Retraction Watch’s Post

Manni Mohyuddin, a professor of the Division of Hematology/Bone Marrow Transplant at the University of Utah Huntsman Cancer Institute recently published an opinion piece about the ethical challenges of clinical trials in oncological care (https://lnkd.in/dtqMvshe). Clinical trials are at the forefront of advancing oncological treatment and care, often fostering new approaches and therapies for patients battling cancer, thus offering them additional hope regarding the clinical outcomes and their quality of life. However, these trials often pose significant ethical challenges that demand our attention, mainly due to the need to balance the urgent need for innovation and the imperative to protect patient's rights and safety. Informed consent, patient selection, and the management of potential risks and benefits are of paramount and critical importance regarding ethical vigilance. As we push the boundaries of cancer research, it is essential to maintain a steadfast commitment to ethical principles, ensuring that every step forward is guided by a deep respect for patient rights and well-being. In doing so, I find it important to expand a little bit beyond the important and key Belmont Principles and always keep in mind the principle of "CLINICAL EQUIPOISE" which Jonathan Kimmelman, James McGill Professor in the Biomedical Ethics Unit of McGill University, addressed in 2021 when talking about the Ethics of Randomization in an interview for the American Society of Clinical Oncology (ASCO) Post: "The concept of clinical equipoise makes trial participation an ethical and valuable proposition for those physicians. This moral principle requires that randomized controlled trials should not be pursued without uncertainty in the expert community about the clinical merits of a treatment compared with the standard of care." The question raised is complex and this post aims not to bring a definitive answer to it but only to promote additional thoughts. The ASCO Post interview may be found here: https://lnkd.in/dW2AbpYs

The preprint of Estonian results from the EIT Health supported BRIGHT project study has been uploaded to medRxiv. Our study tested a genetic risk-based breast cancer screening model for women under 50 by polygenic risk score (PRS) and questionnaire-based monogenic pathogenic variant testing to identify higher-risk women for stratified follow-up. The study demonstrated the feasibility, clinical utility, and acceptability of the model, showing it could improve screening outcomes for those at higher genetic risk while avoiding unnecessary interventions for low-risk women. This model's implementation has the potential to enhance public breast cancer prevention strategies. The full text is available from https://lnkd.in/d9k-MEBv Congrats to Madli Tamm and our BRIGHT team! https://lnkd.in/dD9y5bGh #brightscreening #precisionprevention #breastcancer

⭐️Such a delight to share our paper on “Quantitative bias analysis for external control arms using real-world data in clinical trials: a primer for clinical researchers” 👉🏼Development of medicines in rare oncologic patient populations are growing, but well-powered randomized controlled trials are typically extremely challenging to conduct. 👉🏼External control arms using real-world data are increasingly used to supplement clinical trial evidence where no or little control arm data exists. 👉🏼Using an example of a comparison between pralsetinib single-arm trial data versus pembrolizumab alone or combined with chemotherapy real-world data for RET fusion-positive advanced non-small cell lung cancer (aNSCLC) patients (1-2% among all NSCLC), we illustrate how QBA can be applied to external control arms. ⭐️It was such a pleasure to work with amazing colleagues bringing in different perspectives to this work. Kristian Thorlund Sreeram Ramagopalan Alind Gupta Grace Hsu Paul Arora

CORAL: Expert-Curated Oncology Reports to Advance Language Model Inference https://lnkd.in/dUKbqVep Abstract Both medical care and observational studies in oncology require a thorough understanding of a patient’s disease progression and treatment history, often elaborately documented within clinical notes. As large language models (LLMs) are being considered for use within medical workflows, it becomes important to evaluate their potential in oncology. However, no current information representation schema fully encapsulates the diversity of oncology information within clinical notes, and no comprehensively annotated oncology notes exist publicly, thereby limiting a thorough evaluation. Authors: Madhumita Sushil, M.Sc., Ph.D., Vanessa E. Kennedy, M.D., Divneet Mandair, M.D., Brenda Y. Miao, B.A., Travis Zack, M.D., Ph.D. and Atul J. Butte, M.D., Ph.D

This article delves into a thought-provoking aspect of disparities in oncology care. Even in the egalitarian Dutch healthcare system, where all patients theoretically have equal opportunities to receive the best treatment, only oncology patients who can afford to pay out-of-pocket for whole genome sequencing (WGS) costing around 2,500 euros may have access to better treatments for their tumours. This is because some targeted, publicly funded treatments are only available to patients identified through WGS. However, WGS may not be available or reimbursed in all hospitals, creating a barrier to access for patients who cannot afford it.

"For years there has been an ongoing debate that real-world population outcomes are below those of the original clinical trial populations...Our recently announced partnership with NeoGenomics is directed at the importance and complexity of hematological malignancies real world studies and clinical trials. We now have the deepest, broadest, biomarker rich, and longest duration of observation data sets in hematology. These now include hundreds of biomarkers and the ability to bring together hematological pathology digital sources for AI model development and enabled insights." A great blog post written by our VP of Informatics (Lindsey Gasparini) and the CEO of ConcertAI (Jeff Elton) on the struggles of RCT, RWE as a potential solution, and our commitment to improving patient care. #cancer #oncology #realworlddata #clinicaltrials #precisionmedicine #nationalcancerpreventionmonth

Glad to share a recently published research article from PhD Scholar Pavan Narapaka on validity and reliability of the Hindi version of the SDM-Q-9 questionnaire in Indian oncology patients. The finding suggests that the SDM-Q-9 questionnaire is a suitable tool for measuring patient-reported involvement in clinical decision-making among Indian oncology patients. https://lnkd.in/gET5AdJ6

Our latest press release details our innovative work on integrating diagnostic data from both BD Biosciences and Beckman Coulter ClearLLab10C panels for Acute Myeloid Leukemia (AML) diagnosis. This integration marks a pivotal step in advancing healthcare access and precision medicine. #HealthcareInnovation #AML #aheadmedicine #flowcytometry

This insightful article in NEJM #AI evaluates #GPT-4's use in interpreting guidelines from the American Society of Clinical Oncology (ASCO) and the ESMO - European Society for Medical Oncology. The study assessed GPT-4’s ability to answer clinically relevant questions regarding pancreatic #cancer, metastatic colorectal cancer, and hepatocellular carcinoma. The results were striking: GPT-4 with Retrieval-Augmented Generation (RAG) provided correct responses in 84% of cases, compared to 57% without RAG. This 27% improvement highlights the potential of this technology to enhance clinical decision-making. These findings lead me to ponder several questions: How many #oncologists would face the same challenges in answering these questions accurately? How up-to-date are oncologists with the latest guidelines, considering the rapid pace of new cancer therapies and guideline revisions? What guidelines did GPT-4 get correct: those based on expert opinion or solid evidence? At Medint, we strive to envision a future where guidelines are updated much faster than we are accustomed to today. This raises another important consideration: what about those patients who do not perfectly fit within these guidelines? As we move towards the next stage of #personalizedmedicine, the ability of AI to provide #patient-centered and up-to-date recommendations will be crucial in ensuring the best possible outcomes for each patient. Read more here: https://lnkd.in/evFPdCii NEJM Group #healthcare #biotech

Intrinsic Subtype and Overall Survival in Advanced HR+/HER2− Breast Cancer Treated With Ribociclib and Endocrine Therapy Clinical Cancer Research BACKGROUND The MONALEESA-2, -3, -7 trials demonstrated statistically significant and clinically meaningful progression-free survival (PFS) and overall survival (OS) benefits with ribociclib + endocrine therapy (ET) vs ET alone in hormone receptor-positive, human epidermal growth factor receptor 2-negative (HR+/HER2-) advanced breast cancer (ABC). Understanding the association of intrinsic subtypes with survival outcomes could potentially guide treatment decisions. Here, we evaluated the association of intrinsic subtypes with OS in MONALEESA-2, -3, -7. PATIENTS AND METHODS Tumor samples from MONALEESA-2, -3, -7 underwent PAM50-based subtyping. The relationship between subtypes and OS was assessed using univariable and multivariable Cox proportional hazards models. Multivariable models were adjusted for clinical prognostic factors. RESULTS Overall, 990 tumors (among 2066 patients) from ribociclib (n=580) and placebo (n=410) arms were profiled. Subtype distribution was luminal A, 54.5%; luminal B, 28.0%; HER2E, 14.6%; basal-like, 2.8%; and was consistent across treatment arms. The luminal A subtype had the best OS outcomes in both arms, while basal-like had the worst. Patients with HER2E (HR, 0.60; P=.018), luminal B (HR, 0.69; P=.023), and luminal A (HR, 0.75; P=.021) subtypes derived OS benefit with ribociclib. Patients with basal-like subtype did not derive benefit from ribociclib (HR, 1.92; P=.137); however, patient numbers were small (n=28). CONCLUSION The prognostic value of intrinsic subtypes for OS was confirmed in this pooled analysis of the MONALEESA trials (largest data set in HR+/HER2- ABC). While basal-like subtype did not benefit, a consistent OS benefit was observed with ribociclib added to ET across luminal and HER2E subtypes.