Riaz, Irbaz B

The emergence of state-of-the-art large language models (LLMs), which hold the ability to generalize to diverse natural language processing tasks, has led to new opportunities in health care. Oncology is especially well-suited to leverage these resources as the journeys of patients with cancer inherently yield extensive, longitudinal data sets comprising clinical narratives, pathology and radiology reports, and genomic sequencing reports. This review begins with an overview of the fundamental concepts behind LLMs, including the definitions, architecture, training paradigm, and performance optimization through prompt engineering and retrieval-augmented generation. We also take a moment to explore the newly emerging paradigm of LLMs in a multiagentic framework. We then synthesize current research on how LLMs may benefit stakeholders within the practice of oncology, including patients, oncologists, researchers, and learners. Finally, we address the limitations and risks of LLMs, including hallucinations, inherent biases, patient privacy, and clinician deskilling. While research thus far shows significant potential for LLMs to transform cancer care, necessary future directions include studies emphasizing patient stakeholder perspectives on LLM incorporation in clinical workflows, the development of relevant clinical benchmarks for LLM evaluation, a greater focus on real-world prospective testing, and deeper exploration of LLM reasoning capabilities.

Abstract Background Socioeconomic position (SEP) is a fundamental social determinant of health (SDoH) contributing to observed disparities in cancer and cardiovascular (CV) care among individuals with prostate cancer (PC). Understanding the influence of SEP on CV health is essential for addressing outcome inequities within this population. Methods We conducted a retrospective study utilizing Surveillance, Epidemiology, and End Results (SEER)-Medicare to evaluate CV outcomes in patients ≥65 years with PC from 2009 to 2017. We studied the impact of SEP on cardiovascular events (CVEs), cardiovascular mortality (CVm), PC-specific mortality (PCsm), and all-cause mortality. CVE, CVm, and PCsm were analyzed using competing risk models and all-cause mortality with Cox proportional hazards models. A subgroup analysis was performed in Non-Hispanic Black and Non-Hispanic White individuals. Results We included 141 242 patients of whom 76 844 were in high SEP areas (45.6%) and 64 398 in low SEP ones (54.4%). Both groups had a mean age of 72 years; patients in low SEP areas were 67.5% Non-Hispanic White, 34.4% having diabetes, 73.3% hypertension, and 67.7% dyslipidemia versus the high SEP group with 85.6% Non-Hispanic White, 30.4% diabetes, 69.9% hypertension, and 70.7% dyslipidemia. Patients in low SEP areas had higher risks of CVm (subdistribution hazard ratio [sHR] = 1.18, 95% CI = 1.12 to 1.25), PCsm (sHR = 1.12, 95% CI = 1.06 to 1.17), CVE (sHR = 1.07, 95% CI = 1.04 to 1.09), and all-cause mortality (HR 1.16, 95% CI = 1.13 to 1.20). Accentuated results were shown in the Non-Hispanic Black subgroup. Conclusion Adverse SEP plays a significant role in shaping outcomes among older patients with PC, contributing to elevated risks of adverse CV and survival outcomes.

ASCO Guidelines provide recommendations with comprehensive review and analyses of the relevant literature for each recommendation, following the guideline development process as outlined in the ASCO Guidelines Methodology Manual . ASCO Guidelines follow the ASCO Conflict of Interest Policy for Clinical Practice Guidelines . Clinical Practice Guidelines and other guidance (“Guidance”) provided by ASCO is not a comprehensive or definitive guide to treatment options. It is intended for voluntary use by clinicians and should be used in conjunction with independent professional judgment. Guidance may not be applicable to all patients, interventions, diseases or stages of diseases. Guidance is based on review and analysis of relevant literature, and is not intended as a statement of the standard of care. ASCO does not endorse third-party drugs, devices, services, or therapies and assumes no responsibility for any harm arising from or related to the use of this information. See complete disclaimer in Appendix 1 and 2 (online only) for more . PURPOSE To provide evidence-based recommendations for patients with metastatic castration-resistant prostate cancer (mCRPC). METHODS An Expert Panel including patient representation completed a systematic review of the evidence and made recommendations. RESULTS Depending upon prior treatment received, androgen receptor pathway inhibitors (ARPIs: enzalutamide, abiraterone with prednisone), poly(ADP-ribose) polymerase inhibitors (PARPi), chemotherapeutic agents (docetaxel, cabazitaxel), radiopharmaceuticals (radium 223, 177 Lu-prostate-specific membrane antigen [PSMA]-617), and sipuleucel-T have demonstrated an overall survival (OS) benefit for patients with mCRPC. For patients with BRCA1 / 2 alterations who did not receive prior ARPI, the combination of PARPi and ARPI (talazoparib + enzalutamide, olaparib and/or niraparib + abiraterone) has shown clinical benefit. For patients with BRCA1 / 2 alterations who received prior ARPI or ARPI followed by docetaxel, olaparib showed OS benefit. In select patients with microsatellite instability-high/mismatch repair-deficient, pembrolizumab showed clinical efficacy. RECOMMENDATIONS Prior systemic therapy for castration-sensitive prostate cancer will determine subsequent therapy used for mCRPC. Continue androgen-deprivation therapy for patients with mCRPC indefinitely. Early adoption of somatic genetic testing and palliative care is recommended. Patients with mCRPC and bony metastases should receive a bone-protective agent. The panel recommends the combination of ARPI with PARPi in patients with BRCA1 / 2 alterations who did not receive prior ARPI. For patients who received prior ARPI, the panel recommends docetaxel chemotherapy. The panel recommends 177 Lu-PSMA-617 or cabazitaxel chemotherapy for patients who receive prior ARPI and docetaxel chemotherapy. For patients with BRCA1 / 2 alterations who received prior ARPI, the panel recommends PARPi monotherapy. Radium 223 is recommended for patients with symptomatic bone–only disease. Evidence for optimal sequencing for mCRPC regimens is lacking. Additional information is available at www.asco.org/genitourinary-cancer-guidelines .

PURPOSEThe advancement of natural language processing (NLP) has promoted the use of detailed textual data in electronic health records (EHRs) to support cancer research and to facilitate patient care. In this review, we aim to assess EHR for cancer research and patient care by using the Minimal Common Oncology Data Elements (mCODE), which is a community-driven effort to define a minimal set of data elements for cancer research and practice. Specifically, we aim to assess the alignment of NLP-extracted data elements with mCODE and review existing NLP methodologies for extracting said data elements.METHODSPublished literature studies were searched to retrieve cancer-related NLP articles that were written in English and published between January 2010 and September 2020 from main literature databases. After the retrieval, articles with EHRs as the data source were manually identified. A charting form was developed for relevant study analysis and used to categorize data including four main topics: metadata, EHR data and targeted cancer types, NLP methodology, and oncology data elements and standards.RESULTSA total of 123 publications were selected finally and included in our analysis. We found that cancer research and patient care require some data elements beyond mCODE as expected. Transparency and reproductivity are not sufficient in NLP methods, and inconsistency in NLP evaluation exists.CONCLUSIONWe conducted a comprehensive review of cancer NLP for research and patient care using EHRs data. Issues and barriers for wide adoption of cancer NLP were identified and discussed.

PURPOSE: Gender disparity persists in academic medicine. Female faculty are underrepresented in leadership positions and have lower research output. We studied gender differences in faculty rank and departmental leadership and contributing factors among academic hematologists and oncologists in the United States. METHODS: For clinical faculty at 146 hematology or oncology fellowship programs listed in the Fellowship and Residency Electronic Interactive Database, we collected data on demographics, academic rank, and research output using the Doximity and Scopus databases. We compared unadjusted characteristics of men and women by using 2-sided t tests and χ2 tests where appropriate. To predict probability of full professorship or leadership position among men versus women, we performed multivariable logistic regression analysis adjusted for clinical experience in years, number of publications, h-index, clinical trial investigator status, National Institutes of Health funding, and workplace ranking (top 20 v not). RESULTS: Two thousand one hundred sixty academic hematologists and oncologists were included. Women composed 21.9% (n = 142) of full professors, 35.7% (n = 169) of associate professors, and 45.4% (n = 415) of assistant professors. Thirty percent (n = 70) of departmental leaders were women. Female faculty, compared with male faculty, had a lower mean h-index (12.1 v 20.9, respectively; P < .001) and fewer years of professional experience since fellowship (10 v 16 years, respectively; P < .001). After adjusting for duration of clinical experience, academic productivity, and workplace ranking, the odds of obtaining professorship (odds ratio [OR], 1.05; 95% CI, 0.71 to 1.57; P = .85) or divisional leadership (OR, 0.57; 95% CI, 0.20 to 1.58; P = .28) for female physicians were not different compared with male physicians. CONCLUSION: Gender disparity exists in senior ranks of academic hematology and oncology; however, gender is not a significant predictor in achieving professorship or department leadership position.

PURPOSE: There is a concern that influenza vaccination could increase the incidence of immune-related adverse events (irAEs) in patients with cancer receiving immune checkpoint inhibitors. The aim of our study was to determine the safety of influenza vaccination in this patient population. PATIENTS AND METHODS: We retrospectively identified patients who received at least 1 dose of pembrolizumab during any influenza season from September 2014 to August 2017 and reviewed medical records for irAEs. The primary endpoint was the incidence of irAEs. We used multivariable logistic regression and cumulative incidence curve with competing risks for comparison. RESULTS: Among 162 patients with cancer included in this study, 70 patients (43.2%) received at least 1 influenza vaccination. The vaccinated group was significantly older ( P = .002) and received more cycles of pembrolizumab ( P = .006). The incidence of any grade irAEs in the vaccinated group trended toward being lower (25.7% v 40.2%; P = .07) compared with the nonvaccinated group. Influenza vaccination was independently associated with fewer irAEs, with an odds ratio of 0.4 (95% CI, 0.2 to 0.9; P = .03) in multivariable analyses. The vaccinated group was less likely to have irAEs compared with the nonvaccinated group (24.7% v 34.4% at 12 months; P = .05), with death as a competing risk. The median irAE-free duration in the vaccinated group was longer than the nonvaccinated group (not reached v 28 months; P = .037). CONCLUSION: Influenza vaccination in patients with cancer receiving immune checkpoint inhibitor therapy was not associated with increased irAEs. This supports the safety of influenza vaccination in this patient population.

Background Thromboprophylaxis is routinely used with lenalidomide‐based regimens in multiple myeloma because of a substantial risk of venous thromboembolism (VTE). However, little is known about the incidence of VTE with contemporary lenalidomide‐based regimens. The objective of the current study was to estimate the incidence of VTE despite thromboprophylaxis with currently used lenalidomide‐based regimens in patients with myeloma. Methods The Ovid MEDLINE, Embase, and Cochrane databases were queried from study inception to January 2019 for keywords to cover the following concepts: “lenalidomide,” “venous thromboembolism,” and “multiple myeloma.” Phase 1, 2, and 3 clinical trials evaluating lenalidomide‐based regimens with thromboprophylaxis were included. The pooled incidence rate of VTE was estimated using a random‐effects model. Results The search generated 1372 citations, with 51 clinical trials and 9069 patients included for analysis. The most common thromboprophylaxis agents were aspirin, low‐molecular‐weight heparin or warfarin, administered either per risk‐stratification or at investigators' discretion. The pooled incidence of VTE in trials of patients who had newly diagnosed and relapsed/refractory myeloma was 6.2% (95% CI, 5.4%‐7.1%) over median treatment durations ranging from 2 to 34 cycles, which translated into 1.2 VTE events per 100 patient‐cycles (95% CI, 0.9‐1.7 VTE events per 100 patient‐cycles). Among contemporary regimens, the risk of VTE was low with combined lenalidomide and low‐dose dexamethasone (0.2 [95% CI, 0.1‐0.6] events/100 patient‐cycles) and lenalidomide maintenance (0.0 [95% CI, 0.0‐0.7] events per 100 patient‐cycles). VTE risk was higher with combined lenalidomide and low‐dose dexamethasone plus proteasome inhibitors (1.3 [95% CI, 0.7‐2.3] events per 100 patient‐cycles). Conclusions Despite adequate thromboprophylaxis, lenalidomide‐based regimens have a substantial risk of VTE in controlled clinical trial settings. Further studies are needed on new thromboprophylaxis strategies with regimens that have a high VTE risk.