NEJM Evidence

Volume 3 Issue 5 of 𝘕𝘌𝘑𝘔 𝘌𝘷𝘪𝘥𝘦𝘯𝘤𝘦 is now available! Here is a preview of the latest content:      𝗢𝗿𝗶𝗴𝗶𝗻𝗮𝗹 𝗔𝗿𝘁𝗶𝗰𝗹𝗲𝘀  CDK4/6 Inhibitor Efficacy in ESR1-Mutant Metastatic Breast Cancer https://eviden.cc/3U5CDpX     A Trial of Automated Outbreak Detection to Reduce Hospital Pathogen Spread https://eviden.cc/3JtpamN    Intranasal Oxytocin for Obesity https://eviden.cc/3UvTFz2    Prostate Cancer Foundation Screening Guidelines for Black Men in the United States https://eviden.cc/3W8AwnI    𝗥𝗲𝘃𝗶𝗲𝘄 𝗔𝗿𝘁𝗶𝗰𝗹𝗲  Diagnostics for Public Health — Infectious Disease Surveillance and Control https://eviden.cc/4djcexI     𝗠𝗼𝗿𝗻𝗶𝗻𝗴 𝗥𝗲𝗽𝗼𝗿𝘁   A 73-Year-Old Man with Shortness of Breath, Edema, and Weight Gain https://eviden.cc/4b2w0vk     𝗖𝘂𝗿𝗯𝘀𝗶𝗱𝗲 𝗖𝗼𝗻𝘀𝘂𝗹𝘁  How Do I Manage Acute Pain for Patients Prescribed Buprenorphine for Opioid Use Disorder? https://eviden.cc/3UtSwqv     Explore all the latest original research and specialty articles in the May issue: https://eviden.cc/current  

What are cluster randomized controlled trials and how do investigators decide when to use them? This animated video dives into the basics of cluster RCTs. Watch the latest Stats, STAT! video: https://lnkd.in/eJ6JUYkd     #ClinicalTrials #MedicalResearch  

Not much longer than a decade ago, the approach to the treatment of estrogen receptor (ER)–positive, human epidermal growth factor receptor 2-negative, metastatic breast cancer focused primarily on the sequential use of a limited number of endocrine agents, continuing until progressively shorter durations of progression-free intervals were observed, suggesting the emergence of endocrine-refractory disease. Although data were emerging to suggest molecular mechanisms of endocrine resistance, including deregulation of the ER pathway, alterations in cell survival signals, and activation of escape pathways, therapeutic strategies that could leverage these insights were not available. Thus, the approach was to pivot to chemotherapy for the remainder of a patient’s journey through metastatic disease.     In recent years, a dual blockade strategy with cyclin-dependent kinase (CDK) 4/6 inhibitor therapy such as palbociclib, ribociclib, or abemaciclib has emerged as first-line therapy. CDK4 and CDK6 inhibit the Rb pathway that regulates progression from the G1 to S phases of the cell cycle. CDK4/6 inhibitors interfere with the function of these kinases and induce growth arrest. As a result of improved progression-free survival, CDK4/6 inhibitor therapy in combination with endocrine therapy has emerged as first-line therapy.     In this editorial, Patricia Robinson, MD, and William J. Gradishar, MD, review the recently published study by Maxwell R. Lloyd, MD, et al. on the effectiveness of CDK 4/6 inhibitors and endocrine therapy in patients with ESR1-mutant breast cancer using real-world data. They discuss the advantages and limitations of real-world data and the impact of these results in the context of the evolving therapeutic landscape for breast cancer.    Read the full editorial: https://eviden.cc/4daFiak 𝗙𝗨𝗥𝗧𝗛𝗘𝗥 𝗥𝗘𝗔𝗗𝗜𝗡𝗚  Original Article by Maxwell R. Lloyd, MD, et al.: CDK4/6 Inhibitor Efficacy in ESR1-Mutant Metastatic Breast Cancer https://eviden.cc/3U5CDpX    #Oncology #MedicalResearch 

Accurate diagnostics are critical in public health to ensure successful disease tracking, prevention, and control. Many of the same characteristics are desirable for diagnostic procedures in both medicine and public health: for example, low cost, high speed, low invasiveness, ease of use and interpretation, day-to-day consistency, and high accuracy. A review by Marc Lipsitch, DPhil, and Yonatan Grad, MD, PhD, lays out five principles that are salient when the goal of diagnosis is to improve the overall health of a population rather than that of a particular patient, and it applies them in two important use cases: pandemic infectious disease and antimicrobial resistance.    Continue reading “Diagnostics for Public Health — Infectious Disease Surveillance and Control,” the latest the latest review in the Diagnostic Evidence series, by Marc Lipsitch, DPhil, and Yonatan Grad, MD, PhD: https://eviden.cc/4djcexI 

Accumulating preclinical and preliminary translational evidence shows that the hypothalamic peptide oxytocin reduces food intake, increases energy expenditure, and promotes weight loss. It is currently unknown whether oxytocin administration is effective in treating human obesity.     In a randomized, double-blind, placebo-controlled trial, Elizabeth A. Lawson, MD, MMSc, et al. randomly assigned adults with obesity 1:1 (stratified by sex and obesity class) to receive intranasal oxytocin (24 IU) or placebo four times daily for 8 weeks. The primary end point was change in body weight (kg) from baseline to week 8. Key secondary end points included change in body composition (total fat mass [g], abdominal visceral adipose tissue [cm2], and liver fat fraction [proportion; range, 0 to 1; higher values indicate a higher proportion of fat]), and resting energy expenditure (kcal/day; adjusted for lean mass) from baseline to week 8 and caloric intake (kcal) at an experimental test meal from baseline to week 6.     The authors found that intranasal oxytocin administered four times daily for 8 weeks did not reduce body weight.    Read the Original Article “Intranasal Oxytocin for Obesity” by Elizabeth A. Lawson, MD, MMSc, et al.: https://eviden.cc/3UvTFz2    𝗙𝗨𝗥𝗧𝗛𝗘𝗥 𝗥𝗘𝗔𝗗𝗜𝗡𝗚  📄 Editorial by Hiroe Hu, DO, and Joseph G. Verbalis, MD: Oxytocin and Body Weight Homeostasis — Wrong Hypothesis or Wrong Methodology? https://eviden.cc/4d91kKH    #ClinicalTrials #MedicalResearch 

Racial inequities are well documented in cancer outcomes and access to novel therapies. Black people in the United States experience higher morbidity and mortality for most cancers compared with other groups and face greater barriers to high-quality cancer care. Black people have been underrepresented in clinical trials that led to U.S. Food and Drug Administration approval of oncology drugs, including novel chimeric antigen receptor T-cell therapies (CARTs). These inequities reflect structural racism that hinders access to high-quality care and perpetuates perceptions of groups of people based on a social construct called race. Eliminating disparities in cancer outcomes will require pharmacoequity, the goal of equitable access to prescribed treatments that meet the medical needs of all people regardless of social conditions or social status.    In an editorial, Drs. Marjory Charlot and Giselle Corbie review the recently published study by Ghilardi et al. describing the access and clinical outcomes of minority health populations with lymphoma eligible for commercial anti-CD19 CART at large academic institutions. They explore the implications of structural inequities contributing to reduced access to care.    Read the full editorial: https://eviden.cc/3TvT2n6    𝗙𝗨𝗥𝗧𝗛𝗘𝗥 𝗥𝗘𝗔𝗗𝗜𝗡𝗚  📄 Original Article by Marco Ruella, MD, Guido Ghilardi, MD, et al.: CAR T-Cell Immunotherapy in Minority Patients with Lymphoma  https://eviden.cc/3VuGgI9  📄 Editorial by LaQuisa Hill, MD, and Melody Smith, MD, MS: An Assessment of CAR-T Cell Therapy Utilization among Racial and Ethnic Minority Patients https://eviden.cc/3x2z1Nv    #MedicalResearch 

In estrogen receptor–positive metastatic breast cancer, ESR1 mutations (ESR1m) are a common mechanism of acquired resistance to aromatase inhibitors (ArIh). However, the impact ESR1 alterations have on CDK4/6 inhibitor (CDK4/6i) sensitivity has not been established. Analyses of CDK4/6i trials suggest that the endocrine therapy partner and specific ESR1 allele may affect susceptibility. This study by Lloyd et al. analyzed a real-world data set to investigate CDK4/6i efficacy in ESR1m metastatic breast cancer and associated clinical factors.     ESR1m were identified by analysis of circulating-tumor deoxyribonucleic acid. The GuardantINFORM database contains genomic information from tumors linked with claims data. Patients who started a CDK4/6i within 30 days of sequencing were categorized as having ESR1m or non-ESR1–mutant (non-ESR1m) breast cancer. Data were analyzed to determine the real-world time-to-next-treatment, defined as the start of a breast cancer treatment to initiation of the subsequent treatment.    Continue reading the Original Article “CDK4/6 Inhibitor Efficacy in ESR1-Mutant Metastatic Breast Cancer” by Maxwell R. Lloyd, MD, et al.: https://eviden.cc/3U5CDpX    𝗙𝗨𝗥𝗧𝗛𝗘𝗥 𝗥𝗘𝗔𝗗𝗜𝗡𝗚  📄 Editorial by Patricia Robinson, MD, and William J. Gradishar, MD: Leveraging Molecular Information for Optimal Treatment Recommendations https://eviden.cc/4daFiak    #MedicalResearch 

Heterogeneity of treatment effect is intuitive to the clinician at the bedside. When we recommend the best treatment for patients on the basis of their individual characteristics, we are applying the concept of heterogeneity of treatment effect. More formally, heterogeneity of treatment effect is defined as nonrandom variation in the benefit or harm of a treatment, in which the variation is associated with or attributable to patient characteristics. The article by Desai et al. in NEJM Evidence provides a contemporary example of exploring heterogeneity of treatment effect and offers an opportunity to understand how their approach fits within the larger research landscape. Investigating heterogeneity of treatment effect is appealing to researchers and clinicians because it promises to bridge the divide between randomized trial protocols (in which patients are treated the same) and bedside clinical decision-making (in which decisions are individualized). Analyses of heterogeneity of treatment effect often include conventional subgroup analyses, in which the effect of a treatment could vary across categories of sex, age, or other variables. Analyses may also include newer approaches in which a treatment effect could vary across subgroups identified through statistical modeling and defined by complex combinations of characteristics.    In this editorial, Drs. Christopher J. Yarnell and Michael Fralick review the article by Desai et al. describing methodologic considerations for individualized treatment effect prediction models using data from the TOPCAT trial, calling it an illustrative and informative example of exploring heterogeneity of treatment effects.    Read the full editorial: https://eviden.cc/3TuT2DP    𝗙𝗨𝗥𝗧𝗛𝗘𝗥 𝗥𝗘𝗔𝗗𝗜𝗡𝗚   Original Article by Rishi Desai, MS, PhD, et al.: Individualized Treatment Effect Prediction with Machine Learning — Salient Considerations https://eviden.cc/4cupGhU    #MedicalResearch 

In the United States, Black men are at highest risk for being diagnosed with and dying from prostate cancer. Given this disparity, William Oh, MD, et al. examined relevant data to establish clinical prostate-specific antigen (PSA) screening guidelines for Black men in the United States.    A comprehensive literature search identified 1848 unique publications for screening. Of those screened, 287 studies were selected for full-text review, and 264 were considered relevant and form the basis for these guidelines. The numbers were reported according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.    These guidelines recommend that Black men should obtain information about PSA screening for prostate cancer. Among Black men who elect screening, baseline PSA testing should occur between ages 40 and 45. Depending on PSA value and health status, annual screening should be strongly considered.    Read the Original Article “Prostate Cancer Foundation Screening Guidelines for Black Men in the United States” by William Oh, MD, et al.: https://eviden.cc/3W8AwnI    𝗙𝗨𝗥𝗧𝗛𝗘𝗥 𝗥𝗘𝗔𝗗𝗜𝗡𝗚  📄 Editorial by Richard M. Hoffman, MD, MPH: Reducing Prostate Cancer Disparities for Black Men https://eviden.cc/4b8bHNd    #MedicalResearch 

Detection and containment of hospital outbreaks currently depend on variable and personnel-intensive surveillance methods. Whether automated statistical surveillance for outbreaks of health care–associated pathogens allows earlier containment efforts that would reduce the size of outbreaks is unknown.     Meghan Baker, MD, ScD, et al. conducted a cluster-randomized trial in 82 community hospitals within a larger health care system. All hospitals followed an outbreak response protocol when outbreaks were detected by their infection prevention programs. Half of the hospitals additionally used statistical surveillance of microbiology data, which alerted infection prevention programs to outbreaks. Statistical surveillance was also applied to microbiology data from control hospitals without alerting their infection prevention programs. The primary outcome was the number of additional cases occurring after outbreak detection. Analyses assessed differences between the intervention period (July 2019 to January 2022) versus baseline period (February 2017 to January 2019) between randomized groups. A post hoc analysis separately assessed pre–coronavirus disease 2019 (Covid-19) and Covid-19 pandemic intervention periods.    Continue reading the Original Article “A Trial of Automated Outbreak Detection to Reduce Hospital Pathogen Spread” by Meghan Baker, MD, ScD, et al.: https://eviden.cc/3JtpamN    𝗙𝗨𝗥𝗧𝗛𝗘𝗥 𝗥𝗘𝗔𝗗𝗜𝗡𝗚  📄 Editorial by Scott C. Roberts, MD, MS, and Richard Martinello, MD: Can Patient Safety Be Improved by Using WHONET-SaTScan to Identify Outbreaks? https://eviden.cc/3xPvJh1    #ClinicalTrials #MedicalResearch