cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.25075424
title: Supplementary material: Cost–effectiveness analysis of Avance allograft for the treatment of peripheral nerve injuries in the USA

description: <b>These are peer-reviewed supplementary tables and figure for the article '</b><b>Cost–effectiveness analysis of Avance allograft for the treatment of peripheral nerve injuries in the USA</b><b>' published in the</b><b> </b><b><i>Journal of Comparative Effectiveness Research</i></b><b>.</b><b>Figure S1:</b> Markov model structure<b>Table S1: </b>Transition probabilities and clinical complication rates<b>Table S2: </b>Cost distribution for nerve repair surgery procedure<b>T</b><b>able S3:</b> Cost input parameters included in the economic model<b>Aim:</b> Peripheral nerve injury (PNI) is a debilitating condition with significant associated morbidity, and which places a substantial socioeconomic burden on healthcare systems worldwide. Recently, allograft has emerged as a viable surgical alternative to autograft for the treatment of PNI. This study evaluated the cost effectiveness of allograft (Avance R ? Nerve Graft) compared with autograft for the peripheral nerve repair, from a US payer perspective. <b>Methods: </b>A Markov cohort model was developed to consider the treatment pathways followed by a patient population undergoing a single transected nerve repair with either allograft, or autograft. The marginal difference in meaningful recovery (MR) (effectiveness), and costs, between the two groups were estimated over a lifetime horizon. Deterministic and probabilistic sensitivity analyses (PSA) were performed to consider the uncertainty surrounding the base-case input parameter values and their effect on the overall incremental cost–effectiveness ratio (ICER). <b>Results: </b>The base-case analysis indicates that there is a small difference in the average probability of MR between the two groups (75.15% vs 70.46%; +4.69% with allograft). Allograft also results in cost savings ($12,677 vs $14,023; -$-1346 with allograft) compared with autograft. Deterministic sensitivity analysis shows that the costs of the initial surgical procedures are the main drivers of incremental cost, but that the intervention is likely to be cost saving compared with autograft regardless of the parameter variations made. <b>Conclusion:</b> The use of allograft with the Avance Nerve Graft has the potential to be a cost-effective alternative to autograft for the surgical treatment of PNI in the USA.
DOI: 10.6084/m9.figshare.25075424.v1
title: Supplementary material: Cost–effectiveness analysis of Avance allograft for the treatment of peripheral nerve injuries in the USA

description: <b>These are peer-reviewed supplementary tables and figure for the article '</b><b>Cost–effectiveness analysis of Avance allograft for the treatment of peripheral nerve injuries in the USA</b><b>' published in the</b><b> </b><b><i>Journal of Comparative Effectiveness Research</i></b><b>.</b><b>Figure S1:</b> Markov model structure<b>Table S1: </b>Transition probabilities and clinical complication rates<b>Table S2: </b>Cost distribution for nerve repair surgery procedure<b>T</b><b>able S3:</b> Cost input parameters included in the economic model<b>Aim:</b> Peripheral nerve injury (PNI) is a debilitating condition with significant associated morbidity, and which places a substantial socioeconomic burden on healthcare systems worldwide. Recently, allograft has emerged as a viable surgical alternative to autograft for the treatment of PNI. This study evaluated the cost effectiveness of allograft (Avance R ? Nerve Graft) compared with autograft for the peripheral nerve repair, from a US payer perspective. <b>Methods: </b>A Markov cohort model was developed to consider the treatment pathways followed by a patient population undergoing a single transected nerve repair with either allograft, or autograft. The marginal difference in meaningful recovery (MR) (effectiveness), and costs, between the two groups were estimated over a lifetime horizon. Deterministic and probabilistic sensitivity analyses (PSA) were performed to consider the uncertainty surrounding the base-case input parameter values and their effect on the overall incremental cost–effectiveness ratio (ICER). <b>Results: </b>The base-case analysis indicates that there is a small difference in the average probability of MR between the two groups (75.15% vs 70.46%; +4.69% with allograft). Allograft also results in cost savings ($12,677 vs $14,023; -$-1346 with allograft) compared with autograft. Deterministic sensitivity analysis shows that the costs of the initial surgical procedures are the main drivers of incremental cost, but that the intervention is likely to be cost saving compared with autograft regardless of the parameter variations made. <b>Conclusion:</b> The use of allograft with the Avance Nerve Graft has the potential to be a cost-effective alternative to autograft for the surgical treatment of PNI in the USA.
DOI: 10.6084/m9.figshare.25075391
title: Supplementary materials: Real-world assessment of treatment inertia in the management of patients treated for major depressive disorder in the USA

description: <b>These are peer-reviewed supplementary tables for the article '</b><b>Real-world assessment of treatment inertia in the management of patients treated for major depressive disorder in the USA</b><b>' published in the</b><b> </b><b><i>Journal of Comparative Effectiveness Research</i></b><b>.</b><br><b>Supplementary Table 1: </b>MDD ICD-9/10 diagnosis codes<b>Supplementary Table 2: </b>Factors influencing likelihood of treatment inertia in patients with elevated PHQ-9 score<b>Aim:</b> Major depressive disorder (MDD) is a debilitating illness in which depressive symptoms may persist after treatment. Treatment inertia is the continued use of the same pharmacotherapy regimen when treatment goals are not met. This study assessed the frequency of treatment inertia among adult patients with MDD treated in a real-world setting. <b>Patients & methods:</b> This was a retrospective, observational study of patients with MDD identified in the Decision Resources Group Real World Evidence US Data Repository from January 2014 to June 2018. Patients (≥18 years) had an elevated Patient Health Questionnaire-9 (PHQ-9) score (≥5) following 8 weeks of stable baseline antidepressant use with/without mental-health outpatient therapy. Treatment inertia, modification and discontinuation were evaluated over a 16-week follow-up period (timeline based on the APA Practice Guidelines). The primary outcome was the proportion of MDD patients experiencing treatment inertia. <b>Results:</b> 2850 patients (median age, 55 years; 74% female) met the study criteria. Of these patients, 834 (29%) had study-defined treatment inertia, 1534 (54%) received treatment modification and 482 (17%) discontinued treatment. Use of mirtazapine (Odd ratio [OR]: 0.63; 95% confidence interval [CI]: 0.50–0.79), selective serotonin reuptake inhibitors (OR: 0.64; 95% CI: 0.54–0.75) or bupropion (OR: 0.71; 95% CI: 0.60–0.84) in the baseline period was associated with an increased likelihood of treatment modification versus not receiving treatment with these medications. Frequency of treatment inertia may differ among those who do not have a documented PHQ-9 score. <b>Conclusion:</b> Effective symptom management is critical for optimal outcomes in MDD. Results demonstrate that treatment inertia is common in MDD despite guidelines recommending treatment modification in patients not reaching remission.
DOI: 10.6084/m9.figshare.25075391.v1
title: Supplementary materials: Real-world assessment of treatment inertia in the management of patients treated for major depressive disorder in the USA

description: <b>These are peer-reviewed supplementary tables for the article '</b><b>Real-world assessment of treatment inertia in the management of patients treated for major depressive disorder in the USA</b><b>' published in the</b><b> </b><b><i>Journal of Comparative Effectiveness Research</i></b><b>.</b><br><b>Supplementary Table 1: </b>MDD ICD-9/10 diagnosis codes<b>Supplementary Table 2: </b>Factors influencing likelihood of treatment inertia in patients with elevated PHQ-9 score<b>Aim:</b> Major depressive disorder (MDD) is a debilitating illness in which depressive symptoms may persist after treatment. Treatment inertia is the continued use of the same pharmacotherapy regimen when treatment goals are not met. This study assessed the frequency of treatment inertia among adult patients with MDD treated in a real-world setting. <b>Patients & methods:</b> This was a retrospective, observational study of patients with MDD identified in the Decision Resources Group Real World Evidence US Data Repository from January 2014 to June 2018. Patients (≥18 years) had an elevated Patient Health Questionnaire-9 (PHQ-9) score (≥5) following 8 weeks of stable baseline antidepressant use with/without mental-health outpatient therapy. Treatment inertia, modification and discontinuation were evaluated over a 16-week follow-up period (timeline based on the APA Practice Guidelines). The primary outcome was the proportion of MDD patients experiencing treatment inertia. <b>Results:</b> 2850 patients (median age, 55 years; 74% female) met the study criteria. Of these patients, 834 (29%) had study-defined treatment inertia, 1534 (54%) received treatment modification and 482 (17%) discontinued treatment. Use of mirtazapine (Odd ratio [OR]: 0.63; 95% confidence interval [CI]: 0.50–0.79), selective serotonin reuptake inhibitors (OR: 0.64; 95% CI: 0.54–0.75) or bupropion (OR: 0.71; 95% CI: 0.60–0.84) in the baseline period was associated with an increased likelihood of treatment modification versus not receiving treatment with these medications. Frequency of treatment inertia may differ among those who do not have a documented PHQ-9 score. <b>Conclusion:</b> Effective symptom management is critical for optimal outcomes in MDD. Results demonstrate that treatment inertia is common in MDD despite guidelines recommending treatment modification in patients not reaching remission.
DOI: 10.6084/m9.figshare.25075346
title: Supplementary figures: Improved estimation of overall survival and progression-free survival for state transition modeling

description: <b>These are peer-reviewed supplementary figures for the article </b><b>'</b><b>Improved estimation of overall survival and progression-free survival for state transition modeling</b><b>' published in the</b><b> </b><b><i>Journal of Comparative Effectiveness Research</i></b><b>.</b><br><b>Figure S1: </b>Standard approach: Overview of distributions by health state transitions<b>Figure S2: </b>Novel approach: Overview of distributions by health state transitions<b>Aim:</b> National Institute for Health and Care Excellence guidance (Technical Support Document 19) highlights a key challenge of state transition models (STMs) being their difficulty in achieving a satisfactory fit to the observed within-trial endpoints. Fitting poorly to data over the trial period can then have implications for long-term extrapolations. A novel estimation approach is defined in which the predicted overall survival (OS) and progression-free survival (PFS) extrapolations from an STM are optimized to provide closer estimates of the within-trial endpoints. <b>Materials & methods:</b> An STM was fitted to the SQUIRE trial data in non-small-cell lung cancer (obtained from Project Data Sphere). Two methods were used: a standard approach whereby the maximum likelihood was utilized for the individual transitions and the best-fitting parametric model selected based on AIC/BIC, and a novel approach in which parameters were optimized by minimizing the area between the STM-predicted OS and PFS curves and the corresponding OS and PFS Kaplan–Meier curves. Sensitivity analyses were conducted to assess uncertainty. <b>Results:</b> The novel approach resulted in closer estimations to the OS and PFS Kaplan–Meier for all combinations of parametric distributions analyzed compared with the standard approach. Though the uncertainty associated with the novel approach was slightly larger, it provided better estimates to the restricted mean survival time in 10 of the 12 parametric distributions analyzed. <b>Conclusion:</b> A novel approach is defined which provides an alternative STM estimation method enabling improved fits to modeled endpoints, which can easily be extended to more complex model structures.
DOI: 10.6084/m9.figshare.25075346.v1
title: Supplementary figures: Improved estimation of overall survival and progression-free survival for state transition modeling

description: <b>These are peer-reviewed supplementary figures for the article </b><b>'</b><b>Improved estimation of overall survival and progression-free survival for state transition modeling</b><b>' published in the</b><b> </b><b><i>Journal of Comparative Effectiveness Research</i></b><b>.</b><br><b>Figure S1: </b>Standard approach: Overview of distributions by health state transitions<b>Figure S2: </b>Novel approach: Overview of distributions by health state transitions<b>Aim:</b> National Institute for Health and Care Excellence guidance (Technical Support Document 19) highlights a key challenge of state transition models (STMs) being their difficulty in achieving a satisfactory fit to the observed within-trial endpoints. Fitting poorly to data over the trial period can then have implications for long-term extrapolations. A novel estimation approach is defined in which the predicted overall survival (OS) and progression-free survival (PFS) extrapolations from an STM are optimized to provide closer estimates of the within-trial endpoints. <b>Materials & methods:</b> An STM was fitted to the SQUIRE trial data in non-small-cell lung cancer (obtained from Project Data Sphere). Two methods were used: a standard approach whereby the maximum likelihood was utilized for the individual transitions and the best-fitting parametric model selected based on AIC/BIC, and a novel approach in which parameters were optimized by minimizing the area between the STM-predicted OS and PFS curves and the corresponding OS and PFS Kaplan–Meier curves. Sensitivity analyses were conducted to assess uncertainty. <b>Results:</b> The novel approach resulted in closer estimations to the OS and PFS Kaplan–Meier for all combinations of parametric distributions analyzed compared with the standard approach. Though the uncertainty associated with the novel approach was slightly larger, it provided better estimates to the restricted mean survival time in 10 of the 12 parametric distributions analyzed. <b>Conclusion:</b> A novel approach is defined which provides an alternative STM estimation method enabling improved fits to modeled endpoints, which can easily be extended to more complex model structures.
DOI: 10.5281/zenodo.10618198
title: List of hermit crab interacting with gastropod

description: A list of interactions between hermit crabs interacting with empty gastropod shells is provided here. Cephalotoracic shield length, shell width and length are measured in milimeters. Internal volume and weigth are measured in mililitters and grams respectively. 

Cephalotoracic shield length refers to the length of the protective covering that combines the head (cephalon) and the thorax (thoracic) regions of hermit crab.

Hermit crab measure = Cephalotoracic shield length

Shell measures = shell width, shell length, internal volume and weigth
DOI: 10.5281/zenodo.10618199
title: List of hermit crab interacting with gastropod

description: A list of interactions between hermit crabs interacting with empty gastropod shells is provided here. Cephalotoracic shield length, shell width and length are measured in milimeters. Internal volume and weigth are measured in mililitters and grams respectively. 

Cephalotoracic shield length refers to the length of the protective covering that combines the head (cephalon) and the thorax (thoracic) regions of hermit crab.

Hermit crab measure = Cephalotoracic shield length

Shell measures = shell width, shell length, internal volume and weigth
DOI: 10.24403/jp.1318906
title: Barthlott, W., Porembski, S. Seine, R. & Theisen, L: Karnivoren. Biologie und Kultur Fleischfressender Pflanzen. - Verlag Eugen Ulmer, Stuttgart 2004. / [rezensiert von] H. Manitz
DOI: 10.24403/jp.1318909
title: Müller, F.: Verbreitungsatlas der Moose Sachsens. - Lutra Verlags- und Vertriebsgesellschaft, Teuer 2004. / [rezensiert von] H. Manitz
DOI: 10.6084/m9.figshare.25071107
title: Appendix: Visualizing the target estimand in comparative effectiveness studies with multiple treatments

description: <b>These are peer-reviewed supplementary materials for the article '</b><b>Visualizing the target estimand in comparative effectiveness studies with multiple treatments</b><b>' published in the</b><b> </b><b><i>Journal of Comparative Effectiveness Research</i></b><b>.</b><br>Data-generating mechanismAdditional resultsAdditional Multiple Sclerosis Case Study Methods and ResultsAdditional methodsCohort DefinitionDetails on baseline covariatesMissing data imputationMatchingAdditional resultsMissing data patternBaseline Characteristics Before ImputationBaseline characteristics after imputationAdditional bivariate ellipsesTreatment effect heterogeneity explorationAssessment of matching implementationJoy plotsReferences<b>Aim: </b>Comparative effectiveness research using real-world data often involves pairwise propensity score matching to adjust for confounding bias. We show that corresponding treatment effect estimates may have limited external validity, and propose two visualization tools to clarify the target estimand. <b>Materials & methods:</b> We conduct a simulation study to demonstrate, with bivariate ellipses and joy plots, that differences in covariate distributions across treatment groups may affect the external validity of treatment effect estimates. We showcase how these visualization tools can facilitate the interpretation of target estimands in a case study comparing the effectiveness of teriflunomide (TERI), dimethyl fumarate (DMF) and natalizumab (NAT) on manual dexterity in patients with multiple sclerosis. <b>Results:</b> In the simulation study, estimates of the treatment effect greatly differed depending on the target population. For example, when comparing treatment B with C, the estimated treatment effect (and respective standard error) varied from -0.27 (0.03) to -0.37 (0.04) in the type of patients initially receiving treatment B and C, respectively. Visualization of the matched samples revealed that covariate distributions vary for each comparison and cannot be used to target one common treatment effect for the three treatment comparisons. In the case study, the bivariate distribution of age and disease duration varied across the population of patients receiving TERI, DMF or NAT. Although results suggest that DMF and NAT improve manual dexterity at 1 year compared with TERI, the effectiveness of DMF versus NAT differs depending on which target estimand is used. <b>Conclusion:</b> Visualization tools may help to clarify the target population in comparative effectiveness studies and resolve ambiguity about the interpretation of estimated treatment effects.
DOI: 10.6084/m9.figshare.25071107.v1
title: Appendix: Visualizing the target estimand in comparative effectiveness studies with multiple treatments

description: <b>These are peer-reviewed supplementary materials for the article '</b><b>Visualizing the target estimand in comparative effectiveness studies with multiple treatments</b><b>' published in the</b><b> </b><b><i>Journal of Comparative Effectiveness Research</i></b><b>.</b><br>Data-generating mechanismAdditional resultsAdditional Multiple Sclerosis Case Study Methods and ResultsAdditional methodsCohort DefinitionDetails on baseline covariatesMissing data imputationMatchingAdditional resultsMissing data patternBaseline Characteristics Before ImputationBaseline characteristics after imputationAdditional bivariate ellipsesTreatment effect heterogeneity explorationAssessment of matching implementationJoy plotsReferences<b>Aim: </b>Comparative effectiveness research using real-world data often involves pairwise propensity score matching to adjust for confounding bias. We show that corresponding treatment effect estimates may have limited external validity, and propose two visualization tools to clarify the target estimand. <b>Materials & methods:</b> We conduct a simulation study to demonstrate, with bivariate ellipses and joy plots, that differences in covariate distributions across treatment groups may affect the external validity of treatment effect estimates. We showcase how these visualization tools can facilitate the interpretation of target estimands in a case study comparing the effectiveness of teriflunomide (TERI), dimethyl fumarate (DMF) and natalizumab (NAT) on manual dexterity in patients with multiple sclerosis. <b>Results:</b> In the simulation study, estimates of the treatment effect greatly differed depending on the target population. For example, when comparing treatment B with C, the estimated treatment effect (and respective standard error) varied from -0.27 (0.03) to -0.37 (0.04) in the type of patients initially receiving treatment B and C, respectively. Visualization of the matched samples revealed that covariate distributions vary for each comparison and cannot be used to target one common treatment effect for the three treatment comparisons. In the case study, the bivariate distribution of age and disease duration varied across the population of patients receiving TERI, DMF or NAT. Although results suggest that DMF and NAT improve manual dexterity at 1 year compared with TERI, the effectiveness of DMF versus NAT differs depending on which target estimand is used. <b>Conclusion:</b> Visualization tools may help to clarify the target population in comparative effectiveness studies and resolve ambiguity about the interpretation of estimated treatment effects.