Mind the gap: Gendered publication trends in oncology.

BACKGROUND: Investigating scientific publication trends in the field of oncology may highlight opportunities for improved representation, mentorship, collaboration, and advancement for women. METHODS: We conducted a bibliometric analysis of Annals of Surgical Oncology; Cancer; International Journal of Radiation Oncology, Biology, Physics (IJROBP); JAMA Oncology; and Journal of Clinical Oncology in 1990, 2000, 2010, and 2017. Full name and degree credentials per author role (ie, first or senior author), article type, publication year, and citation metrics were collected. First names were used to identify author gender. RESULTS: Across 9189 articles, female representation rose between 1990 and 2017 (first authors: 17.7% in 1990, 36.6% in 2017; senior authors: 11.7% in 1990, 28.5% in 2017). For the 50 most cited articles per year, women comprised a smaller percent of first (26.5%) and senior (19.9%) authors. The average citation count was higher for male first (44.8 per article) and senior (47.1) authors compared to female first (39.7) and senior (44.1) authors. With male senior authors, the first author was more likely male (71.4% male; 25.0% female); with female senior authors, first authors were 50.2% male and 47.6% female. IJROBP had the lowest total female representation among first (25.1%) and senior (16.7%) authors. Women had more MDs with Masters degrees, whereas men held more MDs only and more MDs with PhDs. CONCLUSION: Despite positive trends, substantial gendered differences in oncology publications persist. Fostering more women in oncology research will benefit female representation at many levels of academia and improve productivity, collaboration, and recruitment, especially in technical fields such as radiation and surgical oncology.

Cause-specific mortality in individuals with lymphoplasmacytic lymphoma/Waldenström macroglobulinaemia, 2000-2016.

Data on cause-specific mortality after lymphoplasmacytic lymphoma (LPL) and Waldenström macroglobulinaemia (WM) are lacking. We identified causes of death amongst 7289 adults diagnosed with incident first primary LPL (n = 3108) or WM (n = 4181) during 2000-2016 in 17 USA population-based cancer registries. Based on 3132 deaths, 16-year cumulative mortality was 23·2% for lymphomas, 8·4% for non-lymphoma cancers and 14·7% for non-cancer causes for patients aged <65 years at diagnosis of LPL/WM, versus 33·4%, 11·2% and 48·7%, respectively, for those aged ≥75 years. Compared with the general population, patients with LPL/WM had a 20% higher risk of death due to non-cancer causes (n = 1341 deaths, standardised mortality ratio [SMR] 1·2, 95% confidence interval [CI] 1·1-1·2), most commonly from infectious (n = 188; SMR 1·8, 95% CI 1·6-2·1), respiratory (n = 143; SMR 1·2, 95% CI 1·0-1·4), and digestive (n = 80; SMR 1·8, 95% CI 1·4-2·2) diseases, but no excess mortality from cardiovascular diseases (n = 477, SMR 1·1, 95% CI 1·0-1·1). Risks were highest for non-cancer causes within 1 year of diagnosis (n = 239; SMR<1year 1·3, 95% CI 1·2-1·5), declining thereafter (n = 522; SMR≥5years 1·1, 95% CI 1·1-1·2). Myelodysplastic syndrome/acute myeloid leukaemia deaths were notably increased (n = 46; SMR 4·4, 95% CI 3·2-5·9), whereas solid neoplasm deaths were only elevated among ≥5-year survivors (n = 145; SMR≥5years 1·3, 95% CI 1·1-1·5). This work identifies new areas for optimising care and reducing mortality for patients with LPL/WM.

Health Care Cost Reductions with Machine Learning-Directed Evaluations during Radiation Therapy - An Economic Analysis of a Randomized Controlled Study.

BACKGROUND: Machine learning (ML) may cost-effectively direct health care by identifying patients most likely to benefit from preventative interventions to avoid negative and expensive outcomes. System for High-Intensity Evaluation During Radiation Therapy (SHIELD-RT; NCT04277650) was a single-institution, randomized controlled study in which electronic health record-based ML accurately identified patients at high risk for acute care (emergency visit or hospitalization) during radiotherapy (RT) and targeted them for supplemental clinical evaluations. This ML-directed intervention resulted in decreased acute care utilization. Given the limited prospective data showing the ability of ML to direct interventions cost-efficiently, an economic analysis was performed. METHODS: A post hoc economic analysis was conducted of SHIELD-RT that included RT courses from January 7, 2019, to June 30, 2019. ML-identified high-risk courses (≥10% risk of acute care during RT) were randomized to receive standard of care weekly clinical evaluations with ad hoc supplemental evaluations per clinician discretion versus mandatory twice-weekly evaluations. The primary outcome was difference in mean total medical costs during and 15 days after RT. Acute care costs were obtained via institutional cost accounting. Physician and intervention costs were estimated via Medicare and Medicaid data. Negative binomial regression was used to estimate cost outcomes after adjustment for patient and disease factors. RESULTS: A total of 311 high-risk RT courses among 305 patients were randomized to the standard (n=157) or the intervention (n=154) group. Unadjusted mean intervention group supplemental visit costs were $155 per course (95% confidence interval, $142 to $168). The intervention group had fewer acute care visits per course (standard, 0.47; intervention, 0.31; P=0.04). Total mean adjusted costs were $3110 per course for the standard group and $1494 for the intervention group (difference in means, $1616 [95% confidence interval, $1450 to $1783]; P=0.03). CONCLUSIONS: In this economic analysis of a randomized controlled, health care ML study, mandatory supplemental evaluations for ML-identified high-risk patients were associated with both reduced total medical costs and improved clinical outcomes. Further study is needed to determine whether economic results are generalizable. (Funded in part by The Duke Endowment, The Conquer Cancer Foundation, the Duke Department of Radiation Oncology, and the National Cancer Institute of the National Institutes of Health [R01CA277782]; ClinicalTrials.gov number, NCT04277650.).

Trends in risk for therapy-related myelodysplastic syndrome/acute myeloid leukemia after initial chemo/immunotherapy for common and rare lymphoid neoplasms, 2000-2018.

Background: Historically, survivors of common lymphoid neoplasms (LNs) had increased risks for therapy-related myelodysplastic syndrome/acute myeloid leukemia (tMDS/AML). Despite major treatment advances in the treatment of LNs over the last two decades, a comprehensive evaluation of tMDS/AML trends following both common and rare LNs treated in this contemporary period is lacking. Methods: In US cancer registries during 2000-2018, we identified 1496 tMDS/AML cases among 186,503 adults who were treated with initial chemo/immunotherapy for first primary LN and survived ≥1 year. We quantified tMDS/AML standardized incidence ratios (SIRs), excess absolute risks (EARs, per 10,000 person-years), and cumulative incidence. Findings: The highest tMDS/AML risks occurred after precursor leukemia/lymphoma (SIR = 39, EAR = 30), Burkitt leukemia/lymphoma (SIR = 20, EAR = 24), peripheral T-cell lymphoma (SIR = 12, EAR = 23), chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL; SIR = 9.0, EAR = 27), and mantle cell lymphoma (SIR = 8.5, EAR = 25). Elevated risks (SIRs = 4.2-6.9, EARs = 4.9-15) also were observed after all other LN subtypes except hairy cell leukemia and mycosis fungoides/Sézary syndrome. Among patients treated more recently, tMDS/AML risks were significantly higher after CLL/SLL (SIR2000-2005 = 4.8, SIR2012-2017 = 10, Ptrend = 0.0043), significantly lower after Hodgkin (SIR2000-2005 = 15, SIR2012-2017 = 6.3, Ptrend = 0.024) and marginal zone (SIR2000-2005 = 7.5, SIR2012-2017 = 2.3, Ptrend = 0.015) lymphomas, and non-significantly lower after mantle cell lymphoma (SIR2000-2005 = 10, SIR2012-2017 = 3.2, Ptrend = 0.054), lymphoplasmacytic lymphoma/Waldenström macroglobulinemia (SIR2000-2005 = 6.9, SIR2012-2017 = 1.0, Ptrend = 0.067), and plasma cell neoplasms (SIR2000-2005 = 5.4, SIR2012-2017 = 3.1, Ptrend = 0.051). EAR and cumulative incidence trends generally were similar to SIR trends. Median survival after tMDS/AML was 8.0 months (interquartile range, 3.0-22.0). Interpretation: Although tMDS/AML risks are significantly elevated after initial chemo/immunotherapy for most LNs, patients treated more recently have lower tMDS/AML risks, except after CLL/SLL. Though rare, the poor prognosis following tMDS/AML emphasizes the importance of continued efforts to reduce treatment-associated toxicity. Funding: This research was supported in part by the Intramural Research Program of the National Cancer Institute, National Institutes of Health. LMM, GMD, REC, and CBS verified the data, and all authors had access to the data and made the decision to submit for publication.

A Multimedia Strategy to Integrate Introductory Broad-Based Radiation Science Education in US Medical Schools.

US physicians in multiple specialties who order or conduct radiological procedures lack formal radiation science education and thus sometimes order procedures of limited benefit or fail to order what is necessary. To this end, a multidisciplinary expert group proposed an introductory broad-based radiation science educational program for US medical schools. Suggested preclinical elements of the curriculum include foundational education on ionizing and nonionizing radiation (eg, definitions, dose metrics, and risk measures) and short- and long-term radiation-related health effects as well as introduction to radiology, radiation therapy, and radiation protection concepts. Recommended clinical elements of the curriculum would impart knowledge and practical experience in radiology, fluoroscopically guided procedures, nuclear medicine, radiation oncology, and identification of patient subgroups requiring special considerations when selecting specific ionizing or nonionizing diagnostic or therapeutic radiation procedures. Critical components of the clinical program would also include educational material and direct experience with patient-centered communication on benefits of, risks of, and shared decision making about ionizing and nonionizing radiation procedures and on health effects and safety requirements for environmental and occupational exposure to ionizing and nonionizing radiation. Overarching is the introduction to evidence-based guidelines for procedures that maximize clinical benefit while limiting unnecessary risk. The content would be further developed, directed, and integrated within the curriculum by local faculties and would address multiple standard elements of the Liaison Committee on Medical Education and Core Entrustable Professional Activities for Entering Residency of the Association of American Medical Colleges.

Cause-Specific Mortality Following Initial Chemotherapy in a Population-Based Cohort of Patients With Classical Hodgkin Lymphoma, 2000-2016.

PURPOSE: Mortality for patients with classical Hodgkin lymphoma (cHL) treated during an era characterized in the United States by widespread use of doxorubicin, bleomycin, vinblastine, and dacarbazine and diminishing use of radiotherapy is not well understood. PATIENTS AND METHODS: We identified 20,007 individuals diagnosed with stage I/II (early) or III/IV (advanced) cHL between age 20 and 74 years treated with initial chemotherapy in US population-based cancer registries during 2000-2015 (follow-up through 2016). We used standardized mortality ratios (SMRs) to compare cause-specific relative mortality risk following cHL to that expected in the general population and estimated excess absolute risks (EARs; per 10,000 patient-years) to quantify disease-specific death burden. RESULTS: We identified 3,380 deaths in the cHL cohort, including 1,321 (39%) not attributed to lymphoma. Overall, noncancer SMRs were increased 2.4-fold (95% CI, 2.2 to 2.6; observed, 559; EAR, 61.6) and 1.6-fold (95% CI, 1.4 to 1.7; observed, 473; EAR, 18.2) for advanced- and early-stage cHL, respectively, compared with the general US population. SMRs and EARs differed substantially by cause of death and cHL stage. Among the highest EARs for noncancer causes of death were those for heart disease (EAR, 15.1; SMR, 2.1), infections (EAR, 10.6; SMR, 3.9), interstitial lung disease (ILD; EAR, 9.7; SMR, 22.1), and adverse events (AEs) related to medications/drugs (EAR, 7.4; SMR, 5.0) after advanced-stage cHL and heart disease (EAR, 6.6; SMR, 1.7), ILD (EAR, 3.7; SMR, 13.1), and infections (EAR, 3.1; SMR, 2.2) after early-stage cHL. Strikingly elevated SMRs for ILD, infections, and AEs were observed < 1 year after cHL. Individuals age 60-74 years with advanced-stage cHL experienced a disproportionate excess of deaths as a result of heart disease, ILD, infections, AEs, and solid tumors. CONCLUSION: Despite evolving cHL treatment approaches, patients continue to face increased nonlymphoma mortality risks from multiple, potentially preventable causes. Surveillance, early interventions, and cHL treatment refinements may favorably affect patient longevity, particularly among high-risk subgroups.

System for High-Intensity Evaluation During Radiation Therapy (SHIELD-RT): A Prospective Randomized Study of Machine Learning-Directed Clinical Evaluations During Radiation and Chemoradiation.

PURPOSE: Patients undergoing outpatient radiotherapy (RT) or chemoradiation (CRT) frequently require acute care (emergency department evaluation or hospitalization). Machine learning (ML) may guide interventions to reduce this risk. There are limited prospective studies investigating the clinical impact of ML in health care. The objective of this study was to determine whether ML can identify high-risk patients and direct mandatory twice-weekly clinical evaluation to reduce acute care visits during treatment. PATIENTS AND METHODS: During this single-institution randomized quality improvement study (ClinicalTrials.gov identifier: NCT04277650), 963 outpatient adult courses of RT and CRT started from January 7 to June 30, 2019, were evaluated by an ML algorithm. Among these, 311 courses identified by ML as high risk (> 10% risk of acute care during treatment) were randomized to standard once-weekly clinical evaluation (n = 157) or mandatory twice-weekly evaluation (n = 154). Both arms allowed additional evaluations on the basis of clinician discretion. The primary end point was the rate of acute care visits during RT. Model performance was evaluated using receiver operating characteristic area under the curve (AUC) and decile calibration plots. RESULTS: Twice-weekly evaluation reduced rates of acute care during treatment from 22.3% to 12.3% (difference, -10.0%; 95% CI, -18.3 to -1.6; relative risk, 0.556; 95% CI, 0.332 to 0.924; P = .02). Low-risk patients had a 2.7% acute care rate. Model discrimination was good in high- and low-risk patients undergoing standard once-weekly evaluation (AUC, 0.851). CONCLUSION: In this prospective randomized study, ML accurately triaged patients undergoing RT and CRT, directing clinical management with reduced acute care rates versus standard of care. This prospective study demonstrates the potential benefit of ML in health care and offers opportunities to enhance care quality and reduce health care costs.