Observational data provide invaluable real-world information in medicine, but certain methodological considerations are required to derive causal estimates. In this systematic review, we evaluated the methodology and reporting quality of individual-level patient data meta-analyses (IPD-MAs) conducted with non-randomized exposures, published in 2009, 2014, and 2019 that sought to estimate a causal relationship in medicine. We screened over 16,000 titles and abstracts, reviewed 45 full-text articles out of the 167 deemed potentially eligible, and included 29 into the analysis. Unfortunately, we found that causal methodologies were rarely implemented, and reporting was generally poor across studies. Specifically, only three of the 29 articles used quasi-experimental methods, and no study used G-methods to adjust for time-varying confounding. To address these issues, we propose stronger collaborations between physicians and methodologists to ensure that causal methodologies are properly implemented in IPD-MAs. In addition, we put forward a suggested checklist of reporting guidelines for IPD-MAs that utilize causal methods. This checklist could improve reporting thereby potentially enhancing the quality and trustworthiness of IPD-MAs, which can be considered one of the most valuable sources of evidence for health policy.

Difference-in-difference (DID) estimators are a valuable method for identifying causal effects in the public health researcher\'s toolkit. A growing methods literature points out potential problems with DID estimators when treatment is staggered in adoption and varies with time. Despite this, no practical guide exists for addressing these new critiques in public health research. We illustrate these new DID concepts with step-by-step examples, code, and a checklist. We draw insights by comparing the simple 2 × 2 DID design (single treatment group, single control group, two time periods) with more complex cases: additional treated groups, additional time periods of treatment, and treatment effects possibly varying over time. We outline newly uncovered threats to causal interpretation of DID estimates and the solutions the literature has proposed, relying on a decomposition that shows how the more complex DIDs are an average of simpler 2 × 2 DID subexperiments.

This paper provides guidelines for performing Mendelian randomization investigations. It is aimed at practitioners seeking to undertake analyses and write up their findings, and at journal editors and reviewers seeking to assess Mendelian randomization manuscripts. The guidelines are divided into ten sections: motivation and scope, data sources, choice of genetic variants, variant harmonization, primary analysis, supplementary and sensitivity analyses (one section on robust statistical methods and one on other approaches), extensions and additional analyses, data presentation, and interpretation. These guidelines will be updated based on feedback from the community and advances in the field. Updates will be made periodically as needed, and at least every 24 months.

The survival impact of adhering to current physical activity guidelines after prostate cancer diagnosis is unknown. We therefore emulated a target trial of guideline-based physical activity interventions and 10-year survival among US men with nonmetastatic prostate cancer. We used observational data on 2,299 men in the Health Professionals Follow-up Study who were diagnosed with nonmetastatic prostate cancer from 1998 to 2010 and were free of conditions that might have precluded participation at baseline (first postdiagnostic questionnaire). We estimated their survival under several guideline-based physical activity interventions starting at baseline and ending at the development of conditions limiting physical ability. We adjusted for baseline and time-varying risk factors for death using the parametric g-formula. Compared with the observed 15.4% mortality risk, the estimated 10-year risks of mortality were 13.0% (95% confidence interval (CI): 10.9, 15.4) and 11.1% (95% CI: 8.7, 14.1) for ≥1.25 hours/week and ≥2.5 hours/week of vigorous activity, respectively, and 13.9% (95% CI: 12.0, 16.0) and 12.6% (95% CI: 10.6, 14.7) for ≥2.5 hours/week and ≥5 hours/week of moderate activity, respectively. We estimated that these men would have experienced clinically meaningful reductions in mortality had they followed current physical activity recommendations until the development of conditions limiting physical ability. These findings may help guide clinical recommendations for prostate cancer patients and the design of future randomized trials.

The Guidelines Challenge Conference on which this special issue builds asked as the first of its \"further relevant questions\": \"How do we incorporate more types of causally relevant information in guidelines?\" This paper first supports the presupposition of this question-that we need further kinds of evidence-by pointing out that the randomized controlled trial, touted as the best source of evidence on effectiveness, can do so little for us. Second, it outlines a number of other good ways to learn what will work that the medical community, and much of the public health community, is not making much use of.

OBJECTIVE: There is a lack of real-world studies evaluating the impact on survival of an evidence-based pathway of care in breast cancer. The aim of this work is to investigate the effect of adherence to guidelines on long-term survival for a cohort of Italian breast cancer patients.
METHODS: The cohort included incident female breast cancer cases (2007-12), from the registry of the Milan province (Italy), not metastatic at diagnosis and receiving primary surgery. We selected sets of indicators, according to patient and tumor characteristics. We then defined the pathway of care as adherent to guidelines if it fulfilled at least 80% of the indicators. Indicators were measured using different administrative health databases linked on a unique key. A causal inference approach was used, drawing a directed acyclic graph and fitting an inverse probability weighted marginal structural model, accounting for patient\'s demographic, socioeconomic and tumor characteristics.
RESULTS: The analysis included 6333 patients, 69% of them were classified as having an adherent care. Mean age was 61 years (standard deviation, 13.6 years) and half of the patients were in Stage I (50%) at diagnosis. Median follow-up time was 5.6 years. Overall, 5-year survival was 90% (95% CI, 89-91%). The estimated risk of death was 30% lower for patients with adherent than nonadherent care (hazard ratio [HR], 0.66; 95% CI, 0.55-0.77).
CONCLUSIONS: Our study confirms, in real-world care, the impact on survival of receiving a care pathway adherent to guidelines in non-metastatic breast cancer patients.

Business theories often specify the mediating mechanisms by which a predictor variable affects an outcome variable. In the last 30 years, investigations of mediating processes have become more widespread with corresponding developments in statistical methods to conduct these tests. The purpose of this article is to provide guidelines for mediation studies by focusing on decisions made prior to the research study that affect the clarity of conclusions from a mediation study, the statistical models for mediation analysis, and methods to improve interpretation of mediation results after the research study. Throughout this article, the importance of a program of experimental and observational research for investigating mediating mechanisms is emphasized.