Citations

Abstract Examining treatment effects in subgroups of patients defined by demographic, genetic, or clinical characteristics is increasingly of interest given the pursuit of personalized medicine and the importance of representation and equity in treatment decisions. The magnitude or even the direction of the treatment effect may vary across subgroups, and these differential treatment effects could have clinical implications. Subgroup analyses require caution in their interpretation, however, because of the high probability of a false-positive or false-negative conclusion. We outline study design and analysis considerations for responsibly investigating and reporting differential treatment effects across subgroups in oncology trials, with examples from the National Cancer Institute’s National Clinical Trials Network and Community Oncology Research Program. Recommendations include ensuring appropriate representation of patients from subgroups of interest, recognizing power and multiplicity limitations, and treating exploratory subgroup analyses as hypothesis generating rather than practice changing.

Abstract The intracluster correlation coefficient (ICC) measures the correlation of observations within clusters and is a key parameter for power and sample size calculations for cluster randomized trials (CRTs). To facilitate the design of future CRTs within the National Cancer Institute Community Oncology Research Program (NCORP), all studies from the NCORP website were reviewed to identify completed CRTs. ICCs for primary and secondary outcomes (when available) were ascertained from these trials and summarized in this article as a resource for future trial development. Although ICCs are relatively small for many outcome cluster combinations, that is not always the case, so consideration should always be given to the specific outcome of interest, trial design, and type of cluster when estimating an ICC to facilitate trial development.

Abstract Cancer care delivery research trials conducted within the National Cancer Institute (NCI) Community Oncology Research Program (NCORP) routinely implement interventions at the practice or provider level, necessitating the use of cluster randomized controlled trials (cRCTs). The intervention delivery requires cluster-level randomization instead of participant-level, affecting sample size calculation and statistical analyses to incorporate correlation between participants within a practice. Practical challenges exist in the conduct of these cRCTs due to unique trial network infrastructures, including the possibility of unequal participant accrual totals and rates and staggered study initiation by clusters, potentially with differences between randomized arms. Execution of cRCT designs can be complex, ie, if some clusters do not accrue participants, unintended cluster-level crossover occurs, how best to identify appropriate cluster-level stratification, timing of randomization, and multilevel eligibility criteria considerations. This article shares lessons learned with potential mitigation strategies from 3 NCORP cRCTs.

In the introduction to his 1970 textbook BIOCHEMISTRY, Albert Lehninger wrote “Living things are composed of lifeless molecules [...]

Background: Fecal microbiota transplantation (FMT) is a successful therapy for Clostridioides difficile infection (CDI). FMT from overweight donors is speculated to influence the recipient’s body mass index (BMI) after administration for CDI. Objectives: We investigated changes in the recipient’s BMI after FMT in relation to the donor’s BMI. Design: We conducted a retrospective cohort study involving patients who underwent FMT for recurrent CDI at Mayo Clinic between 2012 and 2019. Methods: We analyzed demographic and donor data for patients undergoing FMT at Mayo Clinic (2012–2019). Recipient BMI (pre- and post-FMT) and donor BMI were extracted from medical records. Mixed-effects linear regression was used to evaluate the impact of donor BMI, donor BMI category, recipient baseline BMI, time before and after FMT, and interactions between these variables on overall BMI change and BMI change per month. Kaplan–Meier curves were used to assess BMI changes (⩾5 units) based on the last recorded post-FMT BMI. Results: We analyzed data from 401 patients with recorded BMI measurements before and after FMT. The median age of the recipients at the time of FMT was 59.1 years (interquartile range (IQR): 40.5–70.1 years), with 61.6% being female. The median BMI for recipients prior to FMT was 26.7 kg/m² (IQR: 22.7–31.6 kg/m²), while the median BMI of the donors was 24.5 kg/m2 (IQR: 23.9–27.5 kg/m2). Stool from donors with a normal BMI was used for 58.2% of recipients, while 41.8% received stool from pre-obese donors. Donor BMI data were missing for 3.2% of recipients. Donor BMI was not significantly associated with changes in recipient BMI; for each 1-unit increase in donor BMI, a 0.01-unit monthly increase was observed (95% confidence interval: −0.0003, 0.02; p = 0.11). The log-rank test for BMI increases (⩾+5) and decreases (⩽−5) revealed no significant differences among the donor BMI groups (Chi-squared = 4.4, p = 0.1 for increases, Chi-squared = 2, p = 0.4 for decreases). Conclusion: The lack of impact of donor BMI on BMI changes post-FMT suggests that these changes are more dependent on the recipient’s metabolic profile. Prospective, controlled trials are required to analyze these results more comprehensively.

BACKGROUND: Pharmacological treatments for fibrocalcific aortic valve stenosis (FCAVS) have been elusive for >50 years. Here, we tested the hypothesis that reactivation of oxidized sGC (soluble guanylate cyclase), the primary receptor for nitric oxide, with ataciguat is a safe and efficacious strategy to slow progression of FCAVS. METHODS: We used quantitative real-time reverse transcription polymerase chain reaction, Western blotting, and immunohistochemistry to characterize sGC signaling and the biological effects of ataciguat on signaling cascades related to nitric oxide, calcification, and fibrosis in excised human aortic valve tissue, aortic valve interstitial cells, and mouse aortic valves. We then conducted randomized, placebo-controlled phase I (14-day safety/tolerance) and phase II (6-month efficacy) trials in patients with moderate aortic valve stenosis. RESULTS: In excised human tissue, we found robust losses in sGC signaling despite upregulation of sGC subunits. In vitro, ataciguat increased sGC signaling and reduced BMP2 (bone morphogenetic protein 2) signaling in aortic valve interstitial cells. In mice with established FCAVS, treatment with ataciguat attenuated BMP signaling and slowed progression of valve calcification and dysfunction. In a phase I, randomized, placebo-controlled trial, treatment with ataciguat for 2 weeks was safe and well tolerated in patients with moderate FCAVS ( https://www.clinicaltrials.gov ; Unique identifier: NCT02049203). In a separate phase II, randomized, placebo-controlled trial, treatment with ataciguat for 6 months slowed the progression of aortic valve calcification and tended to slow the progression of valvular and ventricular dysfunction in patients with moderate FCAVS ( https://www.clinicaltrials.gov ; Unique identifier: NCT02481258). CONCLUSIONS: Collectively, this study highlights the therapeutic potential of the targeted restoration of the diseased/inactive form of sGC for treatment of FCAVS. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02049203. URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02481258.

Abstract Reducing antimicrobial exposure by limiting the duration of therapy is an effective antimicrobial stewardship strategy. In this article, we describe the impact of modification of the electronic health record to remove default durations of therapy on ambulatory antibiotic prescriptions issued from emergency departments in a large, multicenter health system.

Abstract Reconstructing gene expression atlases for human tissues is challenging due to limited access to healthy samples from live donors. Neurologically deceased donors often show ischemic changes, while tissues near diseased regions may have altered gene expression. The liver, with its unique regenerative capacity, allows analysis from live healthy donors (LHDs). Using spatial transcriptomics (Visum, Visium HD and MERFISH), we analyzed 16 liver samples: eight from young LHDs and eight from patients with liver pathology, sampling ‘adjacent normal’ tissue. LHD livers displayed significant gene expression differences from ‘adjacent normal’ tissues. Hepatocytes exhibited marked zonation along the porto-central axis of liver lobules, with key functions pericentrally shifted compared to other mammals. Our atlas identified dynamic programs in early steatotic hepatocytes, showing transitions from lipid uptake in low-lipid regions to insulin hypersensitivity in high-lipid regions. This study presents a spatial gene expression reference for the healthy human liver and insights into hepatocyte adaptations in steatosis.