bluuebunny/crossref_metadata_2025 huggingface dataset:
Development and validation of RSClin N+ tool for hormone receptor-positive (HR+), HER2-negative (HER2-), node-positive breast cancer.
Authors: Pusztai Lajos , Hoag Jess R , Albain Kathy S. , Barlow William E. , Stemmer Salomon M. , Meisner Allison , Hortobagyi Gabriel N. , Shak Steven , Hayes Daniel F. , Rae James M. , Baehner Frederick , Sharma Priyanka , Kalinsky Kevin
Published: May 2024

508

Background: The RSClin tool was developed to provide estimates of recurrence risk and absolute chemotherapy benefit for patients with HR+/HER2- node-negative breast cancer using the 21-gene recurrence score (RS) and clinicopathologic factors. For patients with node-positive disease, we developed a new tool (RSClin N+) to increase the prognostic and predictive utility of risk estimates by combining RS with clinicopathologic factors and menopausal status. Methods: We used Cox regression to estimate 5-year risk of invasive disease or death (iDFS) and likelihood ratio (LR) tests to compare fit of RSClin N+ with RS alone and clinicopathologic factors (tumor grade, tumor size, positive lymph nodes [N1/N2], age) alone in 5283 node-positive patients treated with chemoendocrine therapy (CET) vs endocrine therapy alone (ET) in the S8814 (n=367: N1=227, N2=140, all postmenopausal) and RxPONDER (n/N1=4916) trials. Data from both studies were pooled and stratified by study for postmenopausal models; premenopausal models were fit only on RxPONDER data. Absolute CET benefit across combination of covariate values was estimated as the difference between ET and CET risk estimates. Validation of RSClin N+ was performed in 592 Nmic/N1 patients in the Clalit registry real-world dataset. Results: For pre- and postmenopausal patients, RSClin N+ provided significantly more prognostic information for iDFS than RS or clinicopathologic factors alone (LR Chi-square p<0.05). In postmenopausal patients, RS and clinicopathologic factors were independently prognostic, but only RS showed interaction with CET benefit (p=0.016). Absolute CET benefit for iDFS ranged from <0.1% to 21.5% as the RS increased from 0 to 50. Table shows examples of risk stratification and predicted benefit by RS within clinical low and high risk patients. In premenopausal patients, both RS and clinicopathologic factors remained prognostic but no interaction was observed between RS and CET.In external validation, RSClin N+ risk estimates were concordant with (Lin’s concordance=0.92) and prognostic for observed risk (HR 1.75; 95% CI 1.38 to 2.20). Conclusions: The RSClin N+ model provides improved estimates of prognostic risk and absolute CET benefit than clinical or genomic data alone in node-positive, HR+/HER2- breast cancer and could be used in patient counseling. [Table: see text]
Short-term risk of recurrence in patients (pts) with HR+/HER2− early breast cancer (EBC) treated with endocrine therapy (ET) in randomized clinical trials (RCTs): A meta-analysis.
Authors: Curigliano Giuseppe , Ciruelos Eva , Kalinsky Kevin , Proudman David , Nellesen Dave , Lopez Priscilla , Kaufhold Samantha , Shane Olivia , Kwok Adrienne , Ganapathy Vaidyanathan , Amefule Adaeze Q. , Lteif Agnes , Fasching Peter A. , Hamilton Erika P.
Published: May 2024

541

Background: ET ± chemotherapy (CT) has been standard of care for HR+/HER2− EBC for ≈20 yrs, yet pts continue to experience disease recurrences up to decades after completing adjuvant (adj) treatment (tx). There is little information on early recurrences (≤5 yrs) in the more recent tx landscape, which includes optimized local tx and improved systemic tx. This meta-analysis of ET arms in RCTs in pts with HR+/HER2− EBC seeks to fill this gap by evaluating 3- and 5-yr risk of recurrence (RoR). Methods: A systematic literature review identified RCTs that met study criteria: phase 3 trials that included pts with HR+/HER2− EBC who received 5 yrs of adj ET (aromatase inhibitors ± ovarian suppression or tamoxifen) ± CT with invasive disease-free survival (iDFS) or disease-free survival (DFS) reported at 3 and/or 5 yrs post tx randomization. Neoadj or extended ET trials were excluded. Survival curves were digitized for iDFS estimates. Meta-analysis of proportions, using a random-effects model with double arcsine transformation, was used to evaluate pooled 3-yr RoR (100 − iDFS/DFS rate) for all pts, by lymph node (LN) status (N0: 0, N1: 1-3, N+ any positive LN), and 5-yr RoR where available. The 3-yr RoR across ET arms in a subset of only adj cyclin-dependent kinase 4/6 inhibitor (CDK4/6i) trials was evaluated given the recency of these RCTs. Results: RoR estimates were obtained from 14 trials (across 23 distinct ET-only arms), including 4 adj CDK4/6i trials that met study criteria; studies included pts with stage I-III disease ± nodal involvement. Pooled 3- and 5-yr RoR for the overall HR+/HER2− EBC pt population regardless of LN/stage were 7% and 12%, respectively. In trials with nodal status subgroups, pooled 3-yr RoR was 5% for N0, 6% for N1, and 13% for N+ pts. In a sensitivity analysis excluding cohorts with low to medium risk scores based on genomic testing, pooled 3-yr RoR estimates for N0 and N1 subgroups were 7% and 10%, respectively. Meta-analysis across ET arms of CDK4/6i trials revealed 3-yr RoR of 15% (all stage I-III) and 10% (N0). Conclusions: Despite the potential for late recurrence of HR+/HER2− EBC, short-term RoR is considerable and accumulates over time for these pts treated with ET ± CT in the adj setting. These findings highlight the unmet need for tolerable tx escalation among at-risk pts, including node-positive and select N0 pts with high-risk features.
Clinical outcomes of patients with HER2-positive microinvasive breast cancer.
Authors: Shin Yeokyeong , Lee Soo-Young , Jeong Hyehyun , Lee Hee Jin , Gong Gyungyub , Kim Hee Jeong , Lee Jong Won , Son Byung-Ho , Ko BeomSeok , Kim Jisun , Ahn Jin-Hee , Jung Kyung Hae , Kim Sung-Bae , Lee Sae Byul , Jeong Jae Ho
Published: May 2024

544

Background: Although previous studies have reported that adjuvant trastuzumab with paclitaxel resulted in excellent survival outcomes in small, node-negative HER2-positive breast cancer, the necessity of adjuvant chemotherapy in HER2-positive microinvasive breast cancer (MIBC) remains controversial. Methods: Between January 2000 and January 2020, women with curatively resected pT1mi N0 and/or N1mi in Asan Medical Center were retrospectively identified and their survival outcomes including invasive disease-free survival (IDFS, excluding second primary cancer), distant recurrence-free survival (DRFS), and overall survival (OS) and the effect of adjuvant chemotherapy were analyzed. Results: A total of 833 patients were included. The median age was 51 years, and 51% (n = 426) were premenopausal. Pathologic nodal stage was pN0 in 96% (n = 799) and pN1mi in 0.7% (n = 6), and estrogen receptor (ER) was positive in 30% (n = 247). Adjuvant chemotherapy was administered to 18% (n = 147) of patients, of which 95% were fluorouracil-based. Six patients (0.7%) received adjuvant trastuzumab. With the median follow-up of 118.7 months, the 8-year IDFS and DRFS rates were 90.6% (95% CI, 88.4-92.7), and 97.3% (95% CI, 96.1-98.4), respectively, and the 8-year OS were 98.6% (95% CI, 97.8-99.5). IDFS did not differ by adjuvant chemotherapy, as the 8-year IDFS rates for patients who did and did not receive adjuvant chemotherapy were 91.1% (95% CI, 86.6-95.8) and 90.3% (95% CI, 87.9-92.8), respectively ( p = 0.930). The lack of differences in IDFS by chemotherapy was consistent across subgroups including pre-/postmenopausal patients, grade 1-2/3 tumors, and ER-negative diseases. Conclusions: In HER2-positive MIBC, a clinically meaningful proportion of patients experience IDFS events with long-term follow-up. The role of modern adjuvant chemotherapy regimens, as well as the role of adjuvant trastuzumab, should be further explored in this early-stage patient population.
Deep learning-based quantitative assessment of tumor-infiltrating lymphocytes from hematoxylin and eosin-stained slides in triple-negative breast cancer: A prognostic study.
Authors: Kobayashi Takuma , Hatanaka Kanako C , Tomioka Nobumoto , Konishi Teppei , Grynkiewicz Mateusz , Komura Daisuke , Ishikawa Shumpei , Watanabe Kenichi , Takahashi Masato , Hatanaka Yutaka
Published: May 2024

553

Background: Tumor-infiltrating lymphocytes (TILs) are pivotal in predicting responses to preoperative chemotherapy in triple-negative breast cancer. Yet, their clinical adoption as a diagnostic marker is limited by the challenge of achieving high accuracy with objective measures. This study introduces a novel AI-based method to quantitatively assess stromal TILs within the tumor bed using hematoxylin and eosin (H&E)-stained slides, examining their correlation with disease-free survival (DFS) and overall survival (OS). Methods: In this study, 68 cases of breast cancer with axillary lymph node metastasis at the time of resection were selected from a total of 3,902 resections conducted between 2002 and 2016. We then developed an AI-based model to detect the epithelium and lymphocytes (CD3/CD20) from H&E-stained slides. This model was trained using annotated datasets, which included 26,509 images of the epithelium and 12,273 images of lymphocytes. The tumor bed areas were precisely defined by pathologists. Subsequently, the AI model identified epithelial and lymphocyte regions within these predefined areas. The TILs score was then calculated as the ratio of the lymphocyte area to the total stromal area within the tumor bed, excluding the epithelial areas identified by the AI model. Finally, we assessed the prognostic significance of the TILs score for DFS and OS through ROC analysis and log-rank tests. Results: ROC analysis identified an optimal TILs score threshold of 0.0042 for both DFS and OS, with an AUC of 0.743 (95% CI, 0.622-0.864) for DFS and 0.686 (95% CI, 0.559-0.812) for OS. This threshold significantly stratified patients into groups with distinct DFS and OS outcomes (P=0.003 and P=0.008, respectively). Conclusions: AI quantification of TILs offers a promising prognostic tool in triple-negative breast cancer, enhancing the objectivity and clinical utility of pathological analyses. Accurate TILs measurement could revolutionize prognostication and treatment planning.
Impact of race/ethnicity on the MammaPrint genomic assay risk and prognosis in early breast cancer (EBC): A National Cancer Database (NCDB) analysis.
Authors: Patel Rima , Sheng Tianxiang , Diniz Marcio A. , Sparano Joseph A. , Tiersten Amy
Published: May 2024

564

Background: The 21-gene Oncotype DX Recurrence Score (RS) and 70-gene MammaPrint (MP) assays provide prognostic information for distant recurrence and are used to guide chemotherapy use in hormone receptor (HR)-positive, HER2-negative EBC. Previous reports have demonstrated that Black women with low genomic risk (RS 0-25) have a higher recurrence risk than White women in the TAILORx (PMID: 32986828) and RxPONDER trials (SABCS 2023, abstract GS1-01), and that Black race was associated with worse overall survival (OS) in multivariate models including RS in the NCDB registry (PMID: 33649322).The goal of this study was to evaluate the impact of race/ethnicity on MP risk distribution and prognostic information provided by the MP assay in the NCDB cohort. Methods: Women with HR-positive EBC with tumor size up to 5 centimeters (T1-T2), 0-3 involved lymph nodes (LNs, N0-N1), diagnosed between 2009-2018, and who had available information on MP testing and OS in the NCDB 2019 dataset were identified. Patients (pt) were stratified by MP result of high or low risk. T-tests and chi-square tests were used to compare pt characteristics, while log-rank tests assessed differences in OS between the high- and low-risk MP groups, as well as across different racial/ethnic categories. Results: 6096 eligible women were included of whom 41.0% (N=2502) were MP high-risk and 59.0% (N=3594) MP low-risk. Overall, 82.7% of pts were Non-Hispanic White (NHW), 8.7% Non-Hispanic Black (NHB), 4.7% Hispanic (H), and the remainder other/unknown (O). A higher proportion of H and NHB pts had high MP results, p<0.0001. The MP high-risk group had a greater proportion of pts </= 50 years (p=0.0013) and larger tumors (p<0.0001) and higher grade (p<0.0001), but not LN positive (p=0.7649). The 5-year OS rates (and 95% Confidence Intervals) for the MP high and low-risk groups were 92.6% (91.6% - 93.7%) and 96.6% (95.9% - 97.2%), respectively, p<0.0001. There were no differences in OS based on race/ethnicity in the low-risk group with 5-year OS rates of 98.4% (96.1%-100%), 95.9% (93.3% - 98.6%), 96.4% (95.7% - 97.1%), and 99.2% (97.7% - 100%) for H, NHB, NHW and O, respectively, p=0.34. Similarly, in MP high-risk, race/ethnicity did not impact prognosis with OS rates of 92.6% (88.2% - 97.1%), 90.8% (87.2% - 94.5%), 92.8% (91.7% - 94.1%), and 95.8% (91.2% - 100%) for H, NHB, NHW and O groups, respectively, p=0.45. There was no significant interaction between race and MP for OS when accounting for age, tumor grade, tumor size, and LN status, p=0.75. Conclusions: NHB and H women were more likely to have high-risk MP results compared with NHW women in this NCDB cohort, although race/ethnicity did not impact prognosis for 5-year OS in either MP risk group. Limitations of this analysis include absence of information on recurrence and short follow up, as about one-half of recurrences in HR-positive EBC occur after 5 years.
Predictive markers of complete pathological response to neoadjuvant chemo-immunotherapy in triple negative breast cancer.
Authors: Cankar Kaja , Auprih Maša , Ovcaricek Tanja , Kovac Anja , Sarvari Natasa Snoj , Dobovisek Luka , Borstnar Simona
Published: May 2024

e12650

Background: Results from the Keynote 522 clinical trial, which played a pivotal role in evaluating the efficacy of neoadjuvant pembrolizumab in combination with chemotherapy (NAICT), showed a significant improvement in pathological complete response (pCR) rates compared with chemotherapy alone. To date, no significant markers have been identified to predict pathological complete response to NAICT. The primary objective was to identify markers, both molecular and clinical, predictive of pCR to NAICT in a real-world clinical setting. Methods: The retrospective analysis included 38 consecutively treated pts with early stage TNBC who received NAICT including pembrolizumab at the Institute of Oncology, Ljubljana (OIL) between 4 January 2022 and 17 October 2023. Data collected from electronic medical records included tumour size, nodal status, UICC stage, BRCA status, systemic immune-inflammation index (SII) before NAICT and before surgery, and frequency and grade of immune-related adverse events (iAEs) (according to the Common Terminology Criteria for Adverse Events (CTCAE) version 5). In pts who completed surgical treatment, response to treatment was assessed by pathological examination of post-treatment surgical specimens. Descriptive statistical methods were used to summarise and describe the main characteristics. Pearson chi-squared test was used to analyse categorical variables and t-test to evaluate associations between continuous variables. Results: Of the 38 pts, 28 completed surgical treatment and were further analysed. Pathohistological examination of post-treatment surgical specimens revealed pCR in 11 pts (39.3%), with residual disease in 17 pts (60.7%). Of the 17 pts without pCR, 11 pts had RCB score 2 (64.7%) and 5 pts had score 3 (29.4%). The distribution of size, nodal status, UICC stage at diagnosis, BRCA status, frequency of iAEs in correlation with pCR is shown in the Table. A borderline correlation was found between pCR and SII at the start of pembrolizumab treatment (p=0.05). Age, tumour size, nodal status, UICC stage, BRCA status, AEs, SII before surgery were not found to be predictive of pCR. Conclusions: SII at the start of pembrolizumab was found to be a borderline significant marker predictive of pCR. Other characteristics evaluated did not correlate with pCR. [Table: see text]
EGFR mutation testing trends for patients with metastatic, non-squamous non-small cell lung cancer (non-SQ NSCLC) in Queensland, Australia from 2014-2021.
Authors: Yang Zane , Niranjan Navin , Guan Tracey , Mason Robert , Chan Bryan Anthony , Sanmugarajah Jasotha
Published: May 2024

e13505

Background: Lung cancer is the leading cause of cancer-related mortality worldwide. Epidermal growth factor receptor (EGFR) is the most common actionable mutation in non-small cell lung cancer (NSCLC) with routine testing recommended globally. In late 2013, screening for EGFR mutations was publicly funded in Australia for metastatic non-SQ-NSCLC. However, timely EGFR results are not universally available, often limited by tissue quantity/quality or prolonged turnaround times. This in turn affects access to treatment and thus survival. Methods: We aimed to examine the rates of EGFR testing over time and explore factors impacting results. Cases were identified from the Queensland Oncology Repository, a clinical database consolidating diagnostic, treatment and outcome data for all Queenslanders with cancer through the Queensland Cancer Registry. Cases were included if they had metastatic non-SQ-NSCLC, EGFR testing available via Pathology Queensland, and no other metastatic solid organ cancer within 1 year. Primary outcomes were EGFR mutation testing rates and time from first biopsy to EGFR mutation result, stratified by year of diagnosis and rurality. Results: A total of 3369 cases were included, of which 2871 had EGFR testing. The EGFR mutant (mt) rate was 12.6%, while 16.1% of cases had no EGFR results. Of cases without a conclusive EGFR result, reasons included: 179 transitioned to best supportive care before testing, 208 with insufficient tissue for a conclusive result, and 155 without testing for unclear reasons. The average time from biopsy to EGFR result improved from 29.9 days in 2014 to 21.5 days in 2021, with no significant difference in time to result between major cities, regional or remote areas. Cases with no EGFR results were more prevalent in rural areas. The proportion of patients living in outer regional/remote areas with no EGFR result was 21.1% compared to 15.5% in those living in major cities/inner regional sites. This was a relative increase of 36.2% (95% CI: 10.1% - 68.6%), a significant result (χ2 = 7.7483, p=0.005). Cases with no EGFR results in outer regional and remote sites declined from 30.1% in 2014-2015 to 15.3% in 2020-2021. Conclusions: EGFR mutation testing and result time has improved since 2014. Though time to result was not affected by rurality, significantly more rural patients lacked conclusive EGFR data, highlighting a gap in access to care. The cumulative EGFR no result rate of 16% and result time of 24 days indicates health systems need to more rapidly adapt to new treatment paradigms, particularly in the era of targeted therapies. [Table: see text]
Barricades to aiding cascading: Patient-reported barriers to uptake in the context of clinician-facilitated cascade testing for hereditary cancer syndromes.
Authors: Chandler Isabelle , Grant Benjamin , Epstein Emily , Brewer Jesse T , Larosa Taylor , Kalyan Alissa , Schulman Sarah , Llenas Ashley , Cantillo Evelyn , Holcomb Kevin , Chapman-Davis Eloise , Sharaf Ravi N. , Frey Melissa Kristen
Published: May 2024

e13533

Background: Cascade testing extends genetic testing to relatives of individuals with known pathogenic variants. Cascade testing can prompt lifesaving cancer surveillance, however, up to two thirds of at-risk relatives do not complete recommended genetic testing. Previous studies suggest that a clinician-mediated approach of direct relative contact can increase testing rates. As part of an ongoing clinician-facilitated cascade testing intervention, we investigated the barriers to completion of cascade testing. Methods: All patients with a known cancer-associated germline mutation presenting to a gynecologic oncology clinic from 11/2023-2/2024 were offered clinician-facilitated cascade testing, an intervention whereby the genetics team was granted permission to contact designated at-risk relatives by telephone, review the familial mutation, and assist with accessing genetic testing. Patients that declined were asked about their decision and responses were analyzed using the socio-ecological model. Results: Ninety patients were offered clinician-facilitated cascade genetic testing and 50 (55%) declined. Of the patients that declined: median age was 45 (range 23-84), 41 (82%) self-identified as non-Hispanic, 38 (76%) as White, 23 (46%) were of Ashkenazi Jewish heritage, 23 (46%) had a personal history of cancer. There were no significant differences in any of the above variables when comparing those that declined and accepted the intervention. Twenty-nine (58%) patients declined because all family members were already tested. The most common barriers were “limited access to care” (5, 10%) at the healthcare community level, and “perceived readiness of relatives” (5, 10%) at the interpersonal relationship level. While these were the most common, most barriers were at the individual level including “perceived lack of responsibility” (3, 6%), “limited knowledge” (2, 4%), and “emotional burden” (2, 4%) (Table). Stated barriers were not associated with any demographical group. Conclusions: Although clinician-facilitated cascade testing has been shown to increase rates of relative testing uptake, several barriers persist at all levels of the socio-ecological model. While facilitated interventions should be individualized, our findings suggest that future interventions should focus efforts at all socio-ecological levels. Clinical trial information: NCT04613440 . [Table: see text]
Effect of a comprehensive cancer care pathway and a navigation cancer program on breast cancer care in a middle-income country.
Authors: Escobar Marilen , Bravo Maria A , Cervera Sergio , Osorio Ana M , Caicedo Jose Joaquin , Franco Sandra Ximena , Mantilla William Armando
Published: May 2024

e13536

Background: Breast cancer (BC) is the most common cancer in women globally and in Colombia, with around 16.000 new cases estimated in 2022. Mortality associated with BC has decreased for 2 main reasons: screening that leads to early diagnosis and improved treatment of BC. However, BC related mortality remains stable in Colombia, with a 5-year overall survival of 74%, lower than other countries on the continent. This difference could be explained, among other things, by delays, barriers, and fragmentation of cancer care. Luis Carlos Sarmiento Angulo Cancer Treatment and Research Center (CTIC) is an institution designed for comprehensive cancer care, with specialized patient care through cancer clinics dedicated to a single disease (breast cancer, lung cancer, etc.). Every cancer clinic is associated with a cancer navigation program and has clinical care pathways with metrics that seek to monitor and reduce the time to diagnosis and treatment, among others. This study aims to describe the results of the comprehensive breast cancer care program and cancer navigation support in time to breast cancer diagnosis and treatment access. Methods: This descriptive study was carried out by retrospective reviewing of the navigation database from the breast cancer unit of the CTIC, sociodemographic information, clinical characteristics, and time to diagnosis (from first appointment to pathology report) and treatment were collected and described. A comparison between patients with comprehensive and fragmented care was done. Results: Since August 2022, 600 patients with confirmed breast cancer have been evaluated by the BC clinic, 401 (66.8%) patients were admitted through the cancer navigation program, 436 (72.6%) cases presented with a previously established diagnosis of breast cancer, and 164 (27.3%) were the novo cases. Of the novo cases, 37 (23.3%) cases received comprehensive care from diagnosis, with a time to diagnosis of 14 days, and time to treatment of 30.5 days, patients who did not receive comprehensive care presented a time to treatment of 68.1 days. Conclusions: A comprehensive cancer care and support from a navigation program significantly reduce the time to treatment in breast cancer patients. A comprehensive care model in Colombia has the opportunity to generate a better opportunity for access to diagnosis (14 days) and treatment (30.5 days) compared to the time to treatment data reported in the high-cost account (CAC) (27 and 52 days respectively). [Table: see text]
Impact of staffing an inpatient oncology consult service with dedicated hospital-based oncologists.
Authors: Brondfield Sam , Kwon Daniel H , Ko Andrew H. , Wachter Robert M. , Small Eric J.
Published: May 2024

e13538

Background: No standard care model for hospitalized patients with cancer currently exists. The majority of oncology care is provided in the outpatient setting. Consequently, for many oncologists, inpatient care is a secondary responsibility. To address this issue, several U.S. institutions have changed their inpatient oncology models to include dedicated inpatient oncology-trained attendings (hospital-based oncologists). In this study, we investigate outcomes following such a change on an inpatient solid oncology consult service. Methods: This is a single-institution retrospective study of the University of California, San Francisco (UCSF)’s inpatient solid oncology consult service, which switched from a rotating outpatient oncologist attending model to a dedicated inpatient oncologist model in 2018. Since data prior to the switch were not available, we compared all inpatients who received an oncology consult (n=3974) with a comparison group (CG) of all inpatients with a solid tumor diagnosis who did not receive an oncology consult (n=3200) between fiscal years 2018 and 2023. We analyzed trends in case mix index (case complexity), in-hospital mortality index (observed/expected), 30-day unplanned readmission rate, length of stay index, and direct cost index using the Pearson correlation coefficient. In 2022, we conducted an anonymous retrospective pre/post-switch survey of hospitalists who had worked on the hospital medicine service both before and after the switch and compared mean satisfaction with oncology consultation (5-point scale) using Student’s t test. Results: Following the switch, the number of weeks per year covered by dedicated inpatient oncologists increased from seven (2018) to 39 (2023) out of 52. From 2018 to 2023, we found a significant increase in annual consults (495 to 919, r=0.95, p<0.01) and case mix index (2.30 to 3.30, r=0.90, p=0.01; CG 1.60 to 1.70, r=0.60, p=0.20), and a significant decrease in mortality index (1.59 to 0.70, r=-0.98, p<0.01; CG 0.90 to 0.48, r=-0.66, p=0.15). There were non-significant decreases in 30-day unplanned readmission rate (35.8% to 30.5%, r=-0.77, p=0.07), length of stay index (1.45 to 1.32, r=-0.75, p=0.08), and direct cost index (2.2 to 1.8, r=-0.61, p=0.20), similar to the CG. Mean (standard deviation) satisfaction increased from 3.27 (1.22) pre-switch to 4.53 (0.92) post-switch ( p=0.02, response rate 15/51, 29%). Conclusions: Switching to a dedicated inpatient oncologist model on a consult service was associated with decreased in-hospital mortality and increased satisfaction with oncology consultation despite growing case volume and complexity, while readmission rate, length of stay, and cost remained unchanged. This study adds to growing literature supporting dedicated inpatient oncologist attending models of care and is in line with recent literature from other specialties supporting similar inpatient care models.
Application of multidisciplinary team model based on full-course management in health promotion of patients with breast cancer.
Authors: Xie Xiuyuan , Liu Fenghe , Fei Yujie , Xu Haiping
Published: May 2024

e13546

Background: To explore the application effectiveness of the multidisciplinary team model based on full-course management, in advancing the health promotion of breast cancer patients. Methods: This research involved a cohort of 84 breast cancer patients, recruited from the First Affiliated Hospital of Nanjing Medical University, spanning December 2022 and June 2023. These participants were divided into a control group and an intervention group using a convenience sampling method. The control group accepted routine nursing care, while the intervention group was treated with the multidisciplinary team approaches based on full-course management. These approaches included informal pre-admission interventions and multi-dimensional improvements to peri-operative patient comfort, integrated regimens combining Chinese and Western medicine to alleviate chemotherapy complications, diversified and extended nursing care focused on improving patients' quality of life, and facilitating physical and psychological rehabilitation. The two groups of patients were evaluated in satisfaction, comfort, quality of life, psychological state and other aspects. The results were evaluated by self-made satisfaction scale, breast cancer complications during chemotherapy questionnaire, Kolcaba Comfort Scale, Quality of Life Scale (QLQ-C30), self-rating Anxiety Scale (SAS) and self-rating Depression Scale (SDS). Patient outcomes were assessed in terms of satisfaction, comfort, quality of life, and psychological state. The results were evaluated by the self-made satisfaction scale, the breast cancer chemotherapy complications questionnaire, the Kolcaba Comfort Scale, the Quality of Life Scale (QLQ-C30), the Self-Rating Anxiety Scale (SAS), and the Self-Rating Depression Scale (SDS). Results: The intervention group showed statistically significant improvements in patient satisfaction, comfort and quality of life scores compared to the control group (P<0.05). Additionally, they exhibited a lower incidence of chemotherapy complications, severe anxiety and depression during the extended care period (P<0.05). Conclusions: The multi-disciplinary team model based on the full-course management demonstrated significant clinical benefits in the application of the full-course management of breast cancer patients. It effectively reduced chemotherapy-related complications, improved peri-operative comfort, decreased the incidence of severe anxiety and depression during the period of extended care, improved the physical and mental well-being of patients, leading to greater satisfaction and an enhanced quality of life.
Practice patterns in prostate cancer therapy among healthcare professionals: Comparison with expert recommendations from an online tool.
Authors: Becker Marie N. , Rosenthal Kristen M. , Dorff Tanya B. , McKay Rana R. , Schweizer Michael Thomas , VanderWeele David James , Morgans Alicia K.
Published: May 2024

e13549

Background: The treatment landscape of prostate cancer (PC) is complex, and recent approvals of new agents and regimens further challenge healthcare professionals (HCPs) to select optimal therapy for patients with PC. We sought to identify practice patterns among community HCPs for PC by comparing HCP and key opinion leader (KOL) treatment recommendations using an online decision support tool. Methods: The online decision support tool was developed with 5 KOLs who provided therapy recommendations for 96 patient case scenarios encompassing mHSPC, nmCRPC, and mCRPC based on factors including disease volume and symptoms, comorbidities, previous therapy, and biomarker status. HCPs entered specific patient and disease factors into the tool along with their intended treatment plan and were shown the 5 individual KOL recommendations for the patient case. An analysis of HCP selected therapy compared with KOL recommendations was performed. Results: Between September 2023 and January 2024, 286 patient cases were entered by 100 HCPs. KOL consensus defined as ≥3 in agreement. HCP therapy selection discordance with KOL recommendations was 69% for nmCRPC (n = 64 cases), 42% for mHSPC (n = 125 cases), and 46% for mCRPC (n = 97 cases). The level of discordance was 63% (n = 43 cases) for nmCRPC with a PSADT <10 months and 81% (n = 21 cases) with a PSADT ≥10 months (Table). Regardless of PSADT, selection of therapy for nmCRPC without listed comorbidities was highly discordant 82% (n = 34 cases). In mHSPC, the highest level of discordance was seen in cases with de novo, symptomatic, high-volume disease, and diabetes at 73% (n = 11). Discordance was 54% for de novo mHSPC with symptomatic disease (n = 52 cases). HCP selection of 1L, 2L, or 3L therapy for mCRPC was 44% to 47% discordant with KOL recommendations regardless of prior therapy. Selection of therapy for mCRPC with HRR mutations including BRCA (n = 29) was 48% discordant. Among HCPs who initially selected treatment options that diverged from expert recommendations or were uncertain about therapy selection, 48% (n/N = 75/157) intend to change their therapy selection to align with the experts. Detailed data analysis with KOL recommendations will be presented. Conclusions: This analysis suggests differences in clinical practice between HCPs and KOLs for multiple case scenarios in PC and suggests that use of the decision tool may lead to increased alignment of treatment choices with KOLs. [Table: see text]
Objective acuity measures for infusion therapy staffing: A predictive model approach—Phase I.
Authors: Egan Alden , Gehrke Daniela , He Bo , Garey Jody S. , Ye Ping , Shapert Debra , Sassano Jennifer , Garnett Ashley , Velador Sonia , Payne-De Bock Judi
Published: May 2024

e13553

Background: Acuity is a measure of the complexity of patient care and an estimate of nursing workload. The use of acuity tools is shown to improve care standards, nurse satisfaction and productivity. Existing acuity tools have barriers to adoption, including increased nursing workload, estimate variations among different nurses and clinical care settings, and poor understanding of validity of acuity measures. We aim to build a predictive model for prospectively determining acuity levels and staffing requirements in infusion therapy to address these gaps. This project will be implemented with a phased approach. Here we describe Phase I, to establish a standard measure and documentation process for acuity, then collect and analyze a large data set to quantify the relationship of acuity scores to selected patient characteristics. Methods: A US Oncology Network nursing committee developed evidence-based guidelines for acuity measurement and documentation in August 2023. Nine sites from four independent, community oncology practices were selected to perform acuity rating and documentation using the developed guidelines. Multiple training sessions on the guidelines were conducted with nurses from selected sites. Nurses documented acuity scores (level 1~6) and start time for patients’ infusion visits in the EHR 8/30/2023 – 11/30/2023. Acuity documentation rates were calculated and provided to each site weekly to gain feedback and engagement. Acuity scores were extracted from the electronic health record using natural language processing. Structured data on potential predictors including patient demographics, performance status, lab, and treatment-related information were also collected. Results: A total of 14,610 infusion room visits (5,139 distinct patients) with documented acuity scores were reported. The acuity documentation rate from each site was consistent by week and ranged 60 – 96%. Table reports prevalence of select features by acuity score. Conclusions: An operational workflow was successfully implemented to collect and analyze acuity scores and relevant features. Features of interest include chemotherapy Cycle 1 Day 1, five or more drugs and highly emetogenic treatment. In Phase II, the collected acuity scores and clinical features will be used to build a predictive model to objectively estimate acuity. Phase III will focus on the deployment of the predictive model to oncology practices. [Table: see text]
Opportunity cost of oncology subspecialist opinion.
Authors: Barzi Afsaneh , Liang Crystal , Wright Carol , Nathwani Nitya , Wong Debra A. , Sachs Todd M.
Published: May 2024

e13578

Background: The adoption of precision oncology has resulted in a drastic rise in the cost of cancer care in the United States. Payers, providers, and professional organizations are implementing strategies to curb this rising cost. These efforts are mainly focused on the providers patterns of care, such as prescribing behavior and risk assessment for needs such as ER visits and hospitalizations. Most efforts are cross-cutting and intended to work across different tumor types. Yet, with the precision nature of cancer care these cross-cutting efforts have not succeeded. AccessHope (AH) provides an independent subspecialist review of the management cancer as a covered benefit through the employer (Accountable Precision Oncology: APO). The aim of this service is optimizing care delivery to the current and evolving paradigms for each cancer type and sub-type. Here we describe overutilization of treatments and assessments of APO. Methods: AH database was accessed for de-identified cases (with contractual de-identification rights) for this analysis. Cases were completed 1/1/2022 – 12/31/2023. Descriptive statistics was used to describe the observed patterns identified. Results: Among 3644 APOs, 428 (11.7%) had evidence of overutilization. Gastrointestinal, hematological, and thoracic cancers represented 75% of the over utilization cases (Table). Overutilization was categorized by systemic therapy, radiation therapy, invasive procedures, imaging, and testing. Systemic therapy was the most common category (67.8%) and included non-indication use and extended duration of use. This was followed by imaging (22.2%). Systemic agents overutilized varied by cancer site. Bevacizumab and oxaliplatin were commonly overutilized in gastrointestinal cancers; rituximab, imatinib, and dasatinib in hematological malignancies; and check point inhibitors (pembrolizumab, atezolizumab, and durvalumab) in thoracic malignancies. In the imaging category, PET scan overutilization was observed across different tumor types (14.7% of the total volume). We also observed overutilization of molecular testing with ctDNA (Signatera) being at the top of the frequently overutilized tests in cases with no data to support a role for it. Conclusions: This patient centered approach identified areas of overutilization in evaluation and treatment of patients through the expert review process. The reviewer’s depth of knowledge about reported data and limitation of treatments and evaluations is the key to this process. Further analyses of patterns of care and categorization of the overutilization patterns is underway. [Table: see text]
Comparing literature-based cell-free miRNA panels to whole genome miRNA screening for cancer detection.
Authors: Hsieh Tsung-Ting , Lee Ko-Han , Hsieh Jason Chia-Hsun , Chang Yu-Chuan
Published: May 2024

e13587

Background: Cell-free miRNAs (cf-miRNAs) found in bodily fluids like plasma or serum are adept at detecting cancer. When constructing a cancer detection model with a reasonably sized training sample, it seems logical that employing whole genome screening could enhance prediction performance and unveil novel miRNAs. However, screening all cf-miRNAs could be costly and its potential improvement compared to a curated panel remains uncertain. To evaluate the trade-off between accuracy and cost-effectiveness, our study aims to compare the performance of two approaches: a literature-based cf-miRNA panel and a whole genome screening. We utilized real-world datasets to assess the effectiveness of these two methods in cancer detection. Methods: To curate a cf-miRNA panel, we conducted a comprehensive review of published miRNA-related databases, identifying 27 databases, including dbDEMC 2.0, miRCancer, miRStress, HMDD, and others. Of these, 11 databases were both available and downloadable, yielding 196,839 records (database entries). Focusing on cf-miRNAs, we filtered the records to only include those clearly identified as originating from plasma or serum, resulting in 13,595 cf-miRNA records. Next, to ensure robustness, we employed two strategies: requiring multiple records for a given miRNA and confirming its mention in multiple databases to finalize the cf-miRNA panel. For comparison of prediction performance, we obtained a large-scale dataset from the Gene Expression Omnibus, specifically the GPL21263 platform, for modeling experiments. This dataset comprised 8,174 subjects with 2,565 miRNA targets across seven cancer types derived from various cf-miRNA-based cancer studies. We then trained machine learning models on both the curated panel and the full miRNAs from this dataset to facilitate a comparative analysis. Results: Out of the 13,595 cf-miRNA records, 499 miRNAs had over 4 records, and 612 miRNAs were mentioned in multiple databases. There was an overlap of 339 miRNAs, forming our final cf-miRNA panel. The model accuracy using this panel to distinguish between seven cancer types was 67.62%. In contrast, directly employing machine-learning to model whole genome screening resulted in an accuracy of 93.00%, demonstrating a significant improvement compared to the panel-based results. Conclusions: Our study curated a cost-effective cf-miRNA panel of 395 miRNAs, demonstrating the capability to distinguish multiple cancers. However, while the curated panel exhibited reasonable efficacy in cancer detection, the whole genome screening model displayed superior discriminatory power. Hence, for optimizing cancer detection methods, especially in large-scale datasets, employing whole genome screening appears to be a more promising strategy.
A transfer learning-based graph neural network model using mIF images to predict neoadjuvant immunochemotherapy response in patients with gastrointestinal cancer.
Authors: Li Shenglong , Wang Yanan , Su Lan , Wang Jun , Zhou Jiaolin
Published: May 2024

e13592

Background: Neoadjuvant immunochemotherapy has great potential to revolutionize the treatment of gastrointestinal cancer. However, effective biomarkers to classify responders from non-responders are still lacking. We aimed to build a response prediction model using multiplex immunofluorescence (mIF) images from patients with gastrointestinal cancer. Methods: We proposed a graph neural network-based (GNN) approach based on the pre-treatment mIF samples collected from 77 patients, including 30 gastric cancer (GC) patients, 34 colorectal cancer (CRC) patients, and 13 esophageal cancer (ESCA) patients. All the tissue samples were stained by two panels of mIF agents, namely Panel-A (CD3, CD8, PD1, PD-L1) and Panel-B (CD56, CD68, CD163). Cell coordinates, agent densities, and cell morphology features were used to generate cell graphs for model training. Results: Initially, we trained a pan-cancer GNN model for each panel and assessed its performance on the patch- and patient-level using five-fold cross-validation. The Panel-A model achieved higher areas under the receiver operating characteristic curve (AUROC) (patch-level: 0.71 ± 0.036, patient-level: 0.65 ± 0.010) than the Panel-B model (patch-level: 0.59 ±0.017, patient-level: 0.62 ± 0.021) and conventional mIF-based markers (i.e., positive cell ratios/counts of fluorescence agents, AUROC: 0.34 ~ 0.54). Specifically, the performance of CRC was better in the Panel-A model (patch-level: 0.75± 0.053, patient-level: 0.76 ± 0.053) than that in Panel-B (patch-level: 0.52 ± 0.027, patient-level: 0.60 ± 0.028), while the performance of GC was better in Panel-B (patch-level: 0.64 ± 0.030, patient-level: 0.71 ± 0.034) than that in Panel-A (patch-level: 0.53 ± 0.019, patient-level: 0.51 ± 0.018). The AUROCs of both panels of ESCA were less than 0.5, reflecting feature differences associated with treatment response between ESCA and GC/CRC. Furthermore, discrepancies of GC and CRC between Panel-A and -B motivated us to further optimize the performance for individual cancer types using transfer learning (TL). The GC TL-model performance (patch-level: 0.691±0.025, patient-level: 0.751 ± 0.046) was improved compared with the pan-cancer model, but not for the CRC TL-model (patch-level: 0.636 ± 0.066, patient-level: 0.697 ± 0.039). Moreover, the best patient-level specificity and sensitivity under the optimal Youden-Index were 70% and 88% for CRC, and 93% and 62% for GC. Conclusions: The GNN-based approach using mIF images demonstrated promising potential in predicting the immunochemotherapy response of gastrointestinal cancer patients, despite the limited number of samples were curated. The performance variation among cancer types indicated the cancer heterogeneity and the necessity of building single-cancer models when more data becomes available.
Automated survivorship care plan generation using large language models.
Authors: Pradeepkumar Jathurshan , Liebovitz David , Patel Jyoti D. , Sun Jimeng
Published: May 2024

e13595

Background: Cancer survivorship, particularly from post-treatment to end-of-life, faces challenges such as communication gaps and coordination issues, leading to suboptimal care. A survivorship care plan (SCP) is a summarized record of patient cancer history and treatments, along with follow-up care recommendations. Despite extensive survivorship care guidelines from national cancer organizations, their adoption remains limited. Moreover, creating SCPs is time-intensive and burdensome for healthcare providers due to workforce limitations, hindering efficient personalization of care plans. Our study aims to address these issues by employing large language models (LLMs) to generate personalized SCPs. Methods: We introduce SurvGPT, a customized LLM designed to generate personalized SCPs focusing on its two main sections: the treatment summary and the follow-up care plan. Initially, our method extracts information from the structured and unstructured patient records to generate the treatment summary. Subsequently, it retrieves relevant context from a survivorship knowledge base crafted from existing medical literature and guidelines to generate a customized follow-up care plan. To mitigate LLM-related challenges such as hallucinations, our method ensures that the generated follow-up care plan is grounded on existing medical knowledge with a self-checking mechanism. Results: We created synthetic patient data based upon clinical inputs by a medical oncologist and an internist. We conducted a preliminary study using synthetic lung cancer patient EHR data to evaluate our approach. The evaluation focused on several key dimensions to validate the quality of the generated SCPs, including comprehensiveness, personalization, clarity, and actionable recommendations. The results presented in the table suggest promise for this approach yet also need for additional refinements both in degree of details extracted for ongoing care and then in formatting for effective use. The results also illustrate the complexity of generating synthetic cases for this work whose similarity to real patient care improved with iteration yet remained on occasion perceptibly different from current practice as noted by our clinical oncologist team member. Conclusions: In conclusion, our study demonstrates the potential of SurvGPT for generating personalized SCPs. The results of the preliminary results suggest that this approach is technically feasible with further validation required using real patient data. [Table: see text]