difference with the 2013 review and a strength of the current review is that all models were assessed with a formal RoB assessment tool, PROBAST.⁸ We noted that all studies had a high RoB, and most studies had a high RoB in the analysis domain. One of the main general flaws in this domain of all existing prediction models is that calibration was rarely assessed or reported. Only 4 studies reported the results of the Hosmer–Lemeshow goodness-of-fit test,¹⁸,²²,²⁶,²⁹ which has been recognized as inadequate, as it is influenced by sample size and gives no indication of direction or magnitude of miscalibration.⁷⁸ A calibration plot is the preferred method to report calibration performance of a prediction model; this finding was also highlighted in the recent systematic review about mortality prediction models in infants born preterm.⁷⁹ Assessing the accuracy of absolute risk estimates is a key element that provides useful information for clinical decision-making and should be evaluated before considering using a prediction model in clinical practice.⁸⁰ Another main flaw in this domain that caused high RoB was the small sample size, with events per variable <10, which increases the risk of overfitting for which correction with internal validation is necessary. Most models did not perform internal validation or performed an inadequate method using random split of data. Only a few models used cross-validation, which is, next to bootstrapping, recommended to account for overfitting and optimism in a developed prediction model. Finally, most models scored high RoB in the analysis domain due to inappropriate or unclear handling of missing data. Some studies excluded those participants with missing data and performed complete case analysis, which leads to biased model performances. Instead, multiple imputation is recommended to reduce the risk of bias.

Research in BPD prediction has shifted toward the identification of early biomarkers or imaging tools. Many reports of univariate associations between biomarkers and BPD have shown promising data.⁸¹,⁸² Very few multivariable

models using blood, tracheal biomarkers, or lung ultrasound have been developed, and none have undergone external validation.⁵²,⁵⁵ Aside from the potential difficulties in assessing these variables in daily clinical practice, the highlighted pitfalls prevent conclusions about the potential usefulness of prediction models using biomarkers or lung ultrasound data in daily care. In addition, most studies used a single center, which limits the generalizability of the developed and/or validated prediction model. The prediction models with the best 3 discriminating performances showed a c-statistic between 0.97 and 1.00, although there is a risk that these models are overfit. These models included predictors regarding lung mechanics, lung imaging and echocardiographic data, and used logistic regression analysis for model development with timing of model assessment in the first week of life. All models had a low sample size with low events per variable, which probably influence the high c-statistic, and 2 models reported the final model including intercept and predictor weights.⁶³,⁷⁴ However, none of these models were internally or externally validated, and although one model presented the calibration performance with pseudo-R², none reported a calibration plot.⁴⁵ Given these flaws, these models have an increased risk of bias, despite their promising discrimination performances. The best three discriminating externally validated models reported c-statistics between 0.96 and 0.97, which also indicates good discrimination.¹³,²¹,⁶³ However, all models had insufficient sample sizes to perform adequate external validation, and no calibration performances were reported. Although these 3 studies showed promising discriminating performances, none of these models can be recommended for implementation in clinical care due to methodologic flaws.

A strength of this review is our meta-analysis provided a quantification of the overall performances, including a PI and heterogeneity of the models. Meta-analysis of the c-statistic of all validated models for the outcome BPD and death/BPD revealed good performance (0.77 and 0.82, respectively). Subsequently, meta-analysis combining models per time point showed an increase in the pooled c-statistic from the validated models for the outcome BPD and death/BPD after the first week of life. This finding is in line with the pathophysiological understanding that BPD is a developing disease during the neonatal period, and future research should investigate whether dynamic models using different predictors over time improve BPD prediction. The calculated PIs indicate that the validated models in the second week of life can perform very differently in a new set of infants, indicating that updating is necessary.⁸³

This review has some limitations. We were unable to perform external validation of the identified prediction models due to frequent inadequate reporting of final prediction model. In addition, we found no dataset that fulfilled all the requirements to perform validation. The ideal dataset should have a sufficient sample size, with a population-based recruitment of infants born very preterm to limit the risk of selection bias, and contain all the predictors needed
to apply the prediction models, including detailed information on respiratory management, biomarkers that are not routinely collected and imaging data.

In conclusion, many different BPD prediction models have satisfactory performance. However, their actual value in clinical practice remains uncertain as the result of methodologic issues, lack of external validation, and no calibration assessment. Adherence to existing reporting and methodologic guidelines are needed to improve the quality of research on prediction modeling. Future research should aim to validate externally existing models in different countries, assess both discrimination and calibration performances, and conduct impact studies. ■

We thank Shona Kirtley, information specialist in the Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, United Kingdom, for her help in developing the search strategies for this systematic review.

Submitted for publication Jul 15, 2022; last revision received Dec 19, 2022; accepted Jan 15, 2023.

Reprint requests: Michelle Romijn, MD, Emma Children's Hospital, Amsterdam UMC, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands.
E-mail: m.romijn1@amsterdamumc.nl

## References

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2. Twilhaar ES, Wade RM, de Kieviet JF, van Goudoever JB, van Elburg RM, Oosterlaan J. Cognitive outcomes of children born extremely or very preterm since the 1990s and associated risk factors: a meta-analysis and meta-regression. JAMA Pediatr 2018;172:361-7.

3. Hadchouel A, Rousseau J, Rozé JC, Arnaud C, Bellino A, Couderc L, et al. Association between asthma and lung function in adolescents born very preterm: results of the EPIPAGE cohort study. Thorax 2018;73:1174-6.

4. Kuint J, Lerner-Geva L, Chodick G, Boyko V, Shalev V, Reichman B, et al. Rehospitalization through childhood and adolescence: association with neonatal morbidities in infants of very low birth weight. J Pediatr 2017;188:135-41.e2.

5. Higgins RD, Jobe AH, Koso-Thomas M, Bancalari E, Viscardi RM, Hartert TV, et al. Bronchopulmonary dysplasia: executive summary of a workshop. J Pediatr 2018;197:300-8.

6. Onland W, Debray TP, Laughon MM, Miedema M, Cools F, Askie LM, et al. Clinical prediction models for bronchopulmonary dysplasia: a systematic review and external validation study. BMC Pediatr 2013;13:207.

7. Collins GS, Reitsma JB, Altman DG, Moons KGM. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. BMJ 2015;350:g7594.

8. Wolff RF, Moons KGM, Riley RD, Whiting PF, Westwood M, Collins GS, et al. PROBAST: a tool to assess the risk of bias and applicability of prediction model studies. Ann Intern Med 2019;170:51-8.

9. Moons KGM, de Groot JAH, Bouwmeester W, Vergouwe Y, Mallett S, Altman DG, et al. Critical appraisal and data extraction for systematic reviews of prediction modelling studies: the CHARMS checklist. PLoS Med 2014;11:e1001744.

10. Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JPA, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. J Clin Epidemiol 2009;62:e1-34.

11. Snell KI, Ensor J, Debray TP, Moons KG, Riley RD. Meta-analysis of prediction model performance across multiple studies: which scale helps ensure between-study normality for the C-statistic and calibration measures? Stat Methods Med Res 2018;27:3505-22.

12. Damen JA, Pajouheshnia R, Heus P, Moons KGM, Reitsma JB, Scholten RJPM, et al. Performance of the Framingham risk models and pooled cohort equations for predicting 10-year risk of cardiovascular disease: a systematic review and meta-analysis. BMC Med 2019;17:109.

13. Ryan SW, Nycyk J, Shaw BN. Prediction of chronic neonatal lung disease on day 4 of life. Eur J Pediatr 1996;155:668-71.

14. Subhedar NV, Hamdan AH, Ryan SW, Shaw NJ. Pulmonary artery pressure: early predictor of chronic lung disease in preterm infants. Arch Dis Child Fetal Neonatal Ed 1998;78:F20-4.

15. Hentschel J, Friedel C, Maier RF, Bassir C, Obladen M. Predicting chronic lung disease in very low birthweight infants: comparison of 3 scores. J Perinat Med 1998;26:378-83.

16. Yoder BA, Anwar MU, Clark RH. Early prediction of neonatal chronic lung disease: a comparison of three scoring methods. Pediatr Pulmonol 1999;27:388-94.

17. Lui K, Lloyd J, Ang E, Rynn M, Gupta JM. Early changes in respiratory compliance and resistance during the development of bronchopulmonary dysplasia in the era of surfactant therapy. Pediatr Pulmonol 2000;30:282-90.

18. Chien LY, Whyte R, Thiessen P, Walker R, Brabyn D, Lee SK, et al. Snap-II predicts severe intraventricular hemorrhage and chronic lung disease in the neonatal intensive care unit. J Perinatol 2002;22:26-30.

19. Ng PC, Lee CH, Lam CWK, Ma KC, Chan IHS, Wong E, et al. Early pituitary-adrenal response and respiratory outcomes in preterm infants. Arch Dis Child Fetal Neonatal Ed 2004;89:F127-30.

20. Greenough A, Thomas M, Dimitriou G, Williams O, Johnson A, Limb E, et al. Prediction of outcome from the chest radiograph appearance on day 7 of very prematurely born infants. Eur J Pediatr 2004;163:14-8.

21. Kim YD, Kim EAR, Kim KS, Pi SY, Kang W. Scoring method for early prediction of neonatal chronic lung disease using modified respiratory parameters. J Korean Med Sci 2005;20:397-401.

22. Henderson-Smart DJ, Hutchinson JL, Donoghue DA, Evans NJ, Simpson JM, Wright I, et al. Prenatal predictors of chronic lung disease in very preterm infants. Arch Dis Child Fetal Neonatal Ed 2006;91:F40-5.

23. Choi CW, Kim BI, Kim HS, Park JD, Choi JH, Son DW. Increase of interleukin-6 in tracheal aspirate at birth: a predictor of subsequent bronchopulmonary dysplasia in preterm infants. Acta Paediatr 2006;95:38-43.

24. May C, Kavvadia V, Dimitriou G, Greenough A. A scoring system to predict chronic oxygen dependency. Eur J Pediatr 2007;166:235-40.

25. Ambalavanan N, Van Meurs KP, Perritt R, Carlo WA, Ehrenkranz RA, Stevenson DK, et al. Predictors of death or bronchopulmonary dysplasia in preterm infants with respiratory failure. J Perinatol 2008;28:420-6.

26. Subramanian S, El-Mohandes A, Dhanireddy R, Koch MA. Association of bronchopulmonary dysplasia and hypercarbia in ventilated infants with birth weights of 500-1,499 g. Matern Child Health J 2011;15:S17-26.

27. Messerschmidt A, Olischar M, Birnbacher R, Sauer A, Weber M, Puschnig D, et al. Is it possible to make a reliable prognosis within the first hour of life for very low birth weight infants delivered after preterm premature rupture of membranes? Neonatology 2011;99:146-52.

28. Laughon MM, Langer JC, Bose CL, Smith PB, Ambalavanan N, Kennedy KA, et al. Prediction of bronchopulmonary dysplasia by postnatal age in extremely premature infants. Am J Respir Crit Care Med 2011;183:1715-22.

29. Carvalho PRN, Moreira MEL, Sá RAM, Lopes LM. SNAPPE-II application in newborns with very low birth weight: evaluation of adverse outcomes in severe placental dysfunction. J Perinat Med 2011;39:343-7.

30. Ambalavanan N, Walsh M, Bobashev G, Das A, Levine B, Carlo WA, et al. Intercenter differences in bronchopulmonary dysplasia or death among very low birth weight infants. Pediatrics 2011;127:e106-16.

31. Sehgal A, Paul E, Menahem S. Functional echocardiography in staging for ductal disease severity: role in predicting outcomes. Eur J Pediatr 2013;172:179-84.

32. Schneibel KR, Fitzpatrick AM, Ping XD, Brown LAS, Gauthier TW. Inflammatory mediator patterns in tracheal aspirate and their association
to apply the prediction models, including detailed information on respiratory management, biomarkers that are not routinely collected and imaging data.

In conclusion, many different BPD prediction models have satisfactory performance. However, their actual value in clinical practice remains uncertain as the result of methodologic issues, lack of external validation, and no calibration assessment. Adherence to existing reporting and methodologic guidelines are needed to improve the quality of research on prediction modeling. Future research should aim to validate externally existing models in different countries, assess both discrimination and calibration performances, and conduct impact studies. ■

We thank Shona Kirtley, information specialist in the Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, United Kingdom, for her help in developing the search strategies for this systematic review.

Submitted for publication Jul 15, 2022; last revision received Dec 19, 2022; accepted Jan 15, 2023.

Reprint requests: Michelle Romijn, MD, Emma Children's Hospital, Amsterdam UMC, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands.
E-mail: m.romijn1@amsterdamumc.nl

## References

1. Siffel C, Kistler KD, Lewis JFM, Sarda SP. Global incidence of bronchopulmonary dysplasia among extremely preterm infants: a systematic literature review. J Matern Fetal Neonatal Med 2021;34:1721-31.

2. Twilhaar ES, Wade RM, de Kieviet JF, van Goudoever JB, van Elburg RM, Oosterlaan J. Cognitive outcomes of children born extremely or very preterm since the 1990s and associated risk factors: a meta-analysis and meta-regression. JAMA Pediatr 2018;172:361-7.

3. Hadchouel A, Rousseau J, Rozé JC, Arnaud C, Bellino A, Couderc L, et al. Association between asthma and lung function in adolescents born very preterm: results of the EPIPAGE cohort study. Thorax 2018;73:1174-6.

4. Kuint J, Lerner-Geva L, Chodick G, Boyko V, Shalev V, Reichman B, et al. Rehospitalization through childhood and adolescence: association with neonatal morbidities in infants of very low birth weight. J Pediatr 2017;188:135-41.e2.

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8. Wolff RF, Moons KGM, Riley RD, Whiting PF, Westwood M, Collins GS, et al. PROBAST: a tool to assess the risk of bias and applicability of prediction model studies. Ann Intern Med 2019;170:51-8.

9. Moons KGM, de Groot JAH, Bouwmeester W, Vergouwe Y, Mallett S, Altman DG, et al. Critical appraisal and data extraction for systematic reviews of prediction modelling studies: the CHARMS checklist. PLoS Med 2014;11:e1001744.

10. Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JPA, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. J Clin Epidemiol 2009;62:e1-34.

11. Snell KI, Ensor J, Debray TP, Moons KG, Riley RD. Meta-analysis of prediction model performance across multiple studies: which scale helps ensure between-study normality for the C-statistic and calibration measures? Stat Methods Med Res 2018;27:3505-22.

12. Damen JA, Pajouheshnia R, Heus P, Moons KGM, Reitsma JB, Scholten RJPM, et al. Performance of the Framingham risk models and pooled cohort equations for predicting 10-year risk of cardiovascular disease: a systematic review and meta-analysis. BMC Med 2019;17:109.

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14. Subhedar NV, Hamdan AH, Ryan SW, Shaw NJ. Pulmonary artery pressure: early predictor of chronic lung disease in preterm infants. Arch Dis Child Fetal Neonatal Ed 1998;78:F20-4.

15. Hentschel J, Friedel C, Maier RF, Bassir C, Obladen M. Predicting chronic lung disease in very low birthweight infants: comparison of 3 scores. J Perinat Med 1998;26:378-83.

16. Yoder BA, Anwar MU, Clark RH. Early prediction of neonatal chronic lung disease: a comparison of three scoring methods. Pediatr Pulmonol 1999;27:388-94.

17. Lui K, Lloyd J, Ang E, Rynn M, Gupta JM. Early changes in respiratory compliance and resistance during the development of bronchopulmonary dysplasia in the era of surfactant therapy. Pediatr Pulmonol 2000;30:282-90.

18. Chien LY, Whyte R, Thiessen P, Walker R, Brabyn D, Lee SK, et al. Snap-II predicts severe intraventricular hemorrhage and chronic lung disease in the neonatal intensive care unit. J Perinatol 2002;22:26-30.

19. Ng PC, Lee CH, Lam CWK, Ma KC, Chan IHS, Wong E, et al. Early pituitary-adrenal response and respiratory outcomes in preterm infants. Arch Dis Child Fetal Neonatal Ed 2004;89:F127-30.

20. Greenough A, Thomas M, Dimitriou G, Williams O, Johnson A, Limb E, et al. Prediction of outcome from the chest radiograph appearance on day 7 of very prematurely born infants. Eur J Pediatr 2004;163:14-8.

21. Kim YD, Kim EAR, Kim KS, Pi SY, Kang W. Scoring method for early prediction of neonatal chronic lung disease using modified respiratory parameters. J Korean Med Sci 2005;20:397-401.

22. Henderson-Smart DJ, Hutchinson JL, Donoghue DA, Evans NJ, Simpson JM, Wright I, et al. Prenatal predictors of chronic lung disease in very preterm infants. Arch Dis Child Fetal Neonatal Ed 2006;91:F40-5.

23. Choi CW, Kim BI, Kim HS, Park JD, Choi JH, Son DW. Increase of interleukin-6 in tracheal aspirate at birth: a predictor of subsequent bronchopulmonary dysplasia in preterm infants. Acta Paediatr 2006;95:38-43.

24. May C, Kavvadia V, Dimitriou G, Greenough A. A scoring system to predict chronic oxygen dependency. Eur J Pediatr 2007;166:235-40.

25. Ambalavanan N, Van Meurs KP, Perritt R, Carlo WA, Ehrenkranz RA, Stevenson DK, et al. Predictors of death or bronchopulmonary dysplasia in preterm infants with respiratory failure. J Perinatol 2008;28:420-6.

26. Subramanian S, El-Mohandes A, Dhanireddy R, Koch MA. Association of bronchopulmonary dysplasia and hypercarbia in ventilated infants with birth weights of 500-1,499 g. Matern Child Health J 2011;15:S17-26.

27. Messerschmidt A, Olischar M, Birnbacher R, Sauer A, Weber M, Puschnig D, et al. Is it possible to make a reliable prognosis within the first hour of life for very low birth weight infants delivered after preterm premature rupture of membranes? Neonatology 2011;99:146-52.

28. Laughon MM, Langer JC, Bose CL, Smith PB, Ambalavanan N, Kennedy KA, et al. Prediction of bronchopulmonary dysplasia by postnatal age in extremely premature infants. Am J Respir Crit Care Med 2011;183:1715-22.

29. Carvalho PRN, Moreira MEL, Sá RAM, Lopes LM. SNAPPE-II application in newborns with very low birth weight: evaluation of adverse outcomes in severe placental dysfunction. J Perinat Med 2011;39:343-7.

30. Ambalavanan N, Walsh M, Bobashev G, Das A, Levine B, Carlo WA, et al. Intercenter differences in bronchopulmonary dysplasia or death among very low birth weight infants. Pediatrics 2011;127:e106-16.

31. Sehgal A, Paul E, Menahem S. Functional echocardiography in staging for ductal disease severity: role in predicting outcomes. Eur J Pediatr 2013;172:179-84.

32. Schneibel KR, Fitzpatrick AM, Ping XD, Brown LAS, Gauthier TW. Inflammatory mediator patterns in tracheal aspirate and their association
with bronchopulmonary dysplasia in very low birth weight neonates. J Perinatol 2013;33:383-7.

33. Truog WE, Nelin LD, Das A, Kendrick DE, Bell EF, Carlo WA, et al. Inhaled nitric oxide usage in preterm infants in the NICHD Neonatal Research Network: inter-site variation and propensity evaluation. J Perinatol 2014;34:842-6.

34. Popova AP, Cui TX, Kaciroti N, Goldsmith AM, Linn MJ, Pryhuber GS, et al. Tracheal aspirate levels of the matricellular protein SPARC predict development of bronchopulmonary dysplasia. PLoS One 2015;10:e0144122.

35. Kandasamy J, Roane C, Szalai A, Ambalavanan N. Serum eotaxin-1 is increased in extremely-low-birth-weight infants with bronchopulmonary dysplasia or death. Pediatr Res 2015;78:498-504.

36. El-Khuffash A, James AT, Corcoran JD, Dicker P, Franklin O, Elsayed YN, et al. A patent ductus arteriosus severity score predicts chronic lung disease or death before discharge. J Pediatr 2015;167:1354-61.e2.

37. Wai KC, Kohn MA, Ballard RA, Truog WE, Black DM, Asselin JM, et al. Early cumulative supplemental oxygen predicts bronchopulmonary dysplasia in high risk extremely low gestational age newborns. J Pediatr 2016;177:97-102.e2.

38. Sullivan BA, McClure C, Hicks J, Lake DE, Moorman JR, Fairchild KD. Early heart rate characteristics predict death and morbidities in preterm infants. J Pediatr 2016;174:57-62.

39. Özcan B, Kavurt AS, Aydemir Ö, Genççek Z, Baş AY, Demirel N. SNAPPE-II and risk of neonatal morbidities in very low birth weight preterm infants. Turk J Pediatr 2017;59:105-12.

40. Kandasamy J, Olave N, Ballinger SW, Ambalavanan N. Vascular endothelial mitochondrial function predicts death or pulmonary outcomes in preterm infants. Am J Respir Crit Care Med 2017;196:1040-9.

41. Sullivan BA, Wallman-Stokes A, Isler J, Sahni R, Moorman JR, Fairchild KD, et al. Early pulse oximetry data improves prediction of death and adverse outcomes in a two-center cohort of very low birth weight infants. Am J Perinatol 2018;35:1331-8.

42. Gulliver K, Yoder BA. Bronchopulmonary dysplasia: effect of altitude correction and role for the Neonatal Research Network Prediction Algorithm. J Perinatol 2018;38:1046-50.

43. Boghossian NS, Geraci M, Edwards EM, Horbar JD. Neonatal and fetal growth charts to identify preterm infants <30 weeks gestation at risk of adverse outcomes. Am J Obstet Gynecol 2018;219:195.e1-14.

44. Bentsen MH, Markestad T, Halvorsen T. Ventilator flow data predict bronchopulmonary dysplasia in extremely premature neonates. ERJ Open Res 2018;4.

45. Veneroni C, Wallström L, Sindelar R, Dellaca' RL. Oscillatory respiratory mechanics on the first day of life improves prediction of respiratory outcomes in extremely preterm newborns. Pediatr Res 2019;85:312-7.

46. Valenzuela-Stutman D, Marshall G, Tapia JL, Mariani G, Bancalari A, Gonzalez Á, et al. Bronchopulmonary dysplasia: risk prediction models for very-low- birth-weight infants. J Perinatol 2019;39:1275-81.

47. Lee SM, Lee MH, Chang YS, the Korean Neonatal Network. The Clinical Risk Index for Babies II for prediction of time-dependent mortality and short-term morbidities in very low birth weight infants. Neonatology 2019;116:244-51.

48. Jung YH, Jang J, Kim HS, Shin SH, Choi CW, Kim EK, et al. Respiratory severity score as a predictive factor for severe bronchopulmonary dysplasia or death in extremely preterm infants. BMC Pediatr 2019;19:121.

49. Fairchild KD, Nagraj VP, Sullivan BA, Moorman JR, Lake DE. Oxygen desaturations in the early neonatal period predict development of bronchopulmonary dysplasia. Pediatr Res 2019;85:987-93.

50. Beltempo M, Shah PS, Ye XY, Afifi J, Lee S, McMillan DD, et al. SNAP-II for prediction of mortality and morbidity in extremely preterm infants. J Matern Fetal Neonatal Med 2019;32:2694-701.

51. Alvarez-Fuente M, Moreno L, Lopez-Ortego P, Arruza L, Avila- Alvarez A, Muro M, et al. Exploring clinical, echocardiographic and molecular biomarkers to predict bronchopulmonary dysplasia. PLoS One 2019;14:e0213210.

52. Alonso-Ojembarrena A, Serna-Guerediaga I, de Las Heras-Martin M, Rodeno-Fernandez L, Aldecoa-Bilbao V, Gregorio-Hernandez R, et al. The predictive value of lung ultrasound scores in developing bronchopulmonary dysplasia: a prospective multicenter diagnostic accuracy study. Chest 2021;160:1006-16.

53. Sotodate G, Oyama K, Matsumoto A, Konishi Y, Toya Y, Takashimizu N. Predictive ability of neonatal illness severity scores for early death in extremely premature infants. J Matern Fetal Neonatal Med 2022;35:846-51.

54. Sharma A, Xin Y, Chen X, Sood BG. Early prediction of moderate to severe bronchopulmonary dysplasia in extremely premature infants. Pediatr Neonatol 2020;61:290-9.

55. Oulego-Erroz I, Alonso-Quintela P, Terroba-Seara S, Jiménez-González A, Rodríguez-Blanco S. Early assessment of lung aeration using an ultrasound score as a biomarker of developing bronchopulmonary dysplasia: a prospective observational study. J Perinatol 2021;41:62-8.

56. Bhattacharjee I, Das A, Collin M, Aly H. Predicting outcomes of mechanically ventilated premature infants using respiratory severity score. J Matern Fetal Neonatal Med 2022;35:4620-7.

57. Aldecoa-Bilbao V, Velilla M, Teresa-Palacio M, Esponera CB, Barbero AH, Sin-Soler M, et al. Lung ultrasound in bronchopulmonary dysplasia: patterns and predictors in very preterm infants. Neonatology 2021;118:537-45.

58. Baud O, Laughon M, Lehert P. Survival without bronchopulmonary dysplasia of extremely preterm infants: a predictive model at birth. Neonatology 2021;118:385-93.

59. Dai D, Chen H, Dong X, Chen J, Mei M, Lu Y, et al. Bronchopulmonary dysplasia predicted by developing a machine learning model of genetic and clinical information. Front Genet 2021;12:689071.

60. Gerull R, Neumann RP, Atkinson A, Bernasconi L, Schulzke SM, Wellmann S. Respiratory morbidity in preterm infants predicted by natriuretic peptide (MR-proANP) and endothelin-1 (CT-proET-1). Pediatr Res 2022;91:1478-84.

61. Khurshid F, Coo H, Khalil A, Messiha J, Ting JY, Wong J, et al. Comparison of multivariable logistic regression and machine learning models for predicting bronchopulmonary dysplasia or death in very preterm infants. Front Pediatr 2021;9:759776.

62. Liu X, Lv X, Jin D, Li H, Wu H. Lung ultrasound predicts the development of bronchopulmonary dysplasia: a prospective observational diagnostic accuracy study. Eur J Pediatr 2021;180:2781-9.

63. Mohamed A, Mohsen N, Diambomba Y, Lashin A, Louis D, Elsayed Y, et al. Lung ultrasound for prediction of bronchopulmonary dysplasia in extreme preterm neonates: a prospective diagnostic cohort study. J Pediatr 2021;238:187-92.e2.

64. Shim SY, Cho SJ, Yun JY, Kim MH, Park EA. The prediction of bronchopulmonary dysplasia in very low birth weight infants through clinical indicators within 1 hour of delivery. J Korean Med Sci 2021;36:e81.

65. Song M, Lei M, Luo C, Shi Z, Cheng X, Ding W, et al. Development of a nomogram for moderate-to-severe bronchopulmonary dysplasia or death: role of N-terminal pro-brain natriuretic peptide as a biomarker. Front Pediatr 2021;9:727362.

66. Soullane S, Patel S, Claveau M, Wazneh L, Sant'Anna G, Beltempo M. Fluid status in the first 10 days of life and death/bronchopulmonary dysplasia among preterm infants. Pediatr Res 2021;90:353-8.

67. Ushida T, Moriyama Y, Nakatochi M, Kobayashi Y, Imai K, Nakano-Kobayashi T, et al. Antenatal prediction models for short- and medium-term outcomes in preterm infants. Acta Obstet Gynecol Scand 2021;100:1089-96.

68. Woods PL, Woods A, Gill AW, Stoecklin B. Early lung ultrasound affords little to the prediction of bronchopulmonary dysplasia. Arch Dis Child Fetal Neonatal Ed 2021;106:657-62.

69. Zhang R, Xu FL, Li WL, Qin FY, Jin XY, Zhang Y, et al. Construction of early risk prediction models for bronchopulmonary dysplasia in preterm infants. Zhong Guo Dang Dai Er Ke Za Zhi 2021;23:994-1001.

70. Ahmed S, Odumade OA, van Zalm P, Smolen KK, Fujimura K, Muntel J, et al. Urine proteomics for noninvasive monitoring of biomarkers in bronchopulmonary dysplasia. Neonatology 2022;119:193-203.
with bronchopulmonary dysplasia in very low birth weight neonates. J Perinatol 2013;33:383-7.

33. Truog WE, Nelin LD, Das A, Kendrick DE, Bell EF, Carlo WA, et al. Inhaled nitric oxide usage in preterm infants in the NICHD Neonatal Research Network: inter-site variation and propensity evaluation. J Perinatol 2014;34:842-6.

34. Popova AP, Cui TX, Kaciroti N, Goldsmith AM, Linn MJ, Pryhuber GS, et al. Tracheal aspirate levels of the matricellular protein SPARC predict development of bronchopulmonary dysplasia. PLoS One 2015;10:e0144122.

35. Kandasamy J, Roane C, Szalai A, Ambalavanan N. Serum eotaxin-1 is increased in extremely-low-birth-weight infants with bronchopulmonary dysplasia or death. Pediatr Res 2015;78:498-504.

36. El-Khuffash A, James AT, Corcoran JD, Dicker P, Franklin O, Elsayed YN, et al. A patent ductus arteriosus severity score predicts chronic lung disease or death before discharge. J Pediatr 2015;167:1354-61.e2.

37. Wai KC, Kohn MA, Ballard RA, Truog WE, Black DM, Asselin JM, et al. Early cumulative supplemental oxygen predicts bronchopulmonary dysplasia in high risk extremely low gestational age newborns. J Pediatr 2016;177:97-102.e2.

38. Sullivan BA, McClure C, Hicks J, Lake DE, Moorman JR, Fairchild KD. Early heart rate characteristics predict death and morbidities in preterm infants. J Pediatr 2016;174:57-62.

39. Özcan B, Kavurt AS, Aydemir Ö, Genççek Z, Baş AY, Demirel N. SNAPPE-II and risk of neonatal morbidities in very low birth weight preterm infants. Turk J Pediatr 2017;59:105-12.

40. Kandasamy J, Olave N, Ballinger SW, Ambalavanan N. Vascular endothelial mitochondrial function predicts death or pulmonary outcomes in preterm infants. Am J Respir Crit Care Med 2017;196:1040-9.

41. Sullivan BA, Wallman-Stokes A, Isler J, Sahni R, Moorman JR, Fairchild KD, et al. Early pulse oximetry data improves prediction of death and adverse outcomes in a two-center cohort of very low birth weight infants. Am J Perinatol 2018;35:1331-8.

42. Gulliver K, Yoder BA. Bronchopulmonary dysplasia: effect of altitude correction and role for the Neonatal Research Network Prediction Algorithm. J Perinatol 2018;38:1046-50.

43. Boghossian NS, Geraci M, Edwards EM, Horbar JD. Neonatal and fetal growth charts to identify preterm infants <30 weeks gestation at risk of adverse outcomes. Am J Obstet Gynecol 2018;219:195.e1-14.

44. Bentsen MH, Markestad T, Halvorsen T. Ventilator flow data predict bronchopulmonary dysplasia in extremely premature neonates. ERJ Open Res 2018;4.

45. Veneroni C, Wallström L, Sindelar R, Dellaca' RL. Oscillatory respiratory mechanics on the first day of life improves prediction of respiratory outcomes in extremely preterm newborns. Pediatr Res 2019;85:312-7.

46. Valenzuela-Stutman D, Marshall G, Tapia JL, Mariani G, Bancalari A, Gonzalez Á, et al. Bronchopulmonary dysplasia: risk prediction models for very-low- birth-weight infants. J Perinatol 2019;39:1275-81.

47. Lee SM, Lee MH, Chang YS, the Korean Neonatal Network. The Clinical Risk Index for Babies II for prediction of time-dependent mortality and short-term morbidities in very low birth weight infants. Neonatology 2019;116:244-51.

48. Jung YH, Jang J, Kim HS, Shin SH, Choi CW, Kim EK, et al. Respiratory severity score as a predictive factor for severe bronchopulmonary dysplasia or death in extremely preterm infants. BMC Pediatr 2019;19:121.

49. Fairchild KD, Nagraj VP, Sullivan BA, Moorman JR, Lake DE. Oxygen desaturations in the early neonatal period predict development of bronchopulmonary dysplasia. Pediatr Res 2019;85:987-93.

50. Beltempo M, Shah PS, Ye XY, Afifi J, Lee S, McMillan DD, et al. SNAP-II for prediction of mortality and morbidity in extremely preterm infants. J Matern Fetal Neonatal Med 2019;32:2694-701.

51. Alvarez-Fuente M, Moreno L, Lopez-Ortego P, Arruza L, Avila-Alvarez A, Muro M, et al. Exploring clinical, echocardiographic and molecular biomarkers to predict bronchopulmonary dysplasia. PLoS One 2019;14:e0213210.

52. Alonso-Ojembarrena A, Serna-Guerediaga I, de Las Heras-Martin M, Rodeno-Fernandez L, Aldecoa-Bilbao V, Gregorio-Hernandez R, et al. The predictive value of lung ultrasound scores in developing bronchopulmonary dysplasia: a prospective multicenter diagnostic accuracy study. Chest 2021;160:1006-16.

53. Sotodate G, Oyama K, Matsumoto A, Konishi Y, Toya Y, Takashimizu N. Predictive ability of neonatal illness severity scores for early death in extremely premature infants. J Matern Fetal Neonatal Med 2022;35:846-51.

54. Sharma A, Xin Y, Chen X, Sood BG. Early prediction of moderate to severe bronchopulmonary dysplasia in extremely premature infants. Pediatr Neonatol 2020;61:290-9.

55. Oulego-Erroz I, Alonso-Quintela P, Terroba-Seara S, Jiménez-González A, Rodríguez-Blanco S. Early assessment of lung aeration using an ultrasound score as a biomarker of developing bronchopulmonary dysplasia: a prospective observational study. J Perinatol 2021;41:62-8.

56. Bhattacharjee I, Das A, Collin M, Aly H. Predicting outcomes of mechanically ventilated premature infants using respiratory severity score. J Matern Fetal Neonatal Med 2022;35:4620-7.

57. Aldecoa-Bilbao V, Velilla M, Teresa-Palacio M, Esponera CB, Barbero AH, Sin-Soler M, et al. Lung ultrasound in bronchopulmonary dysplasia: patterns and predictors in very preterm infants. Neonatology 2021;118:537-45.

58. Baud O, Laughon M, Lehert P. Survival without bronchopulmonary dysplasia of extremely preterm infants: a predictive model at birth. Neonatology 2021;118:385-93.

59. Dai D, Chen H, Dong X, Chen J, Mei M, Lu Y, et al. Bronchopulmonary dysplasia predicted by developing a machine learning model of genetic and clinical information. Front Genet 2021;12:689071.

60. Gerull R, Neumann RP, Atkinson A, Bernasconi L, Schulzke SM, Wellmann S. Respiratory morbidity in preterm infants predicted by natriuretic peptide (MR-proANP) and endothelin-1 (CT-proET-1). Pediatr Res 2022;91:1478-84.

61. Khurshid F, Coo H, Khalil A, Messiha J, Ting JY, Wong J, et al. Comparison of multivariable logistic regression and machine learning models for predicting bronchopulmonary dysplasia or death in very preterm infants. Front Pediatr 2021;9:759776.

62. Liu X, Lv X, Jin D, Li H, Wu H. Lung ultrasound predicts the development of bronchopulmonary dysplasia: a prospective observational diagnostic accuracy study. Eur J Pediatr 2021;180:2781-9.

63. Mohamed A, Mohsen N, Diambomba Y, Lashin A, Louis D, Elsayed Y, et al. Lung ultrasound for prediction of bronchopulmonary dysplasia in extreme preterm neonates: a prospective diagnostic cohort study. J Pediatr 2021;238:187-92.e2.

64. Shim SY, Cho SJ, Yun JY, Kim MH, Park EA. The prediction of bronchopulmonary dysplasia in very low birth weight infants through clinical indicators within 1 hour of delivery. J Korean Med Sci 2021;36:e81.

65. Song M, Lei M, Luo C, Shi Z, Cheng X, Ding W, et al. Development of a nomogram for moderate-to-severe bronchopulmonary dysplasia or death: role of N-terminal pro-brain natriuretic peptide as a biomarker. Front Pediatr 2021;9:727362.

66. Soullane S, Patel S, Claveau M, Wazneh L, Sant'Anna G, Beltempo M. Fluid status in the first 10 days of life and death/bronchopulmonary dysplasia among preterm infants. Pediatr Res 2021;90:353-8.

67. Ushida T, Moriyama Y, Nakatochi M, Kobayashi Y, Imai K, Nakano-Kobayashi T, et al. Antenatal prediction models for short- and medium-term outcomes in preterm infants. Acta Obstet Gynecol Scand 2021;100:1089-96.

68. Woods PL, Woods A, Gill AW, Stoecklin B. Early lung ultrasound affords little to the prediction of bronchopulmonary dysplasia. Arch Dis Child Fetal Neonatal Ed 2021;106:657-62.

69. Zhang R, Xu FL, Li WL, Qin FY, Jin XY, Zhang Y, et al. Construction of early risk prediction models for bronchopulmonary dysplasia in preterm infants. Zhong Guo Dang Dai Er Ke Za Zhi 2021;23:994-1001.

70. Ahmed S, Odumade OA, van Zalm P, Smolen KK, Fujimura K, Muntel J, et al. Urine proteomics for noninvasive monitoring of biomarkers in bronchopulmonary dysplasia. Neonatology 2022;119:193-203.
71. Alonso-Ojembarrena A, Méndez-Abad P, Alonso-Quintela P, Zafra-Rodríguez P, Oulego-Erroz I, Lubián-López SP. Lung ultrasound score has better diagnostic ability than NT-proBNP to predict moderate-severe bronchopulmonary dysplasia. Eur J Pediatr 2022;181:3013-21.

72. Greenberg RG, McDonald SA, Laughon MM, et al, On behalf of Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network. Online clinical tool to estimate risk of bronchopulmonary dysplasia in extremely preterm infants. Arch Dis Child Fetal Neonatal Ed 2022;107:638-43.

73. Kindt ASD, Förster KM, Cochius-den Otter SCM, Flemmer AW, Hauck SM, Flatley A, et al. Validation of disease-specific biomarkers for the early detection of bronchopulmonary dysplasia. Pediatr Res 2023;93:625-32.

74. Umapathi KK, Muller B, Sosnowski C, Thavamani A, Murphy J, Awad S, et al. A novel patent ductus arteriosus severity score to predict clinical outcomes in premature neonates. J Cardiovasc Dev Dis 2022;9:114.

75. Zayat N, Truffert P, Drumez E, Duhamel A, Labreuche J, Zemlin M, et al. Systemic steroids in preventing bronchopulmonary dysplasia (BPD): neurodevelopmental outcome according to the risk of BPD in the EPICE cohort. Int J Environ Res Public Health 2022;19:5600.

76. Isayama T, Lee SK, Yang J, Lee D, Daspal S, Dunn M, et al. Revisiting the definition of bronchopulmonary dysplasia: effect of changing panoply of respiratory support for preterm neonates. JAMA Pediatr 2017;171:271-9.

77. Jensen EA, Dysart K, Gantz MG, McDonald S, Bamat NA, Keszler M, et al. The diagnosis of bronchopulmonary dysplasia in very preterm infants. An evidence-based approach. Am J Respir Crit Care Med 2019;200:751-9.

78. Moons KGM, Wolff RF, Riley RD, Whiting PF, Westwood M, Collins GS, et al. PROBAST: a tool to assess risk of bias and applicability of prediction model studies: explanation and elaboration. Ann Intern Med 2019;170:W1-33.

79. van Beek PE, Andriessen P, Onland W, Schuit E. Prognostic models predicting mortality in preterm infants: systematic review and meta-analysis. Pediatrics 2021;147.

80. Alba AC, Agoritsas T, Walsh M, Hanna S, Iorio A, Devereaux PJ, et al. Discrimination and calibration of clinical prediction models: users' guides to the medical literature. JAMA 2017;318:1377-84.

81. Zhang ZQ, Huang XM, Lu H. Early biomarkers as predictors for bronchopulmonary dysplasia in preterm infants: a systematic review. Eur J Pediatr 2014;173:15-23.

82. Xiong T, Kulkarni M, Gokulakrishnan G, Shivanna B, Pammi M. Natriuretic peptides in bronchopulmonary dysplasia: a systematic review. J Perinatol 2020;40:607-15.

83. de Jong VMT, Moons KGM, Eijkemans MJC, Riley RD, Debray TPA. Developing more generalizable prediction models from pooled studies and large clustered data sets. Stat Med 2021;40:3533-59.
71. Alonso-Ojembarrena A, Méndez-Abad P, Alonso-Quintela P, Zafra-Rodríguez P, Oulego-Erroz I, Lubián-López SP. Lung ultrasound score has better diagnostic ability than NT-proBNP to predict moderate-severe bronchopulmonary dysplasia. Eur J Pediatr 2022;181:3013-21.

72. Greenberg RG, McDonald SA, Laughon MM, et al, On behalf of Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network. Online clinical tool to estimate risk of bronchopulmonary dysplasia in extremely preterm infants. Arch Dis Child Fetal Neonatal Ed 2022;107:638-43.

73. Kindt ASD, Förster KM, Cochius-den Otter SCM, Flemmer AW, Hauck SM, Flatley A, et al. Validation of disease-specific biomarkers for the early detection of bronchopulmonary dysplasia. Pediatr Res 2023;93:625-32.

74. Umapathi KK, Muller B, Sosnowski C, Thavamani A, Murphy J, Awad S, et al. A novel patent ductus arteriosus severity score to predict clinical outcomes in premature neonates. J Cardiovasc Dev Dis 2022;9:114.

75. Zayat N, Truffert P, Drumez E, Duhamel A, Labreuche J, Zemlin M, et al. Systemic steroids in preventing bronchopulmonary dysplasia (BPD): neurodevelopmental outcome according to the risk of BPD in the EPICE cohort. Int J Environ Res Public Health 2022;19:5600.

76. Isayama T, Lee SK, Yang J, Lee D, Daspal S, Dunn M, et al. Revisiting the definition of bronchopulmonary dysplasia: effect of changing panoply of respiratory support for preterm neonates. JAMA Pediatr 2017;171:271-9.

77. Jensen EA, Dysart K, Gantz MG, McDonald S, Bamat NA, Keszler M, et al. The diagnosis of bronchopulmonary dysplasia in very preterm infants. An evidence-based approach. Am J Respir Crit Care Med 2019;200:751-9.

78. Moons KGM, Wolff RF, Riley RD, Whiting PF, Westwood M, Collins GS, et al. PROBAST: a tool to assess risk of bias and applicability of prediction model studies: explanation and elaboration. Ann Intern Med 2019;170:W1-33.

79. van Beek PE, Andriessen P, Onland W, Schuit E. Prognostic models predicting mortality in preterm infants: systematic review and meta-analysis. Pediatrics 2021;147.

80. Alba AC, Agoritsas T, Walsh M, Hanna S, Iorio A, Devereaux PJ, et al. Discrimination and calibration of clinical prediction models: users' guides to the medical literature. JAMA 2017;318:1377-84.

81. Zhang ZQ, Huang XM, Lu H. Early biomarkers as predictors for bronchopulmonary dysplasia in preterm infants: a systematic review. Eur J Pediatr 2014;173:15-23.

82. Xiong T, Kulkarni M, Gokulakrishnan G, Shivanna B, Pammi M. Natriuretic peptides in bronchopulmonary dysplasia: a systematic review. J Perinatol 2020;40:607-15.

83. de Jong VMT, Moons KGM, Eijkemans MJC, Riley RD, Debray TPA. Developing more generalizable prediction models from pooled studies and large clustered data sets. Stat Med 2021;40:3533-59.
<figure><img src="image_9.png" /><figcaption>**Figure 1.** Flow diagram. BPD, bronchopulmonary dysplasia.</figcaption></figure>
<figure><img src="image_10.png" /><figcaption>**Figure 1.** Flow diagram. BPD, bronchopulmonary dysplasia.</figcaption></figure>
<figure><img src="image_10.png" /></figure>

Day 1 – Day 7

<figure><img src="image_11.png" /></figure>

Day 8 – Day 14

<figure><img src="image_12.png" /></figure>

<figure><img src="image_13.png" /></figure>

Day 1 – Day 7

<figure><img src="image_14.png" /></figure>

Day 8 – Day 14

<figure><img src="image_15.png" /><figcaption>**Figure 4.** Meta-analysis of externally validated models by timing assessment, predicting BPD (**left**) and death/BPD (**right**).</figcaption></figure>

*Prediction model externally validated on outcome moderate or severe BPD. **Prediction model externally validated on outcome grade II or III BPD.
<figure><img src="image_11.png" /></figure>

Day 1 – Day 7

<figure><img src="image_12.png" /></figure>

Day 8 – Day 14

<figure><img src="image_13.png" /></figure>

<figure><img src="image_14.png" /></figure>

Day 1 – Day 7

<figure><img src="image_15.png" /></figure>

Day 8 – Day 14

<figure><img src="image_16.png" /><figcaption>**Figure 4.** Meta-analysis of externally validated models by timing assessment, predicting BPD (**left**) and death/BPD (**right**).</figcaption></figure>

*Prediction model externally validated on outcome moderate or severe BPD. **Prediction model externally validated on outcome grade II or III BPD.
<figure><img src="image_16.png" /></figure>

<table><caption>Table I. Description of included studies</caption><thead><tr><th>First author</th><th>Year of publication, country</th><th>Period of data collection</th><th>Study design</th><th>Inclusion criteria</th><th>Number of participants eligible/analyzed</th><th>Number of outcome events</th><th>Gestational age, wk, mean (SD) or median [IQR]</th><th>Birth weight, g, mean ± SD or median [IQR]</th><th>Timing of model assessment</th><th>Defined outcome</th></tr></thead><tbody><tr><td>Development studies Ahmed<sup>70</sup></td><td>2022, USA</td><td>1997-2015</td><td>Nested case-control, single center</td><td>Gestational age &lt;29 wk</td><td>42/42</td><td>21</td><td>25.9 (1.18)</td><td>809 (175)</td><td>Before 72H</td><td>Moderate/severe BPD supplemental oxygen at 36 weeks of PMA</td></tr><tr><td>Alonso-Ojemarrena<sup>71</sup></td><td>2022, Spain</td><td>2017-2021</td><td>Case-control, multicenter (n = 2)</td><td>Gestational age &lt;32 wk</td><td>199/133</td><td>27</td><td>no BPD group 30 [29-31]<br>BPD group 27 [25-29]</td><td>no BPD 1300 [1100-1445]; BPD 905 (620-1000)</td><td>D1, D3, D7, D14</td><td>Moderate/severe BPD: any respiratory support at 36 weeks of PMA</td></tr><tr><td>Greenberg<sup>72</sup></td><td>2022, USA</td><td>2011-2017</td><td>Prospective cohort, multicenter (n = 38)</td><td>Gestational age 23<sup>0/7</sup> to 28<sup>6/7</sup> wk; BW 501-1250 g;</td><td>9843/9181</td><td>BPD grade 1 2 795; grade 2 1 526; grade 3 551; death 1052</td><td>25.9 (1.57)</td><td>850 (192)</td><td>D1, D3, D7, D14</td><td>Grade 1 BPD/grade 2 BPD/grade 3 BPD/ death according to the 2019 definition by Jensen</td></tr><tr><td>Kindt<sup>73</sup></td><td>2022, Germany</td><td>No information</td><td>Prospective cohort, single center</td><td>Gestational age &lt;32 wk</td><td>55/52</td><td>13</td><td>27.2 (range 23.2-30.6)</td><td>798 [510-1590]</td><td>First week</td><td>Moderate or severe BPD according to NICHD 2001 definition</td></tr><tr><td>Umapathi<sup>74</sup></td><td>2022, USA</td><td>No information</td><td>Prospective cohort, single center</td><td>Gestational age &lt;32 wk</td><td>101/98</td><td>34</td><td>28.9 (1.91)</td><td>122 (319)</td><td>First week</td><td>Moderate/severe BPD or death: supplemental oxygen at 36 weeks of PMA</td></tr><tr><td>Zayat<sup>75</sup></td><td>2022, Europe</td><td>2011-2012</td><td>Prospective cohort, multicenter (n = 19 regions from 11 countries)</td><td>Gestational age 24<sup>0/7</sup> to 29<sup>6/7</sup> wk</td><td>3662/3407</td><td>901</td><td>28 [26-29]</td><td>1000 (IQR 810-1200)</td><td>D14</td><td>Moderate/severe BPD: supplemental oxygen or respiratory support at 36 weeks</td></tr><tr><td>Aldecoa-Bilbao<sup>57</sup></td><td>2021, Spain</td><td>2018-2020</td><td>Prospective cohort</td><td>Gestational age 23<sup>0/7</sup> to 30<sup>6/7</sup> wk</td><td>152/89</td><td>23</td><td>28.1 [26.7-29.8]</td><td>BPD: 856 (284) No BPD: 1077 (320)</td><td>D7</td><td>Moderate/severe BPD: supplemental oxygen or positive pressure ventilation at 36 WG</td></tr><tr><td>Alonso-Ojemarrena<sup>52</sup></td><td>2021, Spain</td><td>2017-2020</td><td>Prospective cohort, multicenter (n = 6)</td><td>Gestational age &lt;32 wk</td><td>356/298</td><td>73</td><td>29 [26-30]</td><td>1100 [859-1340]</td><td>D0, D3, D7, D14</td><td>BPD at 36 WG - physiologic definition (Walsh test)</td></tr><tr><td>Baud<sup>58</sup></td><td>2021, Europe, USA</td><td>2008-2014</td><td>Randomized trial participants, multicenter (n = 21)</td><td>Gestational age 24<sup>0/7</sup> to 27<sup>6/7</sup> wk</td><td>523/523</td><td>232</td><td>26.5 [25.7-27.1]</td><td>840 (735-970)</td><td>At birth</td><td>Death or moderate/severe BPD: respiratory support at 36 WG, physiologic test if FIO<sub>2</sub> 22-29%</td></tr><tr><td>Dai<sup>59</sup></td><td>2021, China</td><td>2017-2019</td><td>Nested case-control, single center</td><td>Gestational age &lt;32 wk</td><td>254/245</td><td>67</td><td>29.1 [27.9-30.6]</td><td>1200 [1020-1410]</td><td>Unclear</td><td>Death due to respiratory insufficiency or severe BPD (NICHD definition)</td></tr><tr><td>Gerull<sup>60</sup></td><td>2021, Switzerland</td><td>2013-2017</td><td>Prospective cohort, multicenter (n = 2)</td><td>Gestational age &lt;32 wk</td><td>523/229</td><td>26</td><td>29.6 [27.0-30.7]</td><td>1150 [840-1410]</td><td>D7</td><td>Death/BPD at 36 weeks</td></tr></tbody></table>

(continued)
<figure><img src="image_17.png" /></figure>

<table><caption>Table I. Description of included studies</caption><thead><tr><th>First author</th><th>Year of publication, country</th><th>Period of data collection</th><th>Study design</th><th>Inclusion criteria</th><th>Number of participants eligible/analyzed</th><th>Number of outcome events</th><th>Gestational age, wk, mean (SD) or median [IQR]</th><th>Birth weight, g, mean ± SD or median [IQR]</th><th>Timing of model assessment</th><th>Defined outcome</th></tr></thead><tbody><tr><td>Development studies Ahmed<sup>70</sup></td><td>2022, USA</td><td>1997-2015</td><td>Nested case-control, single center</td><td>Gestational age &lt;29 wk</td><td>42/42</td><td>21</td><td>25.9 (1.18)</td><td>809 (175)</td><td>Before 72H</td><td>Moderate/severe BPD supplemental oxygen at 36 weeks of PMA</td></tr><tr><td>Alonso-Ojemarrena<sup>71</sup></td><td>2022, Spain</td><td>2017-2021</td><td>Case-control, multicenter (n = 2)</td><td>Gestational age &lt;32 wk</td><td>199/133</td><td>27</td><td>no BPD group 30 [29-31] BPD group 27 [25-29]</td><td>no BPD 1300 [1100-1445]; BPD 905 (620-1000)</td><td>D1, D3, D7, D14</td><td>Moderate/severe BPD: any respiratory support at 36 weeks of PMA</td></tr><tr><td>Greenberg<sup>72</sup></td><td>2022, USA</td><td>2011-2017</td><td>Prospective cohort, multicenter (n = 38)</td><td>Gestational age 23<sup>0/7</sup> to 28<sup>6/7</sup> wk; BW 501-1250 g;</td><td>9843/9181</td><td>BPD grade 1 2 795; grade 2 1 526; grade 3 551; death 1052</td><td>25.9 (1.57)</td><td>850 (192)</td><td>D1, D3, D7, D14</td><td>Grade 1 BPD/grade 2 BPD/grade 3 BPD/ death according to the 2019 definition by Jensen</td></tr><tr><td>Kindt<sup>73</sup></td><td>2022, Germany</td><td>No information</td><td>Prospective cohort, single center</td><td>Gestational age &lt;32 wk</td><td>55/52</td><td>13</td><td>27.2 (range 23.2-30.6)</td><td>798 [510-1590]</td><td>First week</td><td>Moderate or severe BPD according to NICHD 2001 definition</td></tr><tr><td>Umapathi<sup>74</sup></td><td>2022, USA</td><td>No information</td><td>Prospective cohort, single center</td><td>Gestational age &lt;32 wk</td><td>101/98</td><td>34</td><td>28.9 (1.91)</td><td>122 (319)</td><td>First week</td><td>Moderate/severe BPD or death: supplemental oxygen at 36 weeks of PMA</td></tr><tr><td>Zayat<sup>75</sup></td><td>2022, Europe</td><td>2011-2012</td><td>Prospective cohort, multicenter (n = 19 regions from 11 countries)</td><td>Gestational age 24<sup>0/7</sup> to 29<sup>6/7</sup> wk</td><td>3662/3407</td><td>901</td><td>28 [26-29]</td><td>1000 (IQR 810-1200)</td><td>D14</td><td>Moderate/severe BPD: supplemental oxygen or respiratory support at 36 weeks</td></tr><tr><td>Aldecoa-Bilbao<sup>57</sup></td><td>2021, Spain</td><td>2018-2020</td><td>Prospective cohort</td><td>Gestational age 23<sup>0/7</sup> to 30<sup>6/7</sup> wk</td><td>152/89</td><td>23</td><td>28.1 [26.7-29.8]</td><td>BPD: 856 (284) No BPD: 1077 (320)</td><td>D7</td><td>Moderate/severe BPD: supplemental oxygen or positive pressure ventilation at 36 WG</td></tr><tr><td>Alonso-Ojemarrena<sup>52</sup></td><td>2021, Spain</td><td>2017-2020</td><td>Prospective cohort, multicenter (n = 6)</td><td>Gestational age &lt;32 wk</td><td>356/298</td><td>73</td><td>29 [26-30]</td><td>1100 [859-1340]</td><td>D0, D3, D7, D14</td><td>BPD at 36 WG - physiologic definition (Walsh test)</td></tr><tr><td>Baud<sup>58</sup></td><td>2021, Europe, USA</td><td>2008-2014</td><td>Randomized trial participants, multicenter (n = 21)</td><td>Gestational age 24<sup>0/7</sup> to 27<sup>6/7</sup> wk</td><td>523/523</td><td>232</td><td>26.5 [25.7-27.1]</td><td>840 (735-970)</td><td>At birth</td><td>Death or moderate/severe BPD: respiratory support at 36 WG, physiologic test if FiO<sub>2</sub> 22-29%</td></tr><tr><td>Dai<sup>59</sup></td><td>2021, China</td><td>2017-2019</td><td>Nested case-control, single center</td><td>Gestational age &lt;32 wk</td><td>254/245</td><td>67</td><td>29.1 [27.9-30.6]</td><td>1200 [1020-1410]</td><td>Unclear</td><td>Death due to respiratory insufficiency or severe BPD (NICHD definition)</td></tr><tr><td>Gerull<sup>60</sup></td><td>2021, Switzerland</td><td>2013-2017</td><td>Prospective cohort, multicenter (n = 2)</td><td>Gestational age &lt;32 wk</td><td>523/229</td><td>26</td><td>29.6 [27.0-30.7]</td><td>1150 [840-1410]</td><td>D7</td><td>Death/BPD at 36 weeks</td></tr></tbody></table>

(continued)
<figure><img src="image_17.png" /><figcaption>Table I. Continued</figcaption></figure>

<table><thead><tr><th>First author</th><th>Year of publication, country</th><th>Period of data collection</th><th>Study design</th><th>Inclusion criteria</th><th>Number of participants eligible/analyzed</th><th>Number of outcome events</th><th>Gestational age, wk, mean (SD) or median [IQR]</th><th>Birth weight, g, mean ± SD or median [IQR]</th><th>Timing of model assessment</th><th>Defined outcome</th></tr></thead><tbody><tr><td>Khurshid<sup>61</sup></td><td>2021, Canada</td><td>2016-2018</td><td>Registry data, multicenter (n = 31)</td><td>Gestational age &lt;33 wk</td><td>12990/9006 (day 1) to 3899 (day 14)</td><td>3188</td><td>BPD/death group: 26.5 (2.4); survival without BPD group: 29.5 (2.1)</td><td>Not reported</td><td>D1, D7, D14</td><td>Death/BPD: supplemental oxygen or positive pressure ventilation at 36 WG</td></tr><tr><td>Liu<sup>62</sup></td><td>2021, China</td><td>2019-2020</td><td>Prospective cohort, single center</td><td>Gestational age &lt;32 wk</td><td>130/130</td><td>50</td><td>29.2 (1.8)</td><td>1195 (209.8)</td><td>D1, D2, D3, D6, D9, D12</td><td>BPD: 2019 definition by Jensen</td></tr><tr><td>Mohamed<sup>63</sup></td><td>2021, Canada</td><td>2019-2020</td><td>Prospective cohort, multicenter (n = 2)</td><td>Gestational age &lt;29 wk</td><td>223/152</td><td>87</td><td>25.8 (1.5)</td><td>923 (250)</td><td>D3, D7, D14</td><td>BPD: supplementation of oxygen or respiratory support at 36 WG</td></tr><tr><td>Shim<sup>64</sup></td><td>2021, South Korea</td><td>2013-2016</td><td>Registry data, multicenter (n = 66)</td><td>Unclear</td><td>6969/4600</td><td>1370</td><td>BPD 0 30.61 (1.80); BPD 1 27.49 (1.84); BPD 2 27.37 (2.18); BPD 3 26.64 (2.34)</td><td>BPD 0 127(174); BPD 1 1058 (23); BPD 2 1025 (24); BPD 3 886 (264)</td><td>D0</td><td>Moderate and severe BPD: NIH definition</td></tr><tr><td>Song<sup>65</sup></td><td>2021, China</td><td>2016-2021</td><td>Retrospective cohort, single center</td><td>Gestational age &lt;32 wk; BW &lt;1500 g</td><td>564/556</td><td>138</td><td>29.6 [28.6-30.5]</td><td>1200 [1050-1350]</td><td>D7</td><td>Moderate/severe BPD or death: NIH definition</td></tr><tr><td>Soullane<sup>66</sup></td><td>2021, Canada</td><td>2015-2018</td><td>Retrospective cohort, single center</td><td>Gestational age 23<sup>0/7</sup> to 28<sup>6/7</sup> wk</td><td>191/191</td><td>98</td><td>BPD/death 26 [24,26]; no BPD 27 [25,28]</td><td>BPD/death 760 [633 888]; no BPD 950 [750, 1170]</td><td>D10</td><td>BPD: supplemental oxygen or respiratory support at 36 wk or at discharge.</td></tr><tr><td>Ushida<sup>67</sup></td><td>2021, Japan</td><td>2006-2015</td><td>Registry data, multicenter (n = 200)</td><td>Gestational age &lt;32 wk; BW &lt;1500 g</td><td>33690/20 771</td><td>4986</td><td>27.8 (2.5)</td><td>975 (299)</td><td>D0</td><td>BPD: oxygen requirement at 36 wk</td></tr><tr><td>Woods<sup>68</sup></td><td>2021, Australia</td><td>2017-2018</td><td>Prospective cohort, single center</td><td>Gestational age &lt;28 wk</td><td>125/96</td><td>46</td><td>26.4 (range 23.1-27.6)</td><td>855 (range 450-1390)</td><td>D1, D3, D7</td><td>Moderate/severe BPD: respiratory support at 36 wk</td></tr><tr><td>Zhang<sup>69</sup></td><td>2021, China</td><td>2019-2021</td><td>Retrospective cohort, single center</td><td>Gestational age &lt;32 wk; BW &lt;1500 g</td><td>414/414</td><td>98</td><td>BPD group 28.8 (27.9, 30.0); non-BPD group 29.6 (28.7, 30.7)</td><td>BPD 1045.0 (923.8, 1222.5); no-BPD 1240.0 (1102.5, 1360.0)</td><td>D3, D7, D14</td><td>BPD: 2019 definition by Jensen</td></tr><tr><td>Sharma<sup>54</sup></td><td>2020, USA</td><td>2011-2017</td><td>Retrospective cohort, single center</td><td>Gestational age 23-26<sup>6/7</sup> wk</td><td>317/263</td><td>155</td><td>No/mild BPD 26.0 (1.1)</td><td>No/mild BPD 918 (174); Moderate or severe BPD 24.7 (1.3)</td><td>D14</td><td>Moderate or severe BPD: &gt;28 days supplemental oxygen and supplemental oxygen and/or positive pressure respiratory support confirmed by physiological test at 36 weeks of PMA or at time of discharge.</td></tr></tbody><tfoot><tr><td colspan="12" style="text-align: right;">(continued)</td></tr></tfoot></table>
<figure><img src="image_18.png" /><figcaption>Table I. Continued</figcaption></figure>

<table><thead><tr><th>First author</th><th>Year of publication, country</th><th>Period of data collection</th><th>Study design</th><th>Inclusion criteria</th><th>Number of participants eligible/analyzed</th><th>Number of outcome events</th><th>Gestational age, wk, mean (SD) or median [IQR]</th><th>Birth weight, g, mean ± SD or median [IQR]</th><th>Timing of model assessment</th><th>Defined outcome</th></tr></thead><tbody><tr><td>Khurshid<sup>61</sup></td><td>2021, Canada</td><td>2016-2018</td><td>Registry data, multicenter (n = 31)</td><td>Gestational age &lt;33 wk</td><td>12990/9006 (day 1) to 3899 (day 14)</td><td>3188</td><td>BPD/death group: 26.5 (2.4); survival without BPD group: 29.5 (2.1)</td><td>Not reported</td><td>D1, D7, D14</td><td>Death/BPD: supplemental oxygen or positive pressure ventilation at 36 WG</td></tr><tr><td>Liu<sup>62</sup></td><td>2021, China</td><td>2019-2020</td><td>Prospective cohort, single center</td><td>Gestational age &lt;32 wk</td><td>130/130</td><td>50</td><td>29.2 (1.8)</td><td>1195 (209.8)</td><td>D1, D2, D3, D6, D9, D12</td><td>BPD: 2019 definition by Jensen</td></tr><tr><td>Mohamed<sup>63</sup></td><td>2021, Canada</td><td>2019-2020</td><td>Prospective cohort, multicenter (n = 2)</td><td>Gestational age &lt;29 wk</td><td>223/152</td><td>87</td><td>25.8 (1.5)</td><td>923 (250)</td><td>D3, D7, D14</td><td>BPD: supplementation of oxygen or respiratory support at 36 WG</td></tr><tr><td>Shim<sup>64</sup></td><td>2021, South Korea</td><td>2013-2016</td><td>Registry data, multicenter (n = 66)</td><td>Unclear</td><td>6969/4600</td><td>1370</td><td>BPD 0 30.61 (1.80); BPD 1 27.49 (1.84); BPD 2 27.37 (2.18); BPD 3 26.64 (2.34)</td><td>BPD 0 127(174); BPD 1 1058 (23); BPD 2 1025 (24); BPD 3 886 (264)</td><td>D0</td><td>Moderate and severe BPD: NIH definition</td></tr><tr><td>Song<sup>65</sup></td><td>2021, China</td><td>2016-2021</td><td>Retrospective cohort, single center</td><td>Gestational age &lt;32 wk; BW &lt;1500 g</td><td>564/556</td><td>138</td><td>29.6 [28.6-30.5]</td><td>1200 [1050-1350]</td><td>D7</td><td>Moderate/severe BPD or death: NIH definition</td></tr><tr><td>Soullane<sup>66</sup></td><td>2021, Canada</td><td>2015-2018</td><td>Retrospective cohort, single center</td><td>Gestational age 23<sup>0/7</sup> to 28<sup>6/7</sup> wk</td><td>191/191</td><td>98</td><td>BPD/death 26 [24,26]; no BPD 27 [25,28]</td><td>BPD/death 760 [633 888]; no BPD 950 [750, 1170]</td><td>D10</td><td>BPD: supplemental oxygen or respiratory support at 36 wk or at discharge.</td></tr><tr><td>Ushida<sup>67</sup></td><td>2021, Japan</td><td>2006-2015</td><td>Registry data, multicenter (n = 200)</td><td>Gestational age &lt;32 wk; BW &lt;1500 g</td><td>33690/20 771</td><td>4986</td><td>27.8 (2.5)</td><td>975 (299)</td><td>D0</td><td>BPD: oxygen requirement at 36 wk</td></tr><tr><td>Woods<sup>68</sup></td><td>2021, Australia</td><td>2017-2018</td><td>Prospective cohort, single center</td><td>Gestational age &lt;28 wk</td><td>125/96</td><td>46</td><td>26.4 (range 23.1-27.6)</td><td>855 (range 450-1390)</td><td>D1, D3, D7</td><td>Moderate/severe BPD: respiratory support at 36 wk</td></tr><tr><td>Zhang<sup>69</sup></td><td>2021, China</td><td>2019-2021</td><td>Retrospective cohort, single center</td><td>Gestational age &lt;32 wk; BW &lt;1500 g</td><td>414/414</td><td>98</td><td>BPD group 28.8 (27.9, 30.0); non-BPD group 29.6 (28.7, 30.7)</td><td>BPD 1045.0 (923.8, 1222.5); no-BPD 1240.0 (1102.5, 1360.0)</td><td>D3, D7, D14</td><td>BPD: 2019 definition by Jensen</td></tr><tr><td>Sharma<sup>54</sup></td><td>2020, USA</td><td>2011-2017</td><td>Retrospective cohort, single center</td><td>Gestational age 23-26<sup>6/7</sup> wk</td><td>317/263</td><td>155</td><td>No/mild BPD 26.0 (1.1)</td><td>No/mild BPD 918 (174); Moderate or severe BPD 24.7 (1.3)</td><td>D14</td><td>Moderate or severe BPD: &gt;28 days supplemental oxygen and supplemental oxygen and/or positive pressure respiratory support confirmed by physiological test at 36 weeks of PMA or at time of discharge.</td></tr></tbody><tfoot><tr><td colspan="12" style="text-align: right;">(continued)</td></tr></tfoot></table>
<table><caption>Table I. Continued</caption><thead><tr><th>First author</th><th>Year of publication, country</th><th>Period of data collection</th><th>Study design</th><th>Inclusion criteria</th><th>Number of participants eligible/analyzed</th><th>Number of outcome events</th><th>Gestational age, wk, mean (SD) or median [IQR]</th><th>Birth weight, g, mean ± SD or median [IQR]</th><th>Timing of model assessment</th><th>Defined outcome</th></tr></thead><tbody><tr><td>Alvarez-Fuente<sup>51</sup></td><td>2019, Spain</td><td>2014-2016</td><td>Prospective cohort, multicenter (n = 5)</td><td>Gestational age &lt;28 wk; BW &lt;1250 g</td><td>47/47</td><td>22</td><td>26 [25-27]</td><td>871 (161)</td><td>D7</td><td>Moderate or severe BPD: &gt;28 days supplemental oxygen or respiratory support at 36 weeks of PMA. Deaths between D7 and D28 considered as severe BPD.</td></tr><tr><td>Beltempo<sup>50</sup></td><td>2019, Canada</td><td>2010-2015</td><td>Retrospective cohort, multicenter (n = 30)</td><td>Gestational age 22-28<sup>6/7</sup> wk</td><td>9240/7975</td><td>2959</td><td>27 [unclear]</td><td>953 (244)</td><td>H12</td><td>BPD: oxygen supplementation at 36 weeks of PMA or at time of discharge.</td></tr><tr><td>Fairchild<sup>49</sup></td><td>2019, USA</td><td>2009-2014</td><td>Retrospective cohort, single center</td><td>Gestational age 23-33 wk; BW &lt;1500g</td><td>502/Unknown</td><td>187</td><td>28 [25-29]</td><td>1020 [800-1250]</td><td>D7</td><td>Death or BPD: oxygen supplementation or respiratory support at 36 weeks of PMA</td></tr><tr><td>Valenzuela-Stutman<sup>46</sup></td><td>2019, Argentina, Chile, Paraguay, Peru, Uruguay</td><td>2001-2015</td><td>Prospective cohort, multicenter (n = 15)</td><td>BW 500-1500g</td><td>16 407/Unknown</td><td>2580/6121</td><td>29 (2.9)</td><td>1099 (275)</td><td>D1, D3, D7, D14</td><td>4 models with outcome moderate or severe BPD &gt;28 days supplemental oxygen/CPAP or mechanical ventilation at Jenison 36 weeks of PMA; 4 models with outcome moderate or severe BPD/death at 36 weeks of PMA</td></tr><tr><td>Veneroni<sup>45</sup></td><td>2019, Sweden</td><td>2011-2014</td><td>Prospective cohort, single center</td><td>Gestational age &lt;28 wk</td><td>Unknown/22</td><td>15</td><td>24.6 (1.6)</td><td>653 (170)</td><td>D1</td><td>BPD: oxygen supplementation at 36 weeks of PMA</td></tr><tr><td>Bentsen<sup>44</sup></td><td>2018, Norway</td><td>2016-2016</td><td>Prospective cohort, single center</td><td>Gestational age &lt;28 wk</td><td>40/33</td><td>18</td><td>No/mild BPD 26.2 (1.1); Moderate or severe BPD 25.5 (1.3)</td><td>No/mild BPD 864 (164); Moderate or severe BPD 754 (154)</td><td>D2</td><td>Moderate or severe BPD according to NICHD definition</td></tr><tr><td>Boghossian<sup>43</sup></td><td>2018, USA and Puerto Rico</td><td>2006-2014</td><td>Prospective cohort, multicenter (n = 852)</td><td>Gestational age &lt;30 wk</td><td>156 587/Unknown</td><td></td><td>No information</td><td>No information</td><td>At birth</td><td>Moderate or severe BPD: oxygen supplementation at 36 weeks of PMA or at time of discharge</td></tr><tr><td>Sullivan<sup>41</sup></td><td>2018, USA</td><td>2009-2015</td><td>Retrospective cohort, multicenter (n = 2)</td><td>BW &lt;1500 g</td><td>778/730</td><td>186</td><td>28.0 (2.8)</td><td>1029 (298)</td><td>D7</td><td>Moderate or severe BPD: oxygen supplementation at 36 weeks of PMA</td></tr><tr><td>Kandasamy<sup>40</sup></td><td>2017, USA</td><td>No information</td><td>Prospective cohort, single center</td><td>Gestational age &lt;32 wk</td><td>69/69</td><td>35</td><td>26 (3)</td><td>860 (375)</td><td>Unclear</td><td>Death or BPD according to NICHD definition and room air challenge</td></tr></tbody><tfoot><tr><td colspan="12" style="text-align: right;">(continued)</td></tr></tfoot></table>
<table><caption>Table I. Continued</caption><thead><tr><th>First author</th><th>Year of publication, country</th><th>Period of data collection</th><th>Study design</th><th>Inclusion criteria</th><th>Number of participants eligible/analyzed</th><th>Number of outcome events</th><th>Gestational age, wk, mean (SD) or median [IQR]</th><th>Birth weight, g, mean ± SD or median [IQR]</th><th>Timing of model assessment</th><th>Defined outcome</th></tr></thead><tbody><tr><td>Alvarez-Fuente<sup>51</sup></td><td>2019, Spain</td><td>2014-2016</td><td>Prospective cohort, multicenter (n = 5)</td><td>Gestational age &lt;28 wk; BW &lt;1250 g</td><td>47/47</td><td>22</td><td>26 [25-27]</td><td>871 (161)</td><td>D7</td><td>Moderate or severe BPD: &gt;28 days supplemental oxygen or respiratory support at 36 weeks of PMA. Deaths between D7 and D28 considered as severe BPD.</td></tr><tr><td>Beltempo<sup>50</sup></td><td>2019, Canada</td><td>2010-2015</td><td>Retrospective cohort, multicenter (n = 30)</td><td>Gestational age 22-28<sup>6/7</sup> wk</td><td>9240/7975</td><td>2959</td><td>27 [unclear]</td><td>953 (244)</td><td>H12</td><td>BPD: oxygen supplementation at 36 weeks of PMA or at time of discharge.</td></tr><tr><td>Fairchild<sup>49</sup></td><td>2019, USA</td><td>2009-2014</td><td>Retrospective cohort, single center</td><td>Gestational age 23-33 wk; BW &lt;1500g</td><td>502/Unknown</td><td>187</td><td>28 [25-29]</td><td>1020 [800-1250]</td><td>D7</td><td>Death or BPD: oxygen supplementation or respiratory support at 36 weeks of PMA</td></tr><tr><td>Valenzuela-Stutman<sup>46</sup></td><td>2019, Argentina, Chile, Paraguay, Peru, Uruguay</td><td>2001-2015</td><td>Prospective cohort, multicenter (n = 15)</td><td>BW 500-1500g</td><td>16 407/Unknown</td><td>2580/6121</td><td>29 (2.9)</td><td>1099 (275)</td><td>D1, D3, D7, D14</td><td>4 models with outcome moderate or severe BPD &gt;28 days supplemental oxygen/CPAP or mechanical ventilation at Jenison 36 weeks of PMA; 4 models with outcome moderate or severe BPD/death at 36 weeks of PMA</td></tr><tr><td>Veneroni<sup>45</sup></td><td>2019, Sweden</td><td>2011-2014</td><td>Prospective cohort, single center</td><td>Gestational age &lt;28 wk</td><td>Unknown/22</td><td>15</td><td>24.6 (1.6)</td><td>653 (170)</td><td>D1</td><td>BPD: oxygen supplementation at 36 weeks of PMA</td></tr><tr><td>Bentsen<sup>44</sup></td><td>2018, Norway</td><td>2016-2016</td><td>Prospective cohort, single center</td><td>Gestational age &lt;28 wk</td><td>40/33</td><td>18</td><td>No/mild BPD 26.2 (1.1); Moderate or severe BPD 25.5 (1.3)</td><td>No/mild BPD 864 (164); Moderate or severe BPD 754 (154)</td><td>D2</td><td>Moderate or severe BPD according to NICHD definition</td></tr><tr><td>Boghossian<sup>43</sup></td><td>2018, USA and Puerto Rico</td><td>2006-2014</td><td>Prospective cohort, multicenter (n = 852)</td><td>Gestational age &lt;30 wk</td><td>156 587/Unknown</td><td></td><td>No information</td><td>No information</td><td>At birth</td><td>Moderate or severe BPD: oxygen supplementation at 36 weeks of PMA or at time of discharge</td></tr><tr><td>Sullivan<sup>41</sup></td><td>2018, USA</td><td>2009-2015</td><td>Retrospective cohort, multicenter (n = 2)</td><td>BW &lt;1500 g</td><td>778/730</td><td>186</td><td>28.0 (2.8)</td><td>1029 (298)</td><td>D7</td><td>Moderate or severe BPD: oxygen supplementation at 36 weeks of PMA</td></tr><tr><td>Kandasamy<sup>40</sup></td><td>2017, USA</td><td>No information</td><td>Prospective cohort, single center</td><td>Gestational age &lt;32 wk</td><td>69/69</td><td>35</td><td>26 (3)</td><td>860 (375)</td><td>Unclear</td><td>Death or BPD according to NICHD definition and room air challenge</td></tr></tbody><tfoot><tr><td colspan="12" style="text-align: right;">(continued)</td></tr></tfoot></table>
<figure><img src="image_18.png" /><figcaption>Table I. Continued</figcaption></figure>

<table><thead><tr><th>First author</th><th>Year of publication, country</th><th>Period of data collection</th><th>Study design</th><th>Inclusion criteria</th><th>Number of participants eligible/analyzed</th><th>Number of outcome events</th><th>Gestational age, wk, mean (SD) or median [IQR]</th><th>Birth weight, g, mean ± SD or median [IQR]</th><th>Timing of model assessment</th><th>Defined outcome</th></tr></thead><tbody><tr><td>Wai<sup>37</sup></td><td>2016, USA</td><td>2010-2013</td><td>Randomized trial participants, multicenter (n = 25)</td><td>Gestational age &lt;29 wk</td><td>511/474</td><td>336</td><td>25.2 (1.2)</td><td>700 (165)</td><td>D14</td><td>Death or BPD: respiratory support or oxygen supplementation at 36 weeks of PMA and room air challenge</td></tr><tr><td>El-Khuffash<sup>36</sup></td><td>2015, Ireland, Canada, Australia</td><td>No information</td><td>Prospective cohort, multicenter (n = unknown)</td><td>Gestational age &lt;29 wk</td><td>141/141</td><td>79</td><td>26.8 (1.4)</td><td>952 (235)</td><td>D2</td><td>Death or BPD: oxygen supplementation at 36 weeks of PMA</td></tr><tr><td>Kandasamy<sup>35</sup></td><td>2015, USA</td><td>2005-2008</td><td>Prospective cohort, single center</td><td>BW &lt; 1000 g</td><td>152/152</td><td>53</td><td>25.5 (2.8)</td><td>720.16 (147)</td><td>D1</td><td>Death or BPD according to NICHD definition and room air challenge</td></tr><tr><td>Popova<sup>34</sup></td><td>2015, USA</td><td>No information</td><td>Prospective cohort, single center</td><td>Gestational age ≤32 wk</td><td>89/89</td><td>54</td><td>No BPD: 28.71 (2.58) BPD/death 25.93 (2.93)</td><td>No BPD: 1170 (490) BPD/death: 815 (266)</td><td>Unclear</td><td>Death or moderate/severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Schneibel<sup>32</sup></td><td>2013, USA</td><td>2006-2008</td><td>Prospective cohort, multicenter (n = 2)</td><td>Gestational age 23-31 wk; BW &lt;1500 g</td><td>27/27</td><td>11</td><td>No/mild BPD 26.18 (1.86) Moderate/severe BPD 26.95 (2.63)</td><td>No/mild BPD 872 (245) Moderate/severe BPD 817 (263)</td><td>D1</td><td>Moderate/severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Ambalavanan<sup>30</sup></td><td>2011, USA</td><td>2001-2004</td><td>Randomized trial participants</td><td>BW 401-1250 g</td><td>2836/Unknown</td><td>1010</td><td>27.1 [25-29]</td><td>910 (206)</td><td>D7</td><td>Death or moderate/severe BPD: positive pressure support or FiO<sub>2</sub> &gt;30% supplemental oxygen with SaO<sub>2</sub> 90%-96% at 36 weeks of PMA and room air challenge.</td></tr><tr><td>Laughon<sup>28</sup></td><td>2011, USA</td><td>2000-2004</td><td>Randomized trial participants, multicenter (n = 17)</td><td>Gestational age 23-29 wk; BW 401-1250 g</td><td>3636/3629</td><td>2411</td><td>26.7 (1.9)</td><td>897 (203)</td><td>D1, D3, D7 and D14</td><td>Death or mild/moderate/severe BPD according to NICHD definition.</td></tr><tr><td>Messerschmidt<sup>27</sup></td><td>2011, Austria</td><td>1999-2007</td><td>Retrospective cohort, single center</td><td>BW ≤1500 g</td><td>300/223</td><td>33</td><td>No/mild BPD 27.3 (1.9) Moderate/severe BPD 25.9 (1.5)</td><td>No information</td><td>D1</td><td>Moderate/severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Subramanian<sup>26</sup></td><td>2011, USA</td><td>1994-1997</td><td>Retrospective cohort, multicenter (n = 9)</td><td>Gestational age &lt;36 wk; BW 500-1499 g</td><td>493/425</td><td>74</td><td>28.9 (2.5)</td><td>1091 (260)</td><td>D6</td><td>Moderate/severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Ambalavanan<sup>25</sup></td><td>2008, USA</td><td>2001-2003</td><td>Randomized trial participants, multicenter (n = unclear)</td><td>Gestational age &lt;34 wk; BW 401-1500 g</td><td>420/417</td><td>321</td><td>26 (2)</td><td>840 g (260)</td><td>Unclear</td><td>Death or BPD: room air challenge.</td></tr></tbody></table>

(continued)
<table><caption>Table I. Continued</caption><thead><tr><th>First author</th><th>Year of publication, country</th><th>Period of data collection</th><th>Study design</th><th>Inclusion criteria</th><th>Number of participants eligible/analyzed</th><th>Number of outcome events</th><th>Gestational age, wk, mean (SD) or median [IQR]</th><th>Birth weight, g, mean ± SD or median [IQR]</th><th>Timing of model assessment</th><th>Defined outcome</th></tr></thead><tbody><tr><td>Wai<sup>37</sup></td><td>2016, USA</td><td>2010-2013</td><td>Randomized trial participants, multicenter (n = 25)</td><td>Gestational age &lt;29 wk</td><td>511/474</td><td>336</td><td>25.2 (1.2)</td><td>700 (165)</td><td>D14</td><td>Death or BPD: respiratory support or oxygen supplementation at 36 weeks of PMA and room air challenge</td></tr><tr><td>El-Khuffash<sup>36</sup></td><td>2015, Ireland, Canada, Australia</td><td>No information</td><td>Prospective cohort, multicenter (n = unknown)</td><td>Gestational age &lt;29 wk</td><td>141/141</td><td>79</td><td>26.8 (1.4)</td><td>952 (235)</td><td>D2</td><td>Death or BPD: oxygen supplementation at 36 weeks of PMA</td></tr><tr><td>Kandasamy<sup>35</sup></td><td>2015, USA</td><td>2005-2008</td><td>Prospective cohort, single center</td><td>BW &lt; 1000 g</td><td>152/152</td><td>53</td><td>25.5 (2.8)</td><td>720.16 (147)</td><td>D1</td><td>Death or BPD according to NICHD definition and room air challenge</td></tr><tr><td>Popova<sup>34</sup></td><td>2015, USA</td><td>No information</td><td>Prospective cohort, single center</td><td>Gestational age ≤32 wk</td><td>89/89</td><td>54</td><td>No BPD: 28.71 (2.58) BPD/death 25.93 (2.93)</td><td>No BPD: 1170 (490) BPD/death: 815 (266)</td><td>Unclear</td><td>Death or moderate/severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Schneibel<sup>32</sup></td><td>2013, USA</td><td>2006-2008</td><td>Prospective cohort, multicenter (n = 2)</td><td>Gestational age 23-31 wk; BW &lt;1500 g</td><td>27/27</td><td>11</td><td>No/mild BPD 26.18 (1.86) Moderate/severe BPD 26.95 (2.63)</td><td>No/mild BPD 872 (245) Moderate/severe BPD 817 (263)</td><td>D1</td><td>Moderate/severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Ambalavanan<sup>30</sup></td><td>2011, USA</td><td>2001-2004</td><td>Randomized trial participants</td><td>BW 401-1250 g</td><td>2836/Unknown</td><td>1010</td><td>27.1 [25-29]</td><td>910 (206)</td><td>D7</td><td>Death or moderate/severe BPD: positive pressure support or FiO<sub>2</sub> &gt;30% supplemental oxygen with SaO<sub>2</sub> 90%-96% at 36 weeks of PMA and room air challenge.</td></tr><tr><td>Laughon<sup>28</sup></td><td>2011, USA</td><td>2000-2004</td><td>Randomized trial participants, multicenter (n = 17)</td><td>Gestational age 23-29 wk; BW 401-1250 g</td><td>3636/3629</td><td>2411</td><td>26.7 (1.9)</td><td>897 (203)</td><td>D1, D3, D7 and D14</td><td>Death or mild/moderate/severe BPD according to NICHD definition.</td></tr><tr><td>Messerschmidt<sup>27</sup></td><td>2011, Austria</td><td>1999-2007</td><td>Retrospective cohort, single center</td><td>BW ≤1500 g</td><td>300/223</td><td>33</td><td>No/mild BPD 27.3 (1.9) Moderate/severe BPD 25.9 (1.5)</td><td>No information</td><td>D1</td><td>Moderate/severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Subramanian<sup>26</sup></td><td>2011, USA</td><td>1994-1997</td><td>Retrospective cohort, multicenter (n = 9)</td><td>Gestational age &lt;36 wk; BW 500-1499 g</td><td>493/425</td><td>74</td><td>28.9 (2.5)</td><td>1091 (260)</td><td>D6</td><td>Moderate/severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Ambalavanan<sup>25</sup></td><td>2008, USA</td><td>2001-2003</td><td>Randomized trial participants, multicenter (n = unclear)</td><td>Gestational age &lt;34 wk; BW 401-1500 g</td><td>420/417</td><td>321</td><td>26 (2)</td><td>840 g (260)</td><td>Unclear</td><td>Death or BPD: room air challenge.</td></tr></tbody></table>

(continued)
<table><caption>Table I. Continued</caption><thead><tr><th>First author</th><th>Year of publication, country</th><th>Period of data collection</th><th>Study design</th><th>Inclusion criteria</th><th>Number of participants eligible/analyzed</th><th>Number of outcome events</th><th>Gestational age, wk, mean (SD) or median [IQR]</th><th>Birth weight, g, mean ± SD or median [IQR]</th><th>Timing of model assessment</th><th>Defined outcome</th></tr></thead><tbody><tr><td>Choi<sup>23</sup></td><td>2006, Korea</td><td>1998-2002</td><td>Prospective cohort, single center</td><td>Gestational age ≤32 wk</td><td>75/75</td><td>45</td><td>No/mild BPD 29 (2.4)<br>Moderate/severe BPD 27.7 (2)</td><td>No/mild BPD 1221 (361)<br>Moderate/severe BPD 1010 (246)</td><td>Unclear</td><td>Moderate/severe BPD: >28 days oxygen supplementation and oxygen supplementation at 36 weeks of PMA and consistent chest radiograph findings.</td></tr><tr><td>Henderson-Smart<sup>22</sup></td><td>2006, Australia and New Zealand</td><td>1998-1999</td><td>Prospective cohort, multicenter (n = 25)</td><td>Gestational age 22-31 wk</td><td>5599/5599</td><td>1235</td><td>29 [27-30]</td><td>1235 [960-1505]</td><td>At birth</td><td>Moderate/severe BPD: oxygen supplementation or any form of assisted ventilation at 36 weeks of PMA.</td></tr><tr><td>Kim<sup>21</sup></td><td>2005, Korea</td><td>1997-1999</td><td>Retrospective, single center</td><td>BW &lt;1500 g</td><td>197/161</td><td>30</td><td>28.2 (1.9)</td><td>1043 (262.6)</td><td>D4, D7 and D10</td><td>Moderate or severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Ng<sup>19</sup></td><td>2004, China</td><td>No information</td><td>Prospective cohort, single center</td><td>Gestational age &lt;32 wk;<br>BW &lt; 1500</td><td>137/101</td><td>45</td><td>No/mild BPD 26.4 [24.9-28.3]<br>BPD/death 29.1 [27.8-30.6]</td><td>No/mild BPD 860 [706-1148]<br>BPD/death 1168 [1034-1329]</td><td>D14</td><td>Death or BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Chien<sup>18</sup></td><td>2002, Canada</td><td>1996-1997</td><td>Unclear, multicenter (n = 17)</td><td>Gestational age ≤32 wk</td><td>4907/4226</td><td></td><td>29 (2)</td><td>1390 (457)</td><td>H12</td><td>Moderate/severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Lui<sup>17</sup></td><td>2000, Australia</td><td>1992-1995</td><td>Prospective cohort</td><td>BW &lt; 1000</td><td>48/46</td><td>12</td><td>26 (1)</td><td>805 (102)</td><td>Unclear</td><td>Moderate/severe BPD: oxygen supplementation beyond 36 weeks of PMA.</td></tr><tr><td>Yoder<sup>16</sup></td><td>1999, USA</td><td>1990-1992</td><td>Retrospective cohort, single center</td><td>Gestational age ≤29 wk;<br>BW ≤1000 g</td><td>48/48</td><td>15</td><td>Unclear</td><td>Unclear</td><td>H12, H72</td><td>Death or BPD: oxygen supplementation at 36 weeks of PMA and abnormal chest radiograph. Death after D7 related to persistent severe pulmonary disease.</td></tr><tr><td>Subhedar<sup>14</sup></td><td>1998, United Kingdom</td><td>1994-1996</td><td>Prospective cohort, single center</td><td>Gestational age &lt;32 wk</td><td>55/55</td><td>26</td><td>28 [23-31]</td><td>920 [580-2256]</td><td>H24</td><td>Death or BPD: >28 days oxygen supplementation and oxygen supplementation beyond 36 weeks of PMA.</td></tr><tr><td>Ryan<sup>13</sup></td><td>1996, United Kingdom</td><td>1991-1992</td><td>Retrospective cohort, single center</td><td>Gestational age &lt;32 wk</td><td>204/Unknown</td><td>51</td><td>28 [23-31]</td><td>1160 [512-2300]</td><td>D4</td><td>Moderate/severe BPD: oxygen supplementation to achieve SaO<sub>2</sub> &gt;92% at 36 weeks of PMA and abnormal chest radiograph.</td></tr></tbody><tfoot><tr><td colspan="12" style="text-align: right;">(continued)</td></tr></tfoot></table>
<table><caption>Table I. Continued</caption><thead><tr><th>First author</th><th>Year of publication, country</th><th>Period of data collection</th><th>Study design</th><th>Inclusion criteria</th><th>Number of participants eligible/analyzed</th><th>Number of outcome events</th><th>Gestational age, wk, mean (SD) or median [IQR]</th><th>Birth weight, g, mean ± SD or median [IQR]</th><th>Timing of model assessment</th><th>Defined outcome</th></tr></thead><tbody><tr><td>Choi<sup>23</sup></td><td>2006, Korea</td><td>1998-2002</td><td>Prospective cohort, single center</td><td>Gestational age ≤32 wk</td><td>75/75</td><td>45</td><td>No/mild BPD 29 (2.4)<br>Moderate/severe BPD 27.7 (2)</td><td>No/mild BPD 1221 (361)<br>Moderate/severe BPD 1010 (246)</td><td>Unclear</td><td>Moderate/severe BPD: >28 days oxygen supplementation and oxygen supplementation at 36 weeks of PMA and consistent chest radiograph findings.</td></tr><tr><td>Henderson-Smart<sup>22</sup></td><td>2006, Australia and New-Zealand</td><td>1998-1999</td><td>Prospective cohort, multicenter (n = 25)</td><td>Gestational age 22-31 wk</td><td>5599/5599</td><td>1235</td><td>29 [27-30]</td><td>1235 [960-1505]</td><td>At birth</td><td>Moderate/severe BPD: oxygen supplementation or any form of assisted ventilation at 36 weeks of PMA.</td></tr><tr><td>Kim<sup>21</sup></td><td>2005, Korea</td><td>1997-1999</td><td>Retrospective, single center</td><td>BW &lt;1500 g</td><td>197/161</td><td>30</td><td>28.2 (1.9)</td><td>1043 (262.6)</td><td>D4, D7 and D10</td><td>Moderate or severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Ng<sup>19</sup></td><td>2004, China</td><td>No information</td><td>Prospective cohort, single center</td><td>Gestational age &lt;32 wk;<br>BW &lt; 1500</td><td>137/101</td><td>45</td><td>No/mild BPD 26.4 [24.9-28.3]<br>BPD/death 29.1 [27.8-30.6]</td><td>No/mild BPD 860 [706-1148]<br>BPD/death 1168 [1034-1329]</td><td>D14</td><td>Death or BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Chien<sup>18</sup></td><td>2002, Canada</td><td>1996-1997</td><td>Unclear, multicenter (n = 17)</td><td>Gestational age ≤32 wk</td><td>4907/4226</td><td></td><td>29 (2)</td><td>1390 (457)</td><td>H12</td><td>Moderate/severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Lui<sup>17</sup></td><td>2000, Australia</td><td>1992-1995</td><td>Prospective cohort</td><td>BW &lt; 1000</td><td>48/46</td><td>12</td><td>26 (1)</td><td>805 (102)</td><td>Unclear</td><td>Moderate/severe BPD: oxygen supplementation beyond 36 weeks of PMA.</td></tr><tr><td>Yoder<sup>16</sup></td><td>1999, USA</td><td>1990-1992</td><td>Retrospective cohort, single center</td><td>Gestational age ≤29 wk;<br>BW ≤1000 g</td><td>48/48</td><td>15</td><td>Unclear</td><td>Unclear</td><td>H12, H72</td><td>Death or BPD: oxygen supplementation at 36 weeks of PMA and abnormal chest radiograph. Death after D7 related to persistent severe pulmonary disease.</td></tr><tr><td>Subhedar<sup>14</sup></td><td>1998, United Kingdom</td><td>1994-1996</td><td>Prospective cohort, single center</td><td>Gestational age &lt;32 wk</td><td>55/55</td><td>26</td><td>28 [23-31]</td><td>920 [580-2256]</td><td>H24</td><td>Death or BPD: >28 days oxygen supplementation and oxygen supplementation beyond 36 weeks of PMA.</td></tr><tr><td>Ryan<sup>13</sup></td><td>1996, United Kingdom</td><td>1991-1992</td><td>Retrospective cohort, single center</td><td>Gestational age &lt;32 wk</td><td>204/Unknown</td><td>51</td><td>28 [23-31]</td><td>1160 [512-2300]</td><td>D4</td><td>Moderate/severe BPD: oxygen supplementation to achieve SaO<sub>2</sub> &gt;92% at 36 weeks of PMA and abnormal chest radiograph.</td></tr></tbody><tfoot><tr><td colspan="12" style="text-align: right;">(continued)</td></tr></tfoot></table>
<table><caption>Table I. Continued</caption><thead><tr><th>First author</th><th>Year of publication, country</th><th>Period of data collection</th><th>Study design</th><th>Inclusion criteria</th><th>Number of participants eligible/analyzed</th><th>Number of outcome events</th><th>Gestational age, wk, mean (SD) or median [IQR]</th><th>Birth weight, g, mean ± SD or median [IQR]</th><th>Timing of model assessment</th><th>Defined outcome</th></tr></thead><tbody><tr><td>Validation studies<br>Alonso-Ojemarrena<sup>71</sup></td><td>2022, Spain</td><td>2017-2021</td><td>Case-control, multicenter (n = 2)</td><td>Gestational age &lt;32 wk</td><td>199/133</td><td>27</td><td>no BPD group 30 [29-31]<br>BPD group 27 [25-29]</td><td>no BPD 1300 [1100-1445]; BPD 905 (620-1000)</td><td>D1, D3, D7, D14</td><td>Moderate/severe BPD: any respiratory support at 36 weeks of PMA</td></tr><tr><td>Aldecoa-Bilbao<sup>57</sup></td><td>2021, Spain</td><td>2018-2020</td><td>Prospective cohort single center</td><td>Gestational age 23<sup>0/7</sup> to 30<sup>6/7</sup> wk</td><td>152/89</td><td>23</td><td>28.1 [26.7-29.8]</td><td>BPD: 856 (284)<br>No BPD: 1077 (320)</td><td>D7</td><td>Moderate/severe BPD: supplemental oxygen or positive pressure ventilation at 36 WG</td></tr><tr><td>Alonso-Ojemarrena<sup>52</sup></td><td>2021, Spain</td><td>2017-2020</td><td>Prospective cohort, multicenter (n = 6)</td><td>Gestational age &lt;32 wk</td><td>356/298</td><td>73</td><td>29 [26-30]</td><td>1100 [859-1340]</td><td>D0, D3, D7, D14</td><td>BPD at 36 WG - physiologic definition (Walsh test)</td></tr><tr><td>Baud<sup>58</sup></td><td>2021, Europe, USA</td><td>2008-2014</td><td>Randomized trial participants, multicenter (n = 21)</td><td>Gestational age 24<sup>0/7</sup> to 27<sup>6/7</sup> wk</td><td>523/523</td><td>232</td><td>26.5 [25.7-27.1]</td><td>840 (735-970)</td><td>at birth</td><td>Death or moderate/severe BPD: respiratory support at 36 WG, physiologic test if FIO<sub>2</sub> 22%-29%</td></tr><tr><td>Bhattacharjee<sup>56</sup></td><td>2021, USA</td><td>2012-2013</td><td>Retrospective cohort, single center</td><td>ELBW</td><td>69/64</td><td>31</td><td>25 [21-28]</td><td>723 (160)</td><td>D3</td><td>Severe BPD: &gt;30% O<sub>2</sub> and/or positive pressure ventilation or CPAP at 36 wk or discharge</td></tr><tr><td>Gerull<sup>50</sup></td><td>2021, Switzerland</td><td>2013-2017</td><td>Prospective cohort, multicenter (n = 2)</td><td>Gestational age &lt;32 wk</td><td>523/229</td><td>26</td><td>29.6 [27.0-30.7]</td><td>1150 [840-1410]</td><td>D7</td><td>Death/BPD at 36 weeks</td></tr><tr><td>Liu<sup>62</sup></td><td>2021, China</td><td>2019-2020</td><td>Prospective cohort, single center</td><td>Gestational age &lt;32 wk</td><td>130/130</td><td>50</td><td>29.2 (1.8)</td><td>1195 (2&amp;à)</td><td>D1, D2, D3, D6, D9, D12</td><td>BPD: 2019 definition by Jensen</td></tr><tr><td>Mohamed<sup>63</sup></td><td>2021, Canada</td><td>2019-2020</td><td>Prospective cohort, multicenter (n = 2)</td><td>Gestational age &lt;29 wk</td><td>223/152</td><td>87</td><td>25.8 (1.5)</td><td>923 (250)</td><td>D3, D7, D14</td><td>BPD: supplementation of oxygen or respiratory support at 36 WG</td></tr><tr><td>Shim<sup>64</sup></td><td>2021, South Korea</td><td>2013-2016</td><td>Registry data, multicenter (n = 66)</td><td>Unclear</td><td>6969/1795</td><td>1370</td><td>BPD 0 30.61 (1.80);<br>BPD 1 27.49 (1.84);<br>BPD 2 27.37 (2.18);<br>BPD 3 26.64 (2.34)</td><td>BPD 0 127 (174);<br>BPD 1 1058 (23);<br>BPD 2 1025 (24);<br>BPD 3 886 (264)</td><td>D0</td><td>Moderate and severe BPD: NIH definition</td></tr><tr><td>Ushida<sup>67</sup></td><td>2021, Japan</td><td>2006-2015</td><td>Registry data, multicenter (n = 200)</td><td>Gestational age &lt;32 wk;<br>BW &lt; 1500g</td><td>33 690/20 771</td><td>4986</td><td>27.8 (2.5)</td><td>975 (299)</td><td>D0</td><td>BPD: oxygen requirement at 36 wk</td></tr><tr><td>Woods<sup>58</sup></td><td>2021, Australia</td><td>2017-2018</td><td>Prospective cohort, single center</td><td>Gestational age &lt;28 wk</td><td>125/96</td><td>46</td><td>26.4 (range 23.1-27.6)</td><td>855 (range 450-1390)</td><td>D1, D3, D7</td><td>moderate/severe BPD: respiratory support at 36 wk</td></tr></tbody><tfoot><tr><td colspan="12" style="text-align: right;">(continued)</td></tr></tfoot></table>
<table><caption>Table I. Continued</caption><thead><tr><th>First author</th><th>Year of publication, country</th><th>Period of data collection</th><th>Study design</th><th>Inclusion criteria</th><th>Number of participants eligible/analyzed</th><th>Number of outcome events</th><th>Gestational age, wk, mean (SD) or median [IQR]</th><th>Birth weight, g, mean ± SD or median [IQR]</th><th>Timing of model assessment</th><th>Defined outcome</th></tr></thead><tbody><tr><td>Validation studies<br>Alonso-Ojemarrena<sup>71</sup></td><td>2022, Spain</td><td>2017-2021</td><td>Case-control, multicenter (n = 2)</td><td>Gestational age &lt;32 wk</td><td>199/133</td><td>27</td><td>no BPD group 30 [29-31]<br>BPD group 27 [25-29]</td><td>no BPD 1300 [1100-1445]; BPD 905 (620-1000)</td><td>D1, D3, D7, D14</td><td>Moderate/severe BPD: any respiratory support at 36 weeks of PMA</td></tr><tr><td>Aldecoa-Bilbao<sup>57</sup></td><td>2021, Spain</td><td>2018-2020</td><td>Prospective cohort single center</td><td>Gestational age 23<sup>0/7</sup> to 30<sup>6/7</sup> wk</td><td>152/89</td><td>23</td><td>28.1 [26.7-29.8]</td><td>BPD: 856 (284)<br>No BPD: 1077 (320)</td><td>D7</td><td>Moderate/severe BPD: supplemental oxygen or positive pressure ventilation at 36 WG</td></tr><tr><td>Alonso-Ojemarrena<sup>52</sup></td><td>2021, Spain</td><td>2017-2020</td><td>Prospective cohort, multicenter (n = 6)</td><td>Gestational age &lt;32 wk</td><td>356/298</td><td>73</td><td>29 [26-30]</td><td>1100 [859-1340]</td><td>D0, D3, D7, D14</td><td>BPD at 36 WG - physiologic definition (Walsh test)</td></tr><tr><td>Baud<sup>58</sup></td><td>2021, Europe, USA</td><td>2008-2014</td><td>Randomized trial participants, multicenter (n = 21)</td><td>Gestational age 24<sup>0/7</sup> to 27<sup>6/7</sup> wk</td><td>523/523</td><td>232</td><td>26.5 [25.7-27.1]</td><td>840 (735-970)</td><td>at birth</td><td>Death or moderate/severe BPD: respiratory support at 36 WG, physiologic test if FIO<sub>2</sub> 22%-29%</td></tr><tr><td>Bhattacharjee<sup>56</sup></td><td>2021, USA</td><td>2012-2013</td><td>Retrospective cohort, single center</td><td>ELBW</td><td>69/64</td><td>31</td><td>25 [21-28]</td><td>723 (160)</td><td>D3</td><td>Severe BPD: &gt;30% O<sub>2</sub> and/or positive pressure ventilation or CPAP at 36 wk or discharge</td></tr><tr><td>Gerull<sup>50</sup></td><td>2021, Switzerland</td><td>2013-2017</td><td>Prospective cohort, multicenter (n = 2)</td><td>Gestational age &lt;32 wk</td><td>523/229</td><td>26</td><td>29.6 [27.0-30.7]</td><td>1150 [840-1410]</td><td>D7</td><td>Death/BPD at 36 weeks</td></tr><tr><td>Liu<sup>62</sup></td><td>2021, China</td><td>2019-2020</td><td>Prospective cohort, single center</td><td>Gestational age &lt;32 wk</td><td>130/130</td><td>50</td><td>29.2 (1.8)</td><td>1195 (2&amp;à)</td><td>D1, D2, D3, D6, D9, D12</td><td>BPD: 2019 definition by Jensen</td></tr><tr><td>Mohamed<sup>63</sup></td><td>2021, Canada</td><td>2019-2020</td><td>Prospective cohort, multicenter (n = 2)</td><td>Gestational age &lt;29 wk</td><td>223/152</td><td>87</td><td>25.8 (1.5)</td><td>923 (250)</td><td>D3, D7, D14</td><td>BPD: supplementation of oxygen or respiratory support at 36 WG</td></tr><tr><td>Shim<sup>64</sup></td><td>2021, South Korea</td><td>2013-2016</td><td>Registry data, multicenter (n = 66)</td><td>Unclear</td><td>6969/1795</td><td>1370</td><td>BPD 0 30.61 (1.80);<br>BPD 1 27.49 (1.84);<br>BPD 2 27.37 (2.18);<br>BPD 3 26.64 (2.34)</td><td>BPD 0 127 (174);<br>BPD 1 1058 (23);<br>BPD 2 1025 (24);<br>BPD 3 886 (264)</td><td>D0</td><td>Moderate and severe BPD: NIH definition</td></tr><tr><td>Ushida<sup>67</sup></td><td>2021, Japan</td><td>2006-2015</td><td>Registry data, multicenter (n = 200)</td><td>Gestational age &lt;32 wk;<br>BW &lt; 1500g</td><td>33 690/20 771</td><td>4986</td><td>27.8 (2.5)</td><td>975 (299)</td><td>D0</td><td>BPD: oxygen requirement at 36 wk</td></tr><tr><td>Woods<sup>58</sup></td><td>2021, Australia</td><td>2017-2018</td><td>Prospective cohort, single center</td><td>Gestational age &lt;28 wk</td><td>125/96</td><td>46</td><td>26.4 (range 23.1-27.6)</td><td>855 (range 450-1390)</td><td>D1, D3, D7</td><td>moderate/severe BPD: respiratory support at 36 wk</td></tr></tbody><tfoot><tr><td colspan="12" style="text-align: right;">(continued)</td></tr></tfoot></table>
<table><caption>Table I. Continued</caption><thead><tr><th>First author</th><th>Year of publication, country</th><th>Period of data collection</th><th>Study design</th><th>Inclusion criteria</th><th>Number of participants eligible/analyzed</th><th>Number of outcome events</th><th>Gestational age, wk, mean (SD) or median [IQR]</th><th>Birth weight, g, mean ± SD or median [IQR]</th><th>Timing of model assessment</th><th>Defined outcome</th></tr></thead><tbody><tr><td>Bhattacharjee<sup>56</sup></td><td>2020, USA</td><td>2012-2013</td><td>Retrospective cohort, single center</td><td>BW &lt; 1000 g</td><td>69/64</td><td>31</td><td>25 [21-28]</td><td>722 (160)</td><td>Unclear</td><td>Severe BPD: &gt;30% supplemental oxygen and/or positive pressure ventilation or nasal CPAP at 36 weeks of PMA or at time of discharge.</td></tr><tr><td>Oulego-Erroz<sup>55</sup></td><td>2020, Spain</td><td>2017-2019</td><td>Prospective cohort, single center</td><td>Gestational age &lt;32 wk</td><td>42/42</td><td>13</td><td>No/mild BPD 29.5 [28-31.5] BPD/ death 27 [25.7-28.2]</td><td>No/mild BPD 1235g [1110-1507] BPD/ death 890 g [655-1130]</td><td>D7</td><td>Moderate/severe BPD: oxygen supplementation or positive pressure ventilation at 36 weeks of PMA.</td></tr><tr><td>Sotodate<sup>53</sup></td><td>2020, Japan</td><td>2010-2017</td><td>Retrospective cohort, single center</td><td>Gestational age 22-27 wk</td><td>171/152</td><td>69</td><td>25.7 (1.5)</td><td>768 (201)</td><td>H1, H12, and D1 after NICU admission</td><td>Moderate/severe BPD: oxygen supplementation or positive pressure ventilation at 36 weeks of PMA.</td></tr><tr><td>Alonso-Ojembarrena<sup>52</sup></td><td>2019, Spain</td><td>2017-2018</td><td>Prospective cohort, single center</td><td>Gestational age ≤32 wk or BW ≤1500 g</td><td>64/59</td><td>8</td><td>No BPD 29.5 (95% CI 27-32) Mild/ moderate/severe BPD 27.4 (95% CI 23-31)</td><td>No BPD 1241 (95% CI 837-1440 g) Mild/ moderate/severe BPD 914 (95% CI 461-1367)</td><td>D1, D3, D7 and D14</td><td>Moderate/severe BPD: &gt;28 days oxygen supplementation and oxygen supplementation or respiratory support at 36 weeks of PMA and room air challenge.</td></tr><tr><td>Beltempo<sup>50</sup></td><td>2019, Canada</td><td>2010-2015</td><td>Retrospective cohort, multicenter (n = 30)</td><td>Gestational age 22-28<sup>6/7</sup> wk</td><td>9240/7975</td><td>2959</td><td>27 [3-unclear]</td><td>953 (244)</td><td>H12 after NICU admission</td><td>BPD: oxygen supplementation at 36 weeks of PMA or at time of discharge.</td></tr><tr><td>Jung<sup>48</sup></td><td>2019, South Korea</td><td>2010-2014</td><td>Retrospective cohort, single center</td><td>Gestational age &lt;28 wk</td><td>140/138</td><td>66</td><td>No/mild/moderate BPD 26.2 (1.2); death/severe BPD 25.5 (1.4)</td><td>No/mild/moderate BPD 822.36 g (226.6); death/severe BPD 733.79 (214.42)</td><td>D7</td><td>Death or severe BPD: FiO<sub>2</sub> &gt;0.3 or positive pressure ventilation at 36 weeks of PMA.</td></tr><tr><td>Lee<sup>47</sup></td><td>2019, South Korea</td><td>2013-2016</td><td>Prospective cohort, multicenter (n = 67)</td><td>Gestational age 22-32 wk; VLBW</td><td>Group 1 7198/4649 Group 2 7198/6038</td><td>Group 1 1443 Group 2 1916</td><td>Group 1 28.4 (2.4) Group 2 28.3 (2.4)</td><td>Group 1 1070.8 (280.4) Group 2 1058.5 (282.5)</td><td>H1</td><td>Moderate/severe BPD according to NICHD definition.</td></tr><tr><td>Gulliver<sup>42</sup></td><td>2018, USA</td><td>2010-2016</td><td>Prospective cohort, single center</td><td>Gestational age &lt;30 wk</td><td>622/Unknown</td><td>284</td><td>27.0 (1.9)</td><td>963 (301)</td><td>D7 and D14</td><td>Death or BPD: &gt;28 days oxygen supplementation and beyond 36 weeks of PMA with modified criteria accounting for altitude.</td></tr><tr><td>Özcan<sup>39</sup></td><td>2017, Turkey</td><td>2011-2012</td><td>Retrospective cohort, single center</td><td>Gestational age 24-31 wk; BW 400-1499 g</td><td>246/246</td><td>28</td><td>29.2 (2.15)</td><td>1323 (331.4)</td><td>H12</td><td>Moderate/severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr></tbody><tfoot><tr><td colspan="12" style="text-align: right;">(continued)</td></tr></tfoot></table>
<table><caption>Table I. Continued</caption><thead><tr><th>First author</th><th>Year of publication, country</th><th>Period of data collection</th><th>Study design</th><th>Inclusion criteria</th><th>Number of participants eligible/analyzed</th><th>Number of outcome events</th><th>Gestational age, wk, mean (SD) or median [IQR]</th><th>Birth weight, g, mean ± SD or median [IQR]</th><th>Timing of model assessment</th><th>Defined outcome</th></tr></thead><tbody><tr><td>Bhattacharjee<sup>56</sup></td><td>2020, USA</td><td>2012-2013</td><td>Retrospective cohort, single center</td><td>BW &lt; 1000 g</td><td>69/64</td><td>31</td><td>25 [21-28]</td><td>722 (160)</td><td>Unclear</td><td>Severe BPD: &gt;30% supplemental oxygen and/or positive pressure ventilation or nasal CPAP at 36 weeks of PMA or at time of discharge.</td></tr><tr><td>Oulego-Erroz<sup>55</sup></td><td>2020, Spain</td><td>2017-2019</td><td>Prospective cohort, single center</td><td>Gestational age &lt;32 wk</td><td>42/42</td><td>13</td><td>No/mild BPD 29.5 [28-31.5] BPD/ death 27 [25.7-28.2]</td><td>No/mild BPD 1235g [1110-1507] BPD/ death 890 g [655-1130]</td><td>D7</td><td>Moderate/severe BPD: oxygen supplementation or positive pressure ventilation at 36 weeks of PMA.</td></tr><tr><td>Sotodate<sup>53</sup></td><td>2020, Japan</td><td>2010-2017</td><td>Retrospective cohort, single center</td><td>Gestational age 22-27 wk</td><td>171/152</td><td>69</td><td>25.7 (1.5)</td><td>768 (201)</td><td>H1, H12, and D1 after NICU admission</td><td>Moderate/severe BPD: oxygen supplementation or positive pressure ventilation at 36 weeks of PMA.</td></tr><tr><td>Alonso-Ojembarrena<sup>52</sup></td><td>2019, Spain</td><td>2017-2018</td><td>Prospective cohort, single center</td><td>Gestational age ≤32 wk or BW ≤1500 g</td><td>64/59</td><td>8</td><td>No BPD 29.5 (95% CI 27-32) Mild/ moderate/severe BPD 27.4 (95% CI 23-31)</td><td>No BPD 1241 (95% CI 837-1440 g) Mild/ moderate/severe BPD 914 (95% CI 461-1367)</td><td>D1, D3, D7 and D14</td><td>Moderate/severe BPD: &gt;28 days oxygen supplementation and oxygen supplementation or respiratory support at 36 weeks of PMA and room air challenge.</td></tr><tr><td>Beltempo<sup>50</sup></td><td>2019, Canada</td><td>2010-2015</td><td>Retrospective cohort, multicenter (n = 30)</td><td>Gestational age 22-28<sup>6/7</sup> wk</td><td>9240/7975</td><td>2959</td><td>27 [3-unclear]</td><td>953 (244)</td><td>H12 after NICU admission</td><td>BPD: oxygen supplementation at 36 weeks of PMA or at time of discharge.</td></tr><tr><td>Jung<sup>48</sup></td><td>2019, South Korea</td><td>2010-2014</td><td>Retrospective cohort, single center</td><td>Gestational age &lt;28 wk</td><td>140/138</td><td>66</td><td>No/mild/moderate BPD 26.2 (1.2); death/severe BPD 25.5 (1.4)</td><td>No/mild/moderate BPD 822.36 g (226.6); death/severe BPD 733.79 (214.42)</td><td>D7</td><td>Death or severe BPD: FiO<sub>2</sub> &gt;0.3 or positive pressure ventilation at 36 weeks of PMA.</td></tr><tr><td>Lee<sup>47</sup></td><td>2019, South Korea</td><td>2013-2016</td><td>Prospective cohort, multicenter (n = 67)</td><td>Gestational age 22-32 wk; VLBW</td><td>Group 1 7198/4649 Group 2 7198/6038</td><td>Group 1 1443 Group 2 1916</td><td>Group 1 28.4 (2.4) Group 2 28.3 (2.4)</td><td>Group 1 1070.8 (280.4) Group 2 1058.5 (282.5)</td><td>H1</td><td>Moderate/severe BPD according to NICHD definition.</td></tr><tr><td>Gulliver<sup>42</sup></td><td>2018, USA</td><td>2010-2016</td><td>Prospective cohort, single center</td><td>Gestational age &lt;30 wk</td><td>622/Unknown</td><td>284</td><td>27.0 (1.9)</td><td>963 (301)</td><td>D7 and D14</td><td>Death or BPD: &gt;28 days oxygen supplementation and beyond 36 weeks of PMA with modified criteria accounting for altitude.</td></tr><tr><td>Özcan<sup>39</sup></td><td>2017, Turkey</td><td>2011-2012</td><td>Retrospective cohort, single center</td><td>Gestational age 24-31 wk; BW 400-1499 g</td><td>246/246</td><td>28</td><td>29.2 (2.15)</td><td>1323 (331.4)</td><td>H12</td><td>Moderate/severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr></tbody><tfoot><tr><td colspan="12" style="text-align: right;">(continued)</td></tr></tfoot></table>
<figure><img src="image_19.png" /><figcaption>Table I. Continued</figcaption></figure>

<table><thead><tr><th>First author</th><th>Year of publication, country</th><th>Period of data collection</th><th>Study design</th><th>Inclusion criteria</th><th>Number of participants eligible/analyzed</th><th>Number of outcome events</th><th>Gestational age, wk, mean (SD) or median [IQR]</th><th>Birth weight, g, mean ± SD or median [IQR]</th><th>Timing of model assessment</th><th>Defined outcome</th></tr></thead><tbody><tr><td>Sullivan<sup>36</sup></td><td>2016, USA</td><td>2004-2014</td><td>Retrospective cohort, single center</td><td>BW &lt;1500 g</td><td>566/503</td><td>98</td><td>28.6 (2.9)</td><td>No information</td><td>H12, D1, D7</td><td>Moderate/severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Truog<sup>33</sup></td><td>2014, USA</td><td>2008-2010</td><td>Retrospective cohort, single center</td><td>Gestational age &lt;29 wk</td><td>158/147</td><td>37</td><td>No information</td><td>No information</td><td>D7 and D14</td><td>Death or severe BPD: FiO<sub>2</sub> &gt;0.3 or positive pressure ventilation to maintain SpO<sub>2</sub>&gt;90% at 36 weeks of PMA or at time of discharge.</td></tr><tr><td>Sehgal<sup>31</sup></td><td>2013, Australia</td><td>2010-2012</td><td>Retrospective cohort, single center</td><td>Gestational age &lt;32 wk</td><td>52/52</td><td>27</td><td>26 [25-27]</td><td>788.5 [665.5-941]</td><td>Unclear</td><td>Moderate/severe BPD: oxygen supplementation or respiratory support at 36 weeks of PMA.</td></tr><tr><td>Ambalavanan<sup>30</sup></td><td>2011, USA</td><td>2006</td><td>Prospective cohort, multicenter (n = 14)</td><td>BW 401-1250 g</td><td>2794/Unknown</td><td>1458</td><td>26.7 [25-29]</td><td>874 (230)</td><td>D7</td><td>Death or moderate/severe BPD: positive pressure support or FiO<sub>2</sub> &gt;30% supplemental oxygen with SaO<sub>2</sub> 90%-96% at 36 weeks of PMA and room air challenge.</td></tr><tr><td>Carvalho<sup>29</sup></td><td>2011, Brazil</td><td>2002-2009</td><td>Prospective cohort, multicenter (n = 2)</td><td>Gestational age 24-33 wk</td><td>86/86</td><td>20</td><td>28.0 [24-33]</td><td>772 [360-1498]</td><td>H12</td><td>Moderate/severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Laughon<sup>28</sup></td><td>2011, USA</td><td>2000-2004</td><td>Randomized trial participants, multicenter (n = unclear)</td><td>24-27<sup>6/7</sup> wk</td><td>Group 1 1055/Unknown Group 2 722/Unknown</td><td>Group 1 854<br>Group 2 571</td><td>Group 1 25.7 (1.1)<br>Group 2 25.7 (1.1)</td><td>Group 1 830 (175)<br>Group 2 842 (168)</td><td>D1, D3, D7 and D14</td><td>Death or mild/moderate/severe BPD according to NICHD definition.</td></tr><tr><td>May<sup>24</sup></td><td>2007, United Kingdom</td><td>Group 1 1995-1998<br>Group 2 2004-2005</td><td>Group 1, randomized trial participants; group 2, prospective cohort</td><td>Group 1, gestational age &lt;33 wk; BW &lt;1500 g; group 2, gestational age &lt;33 wk</td><td>Group 1 136/131<br>Group 2 75/75</td><td>Group 1 38 Group 2 22</td><td>Group 1 28 [23-33]<br>Group 2 30 [23-32]</td><td>Group 1 1979 [592-1494]<br>Group 2 1246 [555-2164]</td><td>D2, D7</td><td>Moderate/severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Henderson-Smart<sup>22</sup></td><td>2006, Australia and New Zealand</td><td>2000-2001</td><td>Prospective cohort, multicenter (n = 25)</td><td>Gestational age 22-31 wk</td><td>5854/5854</td><td>1425</td><td>29 [27-30]</td><td>1235 [960-1510]</td><td>At birth</td><td>Moderate/severe BPD: oxygen supplementation or any form of assisted ventilation at 36 weeks of PMA.</td></tr><tr><td>Kim<sup>21</sup></td><td>2005, Korea</td><td>2000-2001</td><td>Prospective cohort</td><td>BW &lt;1500 g</td><td>107/96</td><td>9</td><td>28.5 (1.9)</td><td>1095 (270)</td><td>D4, D7, D10</td><td>Moderate or severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr></tbody><tfoot><tr><td colspan="12" style="text-align: right;">(continued)</td></tr></tfoot></table>
<figure><img src="image_19.png" /><figcaption>Table I. Continued</figcaption></figure>

<table><thead><tr><th>First author</th><th>Year of publication, country</th><th>Period of data collection</th><th>Study design</th><th>Inclusion criteria</th><th>Number of participants eligible/analyzed</th><th>Number of outcome events</th><th>Gestational age, wk, mean (SD) or median [IQR]</th><th>Birth weight, g, mean ± SD or median [IQR]</th><th>Timing of model assessment</th><th>Defined outcome</th></tr></thead><tbody><tr><td>Sullivan<sup>36</sup></td><td>2016, USA</td><td>2004-2014</td><td>Retrospective cohort, single center</td><td>BW &lt;1500 g</td><td>566/503</td><td>98</td><td>28.6 (2.9)</td><td>No information</td><td>H12, D1, D7</td><td>Moderate/severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Truog<sup>33</sup></td><td>2014, USA</td><td>2008-2010</td><td>Retrospective cohort, single center</td><td>Gestational age &lt;29 wk</td><td>158/147</td><td>37</td><td>No information</td><td>No information</td><td>D7 and D14</td><td>Death or severe BPD: FiO<sub>2</sub> &gt;0.3 or positive pressure ventilation to maintain SpO<sub>2</sub>&gt;90% at 36 weeks of PMA or at time of discharge.</td></tr><tr><td>Sehgal<sup>31</sup></td><td>2013, Australia</td><td>2010-2012</td><td>Retrospective cohort, single center</td><td>Gestational age &lt;32 wk</td><td>52/52</td><td>27</td><td>26 [25-27]</td><td>788.5 [665.5-941]</td><td>Unclear</td><td>Moderate/severe BPD: oxygen supplementation or respiratory support at 36 weeks of PMA.</td></tr><tr><td>Ambalavanan<sup>30</sup></td><td>2011, USA</td><td>2006</td><td>Prospective cohort, multicenter (n = 14)</td><td>BW 401-1250 g</td><td>2794/Unknown</td><td>1458</td><td>26.7 [25-29]</td><td>874 (230)</td><td>D7</td><td>Death or moderate/severe BPD: positive pressure support or FiO<sub>2</sub> &gt;30% supplemental oxygen with SaO<sub>2</sub> 90%-96% at 36 weeks of PMA and room air challenge.</td></tr><tr><td>Carvalho<sup>29</sup></td><td>2011, Brazil</td><td>2002-2009</td><td>Prospective cohort, multicenter (n = 2)</td><td>Gestational age 24-33 wk</td><td>86/86</td><td>20</td><td>28.0 [24-33]</td><td>772 [360-1498]</td><td>H12</td><td>Moderate/severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Laughon<sup>28</sup></td><td>2011, USA</td><td>2000-2004</td><td>Randomized trial participants, multicenter (n = unclear)</td><td>24-27<sup>6/7</sup> wk</td><td>Group 1 1055/Unknown Group 2 722/Unknown</td><td>Group 1 854<br>Group 2 571</td><td>Group 1 25.7 (1.1)<br>Group 2 25.7 (1.1)</td><td>Group 1 830 (175)<br>Group 2 842 (168)</td><td>D1, D3, D7 and D14</td><td>Death or mild/moderate/severe BPD according to NICHD definition.</td></tr><tr><td>May<sup>24</sup></td><td>2007, United Kingdom</td><td>Group 1 1995-1998<br>Group 2 2004-2005</td><td>Group 1, randomized trial participants; group 2, prospective cohort</td><td>Group 1, gestational age &lt;33 wk; BW &lt;1500 g; group 2, gestational age &lt;33 wk</td><td>Group 1 136/131<br>Group 2 75/75</td><td>Group 1 38 Group 2 22</td><td>Group 1 28 [23-33]<br>Group 2 30 [23-32]</td><td>Group 1 1979 [592-1494]<br>Group 2 1246 [555-2164]</td><td>D2, D7</td><td>Moderate/severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Henderson-Smart<sup>22</sup></td><td>2006, Australia and New-Zealand</td><td>2000-2001</td><td>Prospective cohort, multicenter (n = 25)</td><td>Gestational age 22-31 wk</td><td>5854/5854</td><td>1425</td><td>29 [27-30]</td><td>1235 [960-1510]</td><td>At birth</td><td>Moderate/severe BPD: oxygen supplementation or any form of assisted ventilation at 36 weeks of PMA.</td></tr><tr><td>Kim<sup>21</sup></td><td>2005, Korea</td><td>2000-2001</td><td>Prospective cohort</td><td>BW &lt;1500 g</td><td>107/96</td><td>9</td><td>28.5 (1.9)</td><td>1095 (270)</td><td>D4, D7, D10</td><td>Moderate or severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr></tbody><tfoot><tr><td colspan="12" style="text-align: right;">(continued)</td></tr></tfoot></table>
<figure><img src="image_20.png" /></figure>

<table><caption>Table I. Continued</caption><thead><tr><th>First author</th><th>Year of publication, country</th><th>Period of data collection</th><th>Study design</th><th>Inclusion criteria</th><th>Number of participants eligible/analyzed</th><th>Number of outcome events</th><th>Gestational age, wk, mean (SD) or median [IQR]</th><th>Birth weight, g, mean ± SD or median [IQR]</th><th>Timing of model assessment</th><th>Defined outcome</th></tr></thead><tbody><tr><td>Greenough<sup>20</sup></td><td>2004, United Kingdom</td><td>Group 1 1998-2001<br>Group 2 1995-1998</td><td>Randomized trial participants, single center</td><td>Group 1, gestational age 23-28 wk<br>Group 2, BW ≤1500</td><td>Group 1 59/48 Group 2 40/32</td><td>Group 1 39 Group 2 18</td><td>Group 1 26 [24-28.6]<br>Group 2 27 [25-31]</td><td>Group 1 768 [528-1097]<br>Group 2 820 [590-1450]</td><td>D7</td><td>Moderate/severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Chien<sup>18</sup></td><td>2002, Canada</td><td>1996-1997</td><td>Unclear, multicenter (n = 17)</td><td>Gestational age ≤32 wk</td><td>4907/4226</td><td>Unknown</td><td>29 (2)</td><td>1390 (457)</td><td>H12</td><td>Moderate/severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Yoder<sup>16</sup></td><td>1999, USA</td><td>1993-1995</td><td>Group 1 prospective cohort, single center<br>Group 2 retrospective cohort, multicenter (n = 2)</td><td>Gestational age ≤29 wk;<br>BW ≤1000 g</td><td>Group 1 54/54 Group 2 56/56 Group 3 158/158</td><td>Group 1 14 Group 2 19<br>Group 3 48</td><td>Group 1 27 (2)<br>Group 2 26 (2)<br>Group 3 unknown</td><td>Group 1 919 (217)<br>Group 2 892 (228)<br>Group 3 unknown</td><td>H12, H72</td><td>Death or BPD: oxygen supplementation at 36 weeks of PMA and abnormal chest radiograph. Death after D7 related to persistent severe pulmonary disease.</td></tr><tr><td>Hentschel<sup>15</sup></td><td>1998, Germany</td><td>1991-1993</td><td>Retrospective cohort, single center</td><td>BW <1500 g</td><td>Group 1 195/156<br>Group 2 195/168<br>Group 3 195/152<br>Group 4 195/157<br>Group 5 195/164<br>Group 6 195/179<br>Group 7 195/104<br>Group 8 195/119</td><td>Group 1 unknown<br>Group 2 72<br>Group 3 unknown<br>Group 4 72<br>Group 5 Unknown<br>Group 6 72<br>Group 7 unknown<br>Group 8 72</td><td>28.57 (2) [23.0-35.0]</td><td>1101 (281) [440-1495]</td><td>At admission, H12, D10</td><td>4 models with outcome moderate/severe BPD: oxygen supplementation at 36 weeks of PMA. 4 models with outcome death/ BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Subhedar<sup>14</sup></td><td>1998, United Kingdom</td><td>1994-1996</td><td>Prospective cohort, single center (same center)</td><td>Gestational age <32 wk</td><td>28/28</td><td>23</td><td>29 [24-31]</td><td>1044 [520-1720]</td><td>H24</td><td>Death or BPD: >28 days oxygen supplementation and oxygen supplementation beyond 36 weeks of PMA.</td></tr><tr><td>Ryan<sup>13</sup></td><td>1996, United Kingdom</td><td>1993</td><td>Retrospective cohort, single center (same center)</td><td>Gestational age <32 wk</td><td>47/Unknown</td><td>Unknown</td><td>Unknown</td><td>Unknown</td><td>D4</td><td>Moderate/severe BPD: oxygen supplementation to achieve SaO<sub>2</sub> >92% at 36 weeks of PMA and abnormal chest radiograph.</td></tr></tbody></table>

BPD, bronchopulmonary dysplasia; BW, birth weight; CPAP, continuous positive airway pressure; ELBW, extremely low birth weight; FiO<sub>2</sub>, fraction of inspired oxygen; NICHD, Eunice Kennedy Shriver National Institute of Child Health and Human Development; NICU, neonatal intensive care unit; NIH, National Institutes of Health; PMA, postmenstrual age; SaO<sub>2</sub>, arterial oxygen saturation; WG, weeks of gestation.
<figure><img src="image_20.png" /></figure>

<table><caption>Table I. Continued</caption><thead><tr><th>First author</th><th>Year of publication, country</th><th>Period of data collection</th><th>Study design</th><th>Inclusion criteria</th><th>Number of participants eligible/analyzed</th><th>Number of outcome events</th><th>Gestational age, wk, mean (SD) or median [IQR]</th><th>Birth weight, g, mean ± SD or median [IQR]</th><th>Timing of model assessment</th><th>Defined outcome</th></tr></thead><tbody><tr><td>Greenough<sup>20</sup></td><td>2004, United Kingdom</td><td>Group 1 1998-2001<br>Group 2 1995-1998</td><td>Randomized trial participants, single center</td><td>Group 1, gestational age 23-28 wk<br>Group 2, BW ≤1500</td><td>Group 1 59/48 Group 2 40/32</td><td>Group 1 39 Group 2 18</td><td>Group 1 26 [24-28.6]<br>Group 2 27 [25-31]</td><td>Group 1 768 [528-1097]<br>Group 2 820 [590-1450]</td><td>D7</td><td>Moderate/severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Chien<sup>18</sup></td><td>2002, Canada</td><td>1996-1997</td><td>Unclear, multicenter (n = 17)</td><td>Gestational age ≤32 wk</td><td>4907/4226</td><td>Unknown</td><td>29 (2)</td><td>1390 (457)</td><td>H12</td><td>Moderate/severe BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Yoder<sup>16</sup></td><td>1999, USA</td><td>1993-1995</td><td>Group 1 prospective cohort, single center<br>Group 2 retrospective cohort, multicenter (n = 2)</td><td>Gestational age ≤29 wk;<br>BW ≤1000 g</td><td>Group 1 54/54 Group 2 56/56 Group 3 158/158</td><td>Group 1 14 Group 2 19<br>Group 3 48</td><td>Group 1 27 (2)<br>Group 2 26 (2)<br>Group 3 unknown</td><td>Group 1 919 (217)<br>Group 2 892 (228)<br>Group 3 unknown</td><td>H12, H72</td><td>Death or BPD: oxygen supplementation at 36 weeks of PMA and abnormal chest radiograph. Death after D7 related to persistent severe pulmonary disease.</td></tr><tr><td>Hentschel<sup>15</sup></td><td>1998, Germany</td><td>1991-1993</td><td>Retrospective cohort, single center</td><td>BW &lt;1500 g</td><td>Group 1 195/156<br>Group 2 195/168<br>Group 3 195/152<br>Group 4 195/157<br>Group 5 195/164<br>Group 6 195/179<br>Group 7 195/104<br>Group 8 195/119</td><td>Group 1 unknown<br>Group 2 72<br>Group 3 unknown<br>Group 4 72<br>Group 5 Unknown<br>Group 6 72<br>Group 7 unknown<br>Group 8 72</td><td>28.57 (2) [23.0-35.0]</td><td>1101 (281) [440-1495]</td><td>At admission, H12, D10</td><td>4 models with outcome moderate/severe BPD: oxygen supplementation at 36 weeks of PMA. 4 models with outcome death/ BPD: oxygen supplementation at 36 weeks of PMA.</td></tr><tr><td>Subhedar<sup>14</sup></td><td>1998, United Kingdom</td><td>1994-1996</td><td>Prospective cohort, single center (same center)</td><td>Gestational age &lt;32 wk</td><td>28/28</td><td>23</td><td>29 [24-31]</td><td>1044 [520-1720]</td><td>H24</td><td>Death or BPD: &gt;28 days oxygen supplementation and oxygen supplementation beyond 36 weeks of PMA.</td></tr><tr><td>Ryan<sup>13</sup></td><td>1996, United Kingdom</td><td>1993</td><td>Retrospective cohort, single center (same center)</td><td>Gestational age &lt;32 wk</td><td>47/Unknown</td><td>Unknown</td><td>Unknown</td><td>Unknown</td><td>D4</td><td>Moderate/severe BPD: oxygen supplementation to achieve SaO<sub>2</sub> &gt;92% at 36 weeks of PMA and abnormal chest radiograph.</td></tr></tbody></table>

BPD, bronchopulmonary dysplasia; BW, birth weight; CPAP, continuous positive airway pressure; ELBW, extremely low birth weight; FiO<sub>2</sub>, fraction of inspired oxygen; NICHD, Eunice Kennedy Shriver National Institute of Child Health and Human Development; NICU, neonatal intensive care unit; NIH, National Institutes of Health; PMA, postmenstrual age; SaO<sub>2</sub>, arterial oxygen saturation; WG, weeks of gestation.
<figure><img src="image_21.png" /><figcaption>Table III. Risk of bias and applicability assessment for A, each development model and B, for each validated model</figcaption></figure>

<table><thead><tr><th rowspan="2">Study</th><th rowspan="2">Year</th><th rowspan="2">Model description<br>(outcome, timing, type of predictors)</th><th colspan="4">RoB</th><th colspan="3">Applicability</th><th colspan="2">Overall</th></tr><tr><th>Participants</th><th>Predictors</th><th>Outcome</th><th>Analysis</th><th>Participants</th><th>Predictors</th><th>Outcome</th><th>RoB</th><th>Applicability</th></tr></thead><tbody><tr><td rowspan="2">Developmental models<br>Ahmed<sup>70</sup></td><td rowspan="2">2022</td><td>BPD, &lt;H72, urinary biomarkers</td><td>?</td><td>+</td><td>+</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>BPD, &lt;H72, urinary biomarkers</td><td>?</td><td>+</td><td>+</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td rowspan="8">Alonso-Ojembarrena<sup>71</sup></td><td rowspan="8">2022</td><td>BPD, D1, LUS score + blood biomarkers</td><td>+</td><td>+</td><td>●</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>BPD, D3, LUS score + blood biomarkers</td><td>+</td><td>+</td><td>●</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>BPD, D7, LUS score + blood biomarkers</td><td>+</td><td>+</td><td>●</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>BPD, D14, LUS score + blood biomarkers</td><td>+</td><td>+</td><td>●</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>BPD, D7, clinical data</td><td>+</td><td>+</td><td>●</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>BPD, D7, LUS score + clinical data</td><td>+</td><td>+</td><td>●</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>BPD, D7, LUS score + blood biomarkers + clinical data</td><td>+</td><td>+</td><td>●</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>BPD, D7, LUS score + blood biomarkers + clinical data</td><td>+</td><td>+</td><td>●</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td rowspan="4">Greenberg<sup>72</sup></td><td rowspan="4">2022</td><td>Death/BPD, D1, clinical data</td><td>+</td><td>+</td><td>●</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>Death/BPD, D3, clinical data</td><td>+</td><td>+</td><td>●</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>Death/BPD, D7, clinical data</td><td>+</td><td>+</td><td>●</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>Death/BPD, D14, clinical data</td><td>+</td><td>+</td><td>●</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>Kindt<sup>73</sup></td><td>2022</td><td>BPD, &lt;D7, blood biomarkers</td><td>+</td><td>+</td><td>●</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>Umapathi<sup>74</sup></td><td>2022</td><td>BPD, &lt;D7, echocardiographic data</td><td>+</td><td>+</td><td>●</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>Zayat<sup>75</sup></td><td>2022</td><td>BPD, D14, clinical data</td><td>+</td><td>+</td><td>●</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>Aldecoa-Bilbao<sup>57</sup></td><td>2021</td><td>BPD, D7, LUS score + clinical data</td><td>+</td><td>+</td><td>●</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td rowspan="2">Alonso-Ojembarrena<sup>52</sup></td><td rowspan="2">2021</td><td>BPD, at admission, clinical data</td><td>+</td><td>+</td><td>●</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>BPD, D3, clinical data</td><td>+</td><td>+</td><td>●</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td></td><td></td><td>BPD, D3, LUS score + clinical data</td><td>+</td><td>+</td><td>●</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr></tbody></table>

(continued)
<figure><img src="image_21.png" /><figcaption>Table III. Risk of bias and applicability assessment for A, each development model and B, for each validated model</figcaption></figure>

<table><thead><tr><th rowspan="2">Study</th><th rowspan="2">Year</th><th rowspan="2">Model description<br>(outcome, timing, type of predictors)</th><th colspan="4">RoB</th><th colspan="3">Applicability</th><th colspan="2">Overall</th></tr><tr><th>Participants</th><th>Predictors</th><th>Outcome</th><th>Analysis</th><th>Participants</th><th>Predictors</th><th>Outcome</th><th>RoB</th><th>Applicability</th></tr></thead><tbody><tr><td rowspan="2">Developmental models<br>Ahmed<sup>70</sup></td><td rowspan="2">2022</td><td>BPD, &lt;H72, urinary biomarkers</td><td>?</td><td>+</td><td>+</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>BPD, &lt;H72, urinary biomarkers</td><td>?</td><td>+</td><td>+</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td rowspan="7">Alonso-Ojembarrena<sup>71</sup></td><td rowspan="7">2022</td><td>BPD, D1, LUS score + blood biomarkers</td><td>+</td><td>+</td><td>+</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>BPD, D3, LUS score + blood biomarkers</td><td>+</td><td>+</td><td>+</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>BPD, D7, LUS score + blood biomarkers</td><td>+</td><td>+</td><td>+</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>BPD, D14, LUS score + blood biomarkers</td><td>+</td><td>+</td><td>+</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>BPD, D7, clinical data</td><td>+</td><td>+</td><td>+</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>BPD, D7, LUS score + clinical data</td><td>+</td><td>+</td><td>+</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>BPD, D7, LUS score + blood biomarkers + clinical data</td><td>+</td><td>+</td><td>+</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td rowspan="4">Greenberg<sup>72</sup></td><td rowspan="4">2022</td><td>BPD, D7, LUS score + blood biomarkers + clinical data</td><td>+</td><td>+</td><td>+</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>Death/BPD, D1, clinical data</td><td>+</td><td>+</td><td>?</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>Death/BPD, D3, clinical data</td><td>+</td><td>+</td><td>?</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>Death/BPD, D7, clinical data</td><td>+</td><td>+</td><td>?</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>Kindt<sup>73</sup></td><td>2022</td><td>BPD, &lt;D7, blood biomarkers</td><td>+</td><td>+</td><td>?</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>Umapathi<sup>74</sup></td><td>2022</td><td>BPD, &lt;D7, echocardiographic data</td><td>+</td><td>+</td><td>+</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>Zayat<sup>75</sup></td><td>2022</td><td>BPD, D14, clinical data</td><td>+</td><td>+</td><td>+</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>Aldecoa-Bilbao<sup>57</sup></td><td>2021</td><td>BPD, D7, LUS score + clinical data</td><td>+</td><td>+</td><td>+</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td rowspan="2">Alonso-Ojembarrena<sup>52</sup></td><td rowspan="2">2021</td><td>BPD, at admission, clinical data</td><td>+</td><td>+</td><td>+</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>BPD, D3, clinical data</td><td>+</td><td>+</td><td>+</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td></td><td></td><td>BPD, D3, LUS score + clinical data</td><td>+</td><td>+</td><td>+</td><td>●</td><td>+</td><td>●</td><td>●</td><td>●</td><td>●</td></tr></tbody></table>

(continued)