Integrase strand-transfer inhibitor use and cardiovascular events in adults with HIV: an emulation of target trials in the HIV-CAUSAL Collaboration and the Antiretroviral Therapy Cohort Collaboration.

BACKGROUND: A recent observational study suggested that the risk of cardiovascular events could be higher among antiretroviral therapy (ART)-naive individuals with HIV who receive integrase strand-transfer inhibitor (INSTI)-based ART than among those who receive other ART regimens. We aimed to emulate target trials separately in ART-naive and ART-experienced individuals with HIV to examine the effect of using INSTI-based regimens versus other ART regimens on the 4-year risk of cardiovascular events. METHODS: We used routinely recorded clinical data from 12 cohorts that collected information on cardiovascular events, BMI, and blood pressure from two international consortia of cohorts of people with HIV from Europe and North America. For the target trial in individuals who had previously never used ART (ie, ART-naive), eligibility criteria were aged 18 years or older, a detectable HIV-RNA measurement while ART-naive (>50 copies per mL), and no history of a cardiovascular event or cancer. Eligibility criteria for the target trial in those with previous use of non-INSTI-based ART (ie, ART-experienced) were the same except that individuals had to have been on at least one non-INSTI-based ART regimen and be virally suppressed (≤50 copies per mL). We assessed eligibility for both trials for each person-month between January, 2013, and January, 2023, and assigned individuals to the treatment strategy that was compatible with their data. We estimated the standardised 4-year risks of cardiovascular events (myocardial infarction, stroke, or invasive cardiovascular procedure) via pooled logistic regression models adjusting for time and baseline covariates. In per-protocol analyses, we censored individuals if they deviated from their assigned treatment strategy for more than 2 months and weighted uncensored individuals by the inverse of their time-varying probability of remaining uncensored. The denominator of the weight was estimated via a pooled logistic model that included baseline and time-varying covariates. FINDINGS: The analysis in ART-naive individuals included 10 767 INSTI initiators and 8292 non-initiators of INSTI. There were 43 cardiovascular events in INSTI initiators (median follow-up of 29 months; IQR 15-45) and 52 in non-initiators (39 months; 18-47): standardised 4-year risks were 0·76% (95% CI 0·51 to 1·04) in INSTI initiators and 0·75% (0·54 to 0·98) in non-INSTI initiators; risk ratio 1·01 (0·57 to 1·57); risk difference 0·0089% (-0·43 to 0·36). The analysis in ART-experienced individuals included 7875 INSTI initiators and 373 965 non-initiators. There were 56 events in INSTI initiators (median follow-up 18 months; IQR 9-29) and 3103 events (808 unique) in non-INSTI initiators (26 months; 15-37) in non-initiators: standardised 4-year risks 1·41% (95% CI 0·88 to 2·03) in INSTI initiators and 1·48% (1·28 to 1·71) in non-initiators; risk ratio 0·95 (0·60 to 1·36); risk difference -0·068% (-0·60 to 0·52). INTERPRETATION: We estimated that INSTI use did not result in a clinically meaningful increase of cardiovascular events in ART-naive and ART-experienced individuals with HIV. FUNDING: National Institute of Allergy and Infectious Diseases and National Institute on Alcohol Abuse and Alcoholism.

Evaluating Metformin Strategies for Cancer Prevention: A Target Trial Emulation Using Electronic Health Records.

BACKGROUND: Metformin users appear to have a substantially lower risk of cancer than nonusers in many observational studies. These inverse associations may be explained by common flaws in observational analyses that can be avoided by explicitly emulating a target trial. METHODS: We emulated target trials of metformin therapy and cancer risk using population-based linked electronic health records from the UK (2009-2016). We included individuals with diabetes, no history of cancer, no recent prescription for metformin or other glucose-lowering medication, and hemoglobin A1c (HbA1c) <64 mmol/mol (<8.0%). Outcomes included total cancer and 4 site-specific cancers (breast, colorectal, lung, and prostate). We estimated risks using pooled logistic regression with adjustment for risk factors via inverse-probability weighting. We emulated a second target trial among individuals regardless of diabetes status. We compared our estimates with those obtained using previously applied analytic approaches. RESULTS: Among individuals with diabetes, the estimated 6-year risk differences (metformin - no metformin) were -0.2% (95% CI = -1.6%, 1.3%) in the intention-to-treat analysis and 0.0% (95% CI = -2.1%, 2.3%) in the per-protocol analysis. The corresponding estimates for all site-specific cancers were close to zero. Among individuals regardless of diabetes status, these estimates were also close to zero and more precise. By contrast, previous analytic approaches yielded estimates that appeared strongly protective. CONCLUSIONS: Our findings are consistent with the hypothesis that metformin therapy does not meaningfully influence cancer incidence. The findings highlight the importance of explicitly emulating a target trial to reduce bias in the effect estimates derived from observational analyses.

Defining the role of real-world data in cancer clinical research: The position of the European Organisation for Research and Treatment of Cancer.

The emergence of the precision medicine paradigm in oncology has led to increasing interest in the integration of real-world data (RWD) into cancer clinical research. As sources of real-world evidence (RWE), such data could potentially help address the uncertainties that surround the adoption of novel anticancer therapies into the clinic following their investigation in clinical trials. At present, RWE-generating studies which investigate antitumour interventions seem to primarily focus on collecting and analysing observational RWD, typically forgoing the use of randomisation despite its methodological benefits. This is appropriate in situations where randomised controlled trials (RCTs) are not feasible and non-randomised RWD analyses can offer valuable insights. Nevertheless, depending on how they are designed, RCTs have the potential to produce strong and actionable RWE themselves. The choice of which methodology to employ for RWD studies should be guided by the nature of the research question they are intended to answer. Here, we attempt to define some of the questions that do not necessarily require the conduct of RCTs. Moreover, we outline the strategy of the European Organisation for Research and Treatment of Cancer (EORTC) to contribute to the generation of robust and high-quality RWE by prioritising the execution of pragmatic trials and studies set up according to the trials-within-cohorts approach. If treatment allocation cannot be left up to random chance due to practical or ethical concerns, the EORTC will consider undertaking observational RWD research based on the target trial principle. New EORTC-sponsored RCTs may also feature concurrent prospective cohorts composed of off-trial patients.

Head-to-head comparison of FOLFIRINOX versus gemcitabine plus nab-paclitaxel in advanced pancreatic cancer: a target trial emulation using real-world data.

PURPOSE: To emulate a hypothetical target trial assessing the effect of initiating 5-fluorouracil, folinic acid, irinotecan, and oxaliplatin (FOLFIRINOX) versus gemcitabine plus nab-paclitaxel (GN) within 8 weeks of diagnosis on overall survival. METHODS: An observational cohort study was conducted using population-level data from Alberta, Canada. Individuals diagnosed with advanced pancreatic cancer between April 2015 and December 2019 were identified through the provincial cancer registry and followed until March 2021. Records were linked to other administrative databases containing information on relevant variables. Individuals were excluded if they did not have adequate hemoglobin, platelet, white blood cell, and serum creatinine measures or if they received prior therapy. The observational analog of the per-protocol effect was estimated using inverse probability weighted Kaplan-Meier curves with bootstrapped 95% confidence intervals. RESULTS: Four hundred seven individuals were eligible. The weighted median overall survival was 8.3 months (95% CI, 5.7-11.9) for FOLFIRINOX and 5.1 months (95% CI: 4.3 to 5.8) for GN. The adjusted difference in median overall survival was 3.2 months (95% CI, 1.1-7.4) and the mortality hazard ratio was 0.78 (95% CI, 0.61-0.97). CONCLUSIONS: Our estimates favored the initiation of FOLFIRINOX over GN with respect to overall survival.

Effect of Colonoscopy Screening on Risks of Colorectal Cancer and Related Death.

BACKGROUND: Although colonoscopy is widely used as a screening test to detect colorectal cancer, its effect on the risks of colorectal cancer and related death is unclear. METHODS: We performed a pragmatic, randomized trial involving presumptively healthy men and women 55 to 64 years of age drawn from population registries in Poland, Norway, Sweden, and the Netherlands between 2009 and 2014. The participants were randomly assigned in a 1:2 ratio either to receive an invitation to undergo a single screening colonoscopy (the invited group) or to receive no invitation or screening (the usual-care group). The primary end points were the risks of colorectal cancer and related death, and the secondary end point was death from any cause. RESULTS: Follow-up data were available for 84,585 participants in Poland, Norway, and Sweden - 28,220 in the invited group, 11,843 of whom (42.0%) underwent screening, and 56,365 in the usual-care group. A total of 15 participants had major bleeding after polyp removal. No perforations or screening-related deaths occurred within 30 days after colonoscopy. During a median follow-up of 10 years, 259 cases of colorectal cancer were diagnosed in the invited group as compared with 622 cases in the usual-care group. In intention-to-screen analyses, the risk of colorectal cancer at 10 years was 0.98% in the invited group and 1.20% in the usual-care group, a risk reduction of 18% (risk ratio, 0.82; 95% confidence interval [CI], 0.70 to 0.93). The risk of death from colorectal cancer was 0.28% in the invited group and 0.31% in the usual-care group (risk ratio, 0.90; 95% CI, 0.64 to 1.16). The number needed to invite to undergo screening to prevent one case of colorectal cancer was 455 (95% CI, 270 to 1429). The risk of death from any cause was 11.03% in the invited group and 11.04% in the usual-care group (risk ratio, 0.99; 95% CI, 0.96 to 1.04). CONCLUSIONS: In this randomized trial, the risk of colorectal cancer at 10 years was lower among participants who were invited to undergo screening colonoscopy than among those who were assigned to no screening. (Funded by the Research Council of Norway and others; NordICC ClinicalTrials.gov number, NCT00883792.).

Emulation of a target trial with sustained treatment strategies: an application to prostate cancer using both inverse probability weighting and the g-formula.

As with many chronic illnesses, recurrent prostate cancer generally requires sustained treatment to prolong survival. However, initiating treatment immediately after recurrence may negatively impact quality of life without any survival gains. Therefore, we consider sustained strategies for initiating treatment based on specific characteristics of prostate-specific antigen (PSA), which can indicate disease progression. We define the protocol for a target trial comparing treatment strategies based on PSA doubling time, in which androgen deprivation therapy is initiated only after doubling time decreases below a certain threshold. Such a treatment strategy means the timing of treatment initiation (if ever) is not known at baseline, and the target trial protocol must explicitly specify the frequency of PSA monitoring until the threshold is met, as well as the duration of treatment. We describe these and other components of a target trial that need to be specified in order for such a trial to be emulated in observational data. We then use the parametric g-formula and inverse-probability weighted dynamic marginal structural models to emulate our target trial in a cohort of prostate cancer patients from clinics across the United States.

Emulating a target trial of the comparative effectiveness of clomiphene citrate and letrozole for ovulation induction.

STUDY QUESTION: What are the comparative pregnancy outcomes in women who receive up to six consecutive cycles of ovulation induction with letrozole versus clomiphene citrate? SUMMARY ANSWER: The risks of pregnancy, livebirth, multiple gestation, preterm birth, neonatal intensive care unit (NICU) admission and congenital malformations were higher for letrozole compared with clomiphene in participants with polycystic ovarian syndrome (PCOS), though no treatment differences were observed in those with unexplained infertility. WHAT IS KNOWN ALREADY: Randomized trials have reported higher pregnancy and livebirth rates for letrozole versus clomiphene among individuals with PCOS, but no differences among those with unexplained infertility. None of these trials were designed to study maternal or neonatal complications. STUDY DESIGN, SIZE, DURATION: We emulated a hypothetical trial of the comparative effectiveness of letrozole versus clomiphene citrate for ovulation induction among all women, then stratified by PCOS and unexplained infertility status. We used real-world data from a large healthcare claims database in the USA (2011-2015). PARTICIPANTS/MATERIALS, SETTING, METHODS: We analyzed data from 18 120 women who initiated letrozole and 49 647 women who initiated clomiphene during 2011-2014, and who were aged 18-45 years with no history of diabetes, thyroid disease, liver disease or breast cancer and had no fertility treatments for 3 months before trial initiation. The treatment strategies were clomiphene citrate or letrozole for six consecutive cycles. The outcomes were pregnancy, livebirth, multiple gestation, preterm birth, small for gestational age (SGA), NICU admission and major congenital malformations. We estimated the probability of each outcome under each strategy via pooled logistic regression and used standardization to adjust for confounding and selection bias due to loss to follow-up. MAIN RESULTS AND THE ROLE OF CHANCE: The estimated probabilities of pregnancy, livebirth and neonatal outcomes were similar under each strategy, both overall and among individuals with unexplained infertility. Among women with PCOS, the probability of pregnancy was 43% for letrozole vs 37% for clomiphene (risk difference [RD] = 6.0%; 95% CI: 4.4, 7.7) in the intention-to-treat analyses. The corresponding probability of livebirth was 32% vs 29% (RD = 3.1%; 95% CI: 1.5, 4.8). In per protocol analyses, the risk of multiple gestation was 19% vs 9%, the risk of preterm birth was 20% vs 15%, the risk of SGA was 5% vs 3%, the risk of NICU admission was 22% vs 16% and the risk of congenital malformation was 8% vs 2% among those with a livebirth. LIMITATIONS, REASONS FOR CAUTION: We cannot completely rule out the possibility of residual confounding by body mass index or duration of infertility. However, we adjusted for proxies identified in administrative data and results did not change. WIDER IMPLICATIONS OF THE FINDINGS: Our findings suggest that for women with unexplained infertility, the two treatments result in comparable probabilities of a livebirth. For women with PCOS, letrozole appears slightly more effective for attaining a livebirth. Neonatal outcomes were similar for the two treatments among women with unexplained infertility; we did not confirm the hypothesized higher risk of adverse neonatal outcomes for clomiphene versus letrozole. The risks of adverse neonatal outcomes were slightly greater among women with PCOS who were treated with letrozole versus clomiphene. It is likely that these effects are partially mediated through an increased risk of multiple gestation among women who received letrozole. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by the National Institute of Child Health and Human Development (R01HD088393). Y.-H.C. reports grants from the American Heart Association (834106) and NIH (R01HD097778). P.R. reports grants from the National Institutes of Health. J.H. reports grants from the National Institutes of Health, the Agency for Healthcare Research and Quality, and the California Health Care Foundation during the conduct of the study; and consulting for several health care delivery organizations including Cambridge Health Alliance, Columbia University, University of Southern California, Community Servings, and the Delta Health Alliance. S.H.-D. reports grants from the National Institutes of Health and the US Food and Drug Administration during the conduct of the study; grants to her institution from Takeda outside the submitted work; consulting for UCB (biopharmaceutical company) and Roche; and being an adviser for the Antipsychotics Pregnancy Registry and epidemiologist for the North American Antiepileptics Pregnancy Registry, both at Massachusetts General Hospital. M.A.H. reports grants from the National Institutes of Health and the U.S. Veterans Administration during the conduct of the study; being a consultant for Cytel; and being an adviser for ProPublica. TRIAL REGISTRATION NUMBER: N/A.

Instrumental variable estimation for a time-varying treatment and a time-to-event outcome via structural nested cumulative failure time models.

BACKGROUND: In many applications of instrumental variable (IV) methods, the treatments of interest are intrinsically time-varying and outcomes of interest are failure time outcomes. A common example is Mendelian randomization (MR), which uses genetic variants as proposed IVs. In this article, we present a novel application of g-estimation of structural nested cumulative failure models (SNCFTMs), which can accommodate multiple measures of a time-varying treatment when modelling a failure time outcome in an IV analysis. METHODS: A SNCFTM models the ratio of two conditional mean counterfactual outcomes at time k under two treatment strategies which differ only at an earlier time m. These models can be extended to accommodate inverse probability of censoring weights, and can be applied to case-control data. We also describe how the g-estimates of the SNCFTM parameters can be used to calculate marginal cumulative risks under nondynamic treatment strategies. We examine the performance of this method using simulated data, and present an application of these models by conducting an MR study of alcohol intake and endometrial cancer using longitudinal observational data from the Nurses' Health Study. RESULTS: Our simulations found that estimates from SNCFTMs which used an IV approach were similar to those obtained from SNCFTMs which adjusted for confounders, and similar to those obtained from the g-formula approach when the outcome was rare. In our data application, the cumulative risk of endometrial cancer from age 45 to age 72 under the "never drink" strategy (4.0%) was similar to that under the "always ½ drink per day" strategy (4.3%). CONCLUSIONS: SNCFTMs can be used to conduct MR and other IV analyses with time-varying treatments and failure time outcomes.

Safety of the BNT162b2 mRNA Covid-19 Vaccine in a Nationwide Setting.

BACKGROUND: Preapproval trials showed that messenger RNA (mRNA)-based vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had a good safety profile, yet these trials were subject to size and patient-mix limitations. An evaluation of the safety of the BNT162b2 mRNA vaccine with respect to a broad range of potential adverse events is needed. METHODS: We used data from the largest health care organization in Israel to evaluate the safety of the BNT162b2 mRNA vaccine. For each potential adverse event, in a population of persons with no previous diagnosis of that event, we individually matched vaccinated persons to unvaccinated persons according to sociodemographic and clinical variables. Risk ratios and risk differences at 42 days after vaccination were derived with the use of the Kaplan-Meier estimator. To place these results in context, we performed a similar analysis involving SARS-CoV-2-infected persons matched to uninfected persons. The same adverse events were studied in the vaccination and SARS-CoV-2 infection analyses. RESULTS: In the vaccination analysis, the vaccinated and control groups each included a mean of 884,828 persons. Vaccination was most strongly associated with an elevated risk of myocarditis (risk ratio, 3.24; 95% confidence interval [CI], 1.55 to 12.44; risk difference, 2.7 events per 100,000 persons; 95% CI, 1.0 to 4.6), lymphadenopathy (risk ratio, 2.43; 95% CI, 2.05 to 2.78; risk difference, 78.4 events per 100,000 persons; 95% CI, 64.1 to 89.3), appendicitis (risk ratio, 1.40; 95% CI, 1.02 to 2.01; risk difference, 5.0 events per 100,000 persons; 95% CI, 0.3 to 9.9), and herpes zoster infection (risk ratio, 1.43; 95% CI, 1.20 to 1.73; risk difference, 15.8 events per 100,000 persons; 95% CI, 8.2 to 24.2). SARS-CoV-2 infection was associated with a substantially increased risk of myocarditis (risk ratio, 18.28; 95% CI, 3.95 to 25.12; risk difference, 11.0 events per 100,000 persons; 95% CI, 5.6 to 15.8) and of additional serious adverse events, including pericarditis, arrhythmia, deep-vein thrombosis, pulmonary embolism, myocardial infarction, intracranial hemorrhage, and thrombocytopenia. CONCLUSIONS: In this study in a nationwide mass vaccination setting, the BNT162b2 vaccine was not associated with an elevated risk of most of the adverse events examined. The vaccine was associated with an excess risk of myocarditis (1 to 5 events per 100,000 persons). The risk of this potentially serious adverse event and of many other serious adverse events was substantially increased after SARS-CoV-2 infection. (Funded by the Ivan and Francesca Berkowitz Family Living Laboratory Collaboration at Harvard Medical School and Clalit Research Institute.).

Strengthening Health Services Research Using Target Trial Emulation: An Application to Volume-Outcomes Studies.

The number of operations that surgeons have previously performed is associated with their patients' outcomes. However, this association may not be causal, because previous studies have often been cross-sectional and their analyses have not considered time-varying confounding or positivity violations. In this paper, using the example of surgeons who perform coronary artery bypass grafting, we describe (hypothetical) target trials for estimation of the causal effect of the surgeons' operative volumes on patient mortality. We then demonstrate how to emulate these target trials using data from US Medicare claims and provide effect estimates. Our target trial emulations suggest that interventions on physicians' volume of coronary artery bypass grafting operations have little effect on patient mortality. The target trial framework highlights key assumptions and draws attention to areas of bias in previous observational analyses that deviated from their implicit target trials. The principles of the presented methodology may be adapted to other scenarios of substantive interest in health services research.

Emulating a target trial in case-control designs: an application to statins and colorectal cancer.

BACKGROUND: Previous case-control studies have reported a strong association between statin use and lower cancer risk. It is unclear whether this association reflects a benefit of statins or is the result of design decisions that cannot be mapped to a (hypothetical) target trial (that would answer the question of interest). METHODS: We outlined the protocol of a target trial to estimate the effect of statins on colorectal cancer incidence among adults with low-density lipoprotein (LDL) cholesterol below 5 mmol/L. We then emulated the target trial using linked electronic health records of 752 469 eligible UK adults (CALIBER 1999-2016) under both a cohort design and a case-control sampling of the cohort. We used pooled logistic regression to estimate intention-to-treat and per-protocol effects of statins on colorectal cancer, with adjustment for baseline and time-varying risk factors via inverse-probability weighting. Finally, we compared our case-control effect estimates with those obtained using previous case-control procedures. RESULTS: Over the 6-year follow-up, 3596 individuals developed colorectal cancer. Estimated intention-to-treat and per-protocol hazard ratios were 1.00 (95% confidence interval [CI]: 0.87, 1.16) and 0.90 (95% CI: 0.71, 1.12), respectively. As expected, adequate case-control sampling yielded the same estimates. By contrast, previous case-control analytical approaches yielded estimates that appeared strongly protective (odds ratio 0.57, 95% CI: 0.36, 0.91, for ≥5 vs. <5 years of statin use). CONCLUSIONS: Our study demonstrates how to explicitly emulate a target trial using case-control data to reduce discrepancies between observational and randomized trial evidence. This approach may inform future case-control analyses for comparative effectiveness research.

Factors Associated With Death in Critically Ill Patients With Coronavirus Disease 2019 in the US.

Importance: The US is currently an epicenter of the coronavirus disease 2019 (COVID-19) pandemic, yet few national data are available on patient characteristics, treatment, and outcomes of critical illness from COVID-19. Objectives: To assess factors associated with death and to examine interhospital variation in treatment and outcomes for patients with COVID-19. Design, Setting, and Participants: This multicenter cohort study assessed 2215 adults with laboratory-confirmed COVID-19 who were admitted to intensive care units (ICUs) at 65 hospitals across the US from March 4 to April 4, 2020. Exposures: Patient-level data, including demographics, comorbidities, and organ dysfunction, and hospital characteristics, including number of ICU beds. Main Outcomes and Measures: The primary outcome was 28-day in-hospital mortality. Multilevel logistic regression was used to evaluate factors associated with death and to examine interhospital variation in treatment and outcomes. Results: A total of 2215 patients (mean [SD] age, 60.5 [14.5] years; 1436 [64.8%] male; 1738 [78.5%] with at least 1 chronic comorbidity) were included in the study. At 28 days after ICU admission, 784 patients (35.4%) had died, 824 (37.2%) were discharged, and 607 (27.4%) remained hospitalized. At the end of study follow-up (median, 16 days; interquartile range, 8-28 days), 875 patients (39.5%) had died, 1203 (54.3%) were discharged, and 137 (6.2%) remained hospitalized. Factors independently associated with death included older age (≥80 vs <40 years of age: odds ratio [OR], 11.15; 95% CI, 6.19-20.06), male sex (OR, 1.50; 95% CI, 1.19-1.90), higher body mass index (≥40 vs <25: OR, 1.51; 95% CI, 1.01-2.25), coronary artery disease (OR, 1.47; 95% CI, 1.07-2.02), active cancer (OR, 2.15; 95% CI, 1.35-3.43), and the presence of hypoxemia (Pao2:Fio2<100 vs ≥300 mm Hg: OR, 2.94; 95% CI, 2.11-4.08), liver dysfunction (liver Sequential Organ Failure Assessment score of 2-4 vs 0: OR, 2.61; 95% CI, 1.30-5.25), and kidney dysfunction (renal Sequential Organ Failure Assessment score of 4 vs 0: OR, 2.43; 95% CI, 1.46-4.05) at ICU admission. Patients admitted to hospitals with fewer ICU beds had a higher risk of death (<50 vs ≥100 ICU beds: OR, 3.28; 95% CI, 2.16-4.99). Hospitals varied considerably in the risk-adjusted proportion of patients who died (range, 6.6%-80.8%) and in the percentage of patients who received hydroxychloroquine, tocilizumab, and other treatments and supportive therapies. Conclusions and Relevance: This study identified demographic, clinical, and hospital-level risk factors that may be associated with death in critically ill patients with COVID-19 and can facilitate the identification of medications and supportive therapies to improve outcomes.

Extending inferences from a randomized trial to a new target population.

When treatment effect modifiers influence the decision to participate in a randomized trial, the average treatment effect in the population represented by the randomized individuals will differ from the effect in other populations. In this tutorial, we consider methods for extending causal inferences about time-fixed treatments from a trial to a new target population of nonparticipants, using data from a completed randomized trial and baseline covariate data from a sample from the target population. We examine methods based on modeling the expectation of the outcome, the probability of participation, or both (doubly robust). We compare the methods in a simulation study and show how they can be implemented in software. We apply the methods to a randomized trial nested within a cohort of trial-eligible patients to compare coronary artery surgery plus medical therapy versus medical therapy alone for patients with chronic coronary artery disease. We conclude by discussing issues that arise when using the methods in applied analyses.

Hypothetical Lifestyle Strategies in Middle-Aged Women and the Long-Term Risk of Stroke.

Background and Purpose- Long-term effect of lifestyle changes on stroke incidence has not been estimated in randomized trials. We used observational data to estimate the incidence of stroke under hypothetical lifestyle strategies in the NHS (Nurses' Health Study). Methods- We considered 3 nondietary strategies (smoking cessation, exercising ≥30 min/d, gradual body mass index reduction if overweight/obese) and several dietary strategies (eating ≥3 servings/wk of fish, ≤3 servings/wk of unprocessed red meat, no processed red meat, ≥1 servings/d of nuts, etc). We used the parametric g-formula to estimate the 26-year risk of stroke under these strategies. Results- In 59 727 women, mean age 52 years at baseline in 1986, the estimated 26-year risks under no lifestyle interventions were 4.7% for total stroke, 2.4% for ischemic stroke, and 0.7% for hemorrhagic stroke. Under the combined nondietary interventions, the estimated 26-year risk of total stroke was 3.5% (95% CI, 2.6%-4.3%) and ischemic stroke was 1.6% (95% CI, 1.1%-2.1%). Smaller reductions in total stroke risk were estimated under isolated dietary strategies of increased intake of fish and nuts and reduced intake of unprocessed red meat. Ischemic stroke risk was lower under reduced intake of unprocessed and processed red meat, and hemorrhagic stroke risk was lower under a strategy of increased fish consumption. Conclusions- In this population of middle-aged women, sustained, lifestyle modifications were estimated to reduce the 26-year risk of total stroke by 25% and ischemic stroke by 36%. Sustained dietary modifications were estimated to reduce the 26-year risk of total stroke by 23%.

Estimates of Overall Survival in Patients With Cancer Receiving Different Treatment Regimens: Emulating Hypothetical Target Trials in the Surveillance, Epidemiology, and End Results (SEER)-Medicare Linked Database.

Importance: The Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database may provide insights into the comparative effectiveness of oncological treatments for elderly individuals who are underrepresented in clinical trials. Objective: To evaluate the suitability of SEER-Medicare data for assessing the effectiveness of adding a drug to an existing treatment regimen on the overall survival of elderly patients with cancer. Design, Setting, and Participants: This comparative effectiveness study analyzed SEER-Medicare data from 9549 individuals who received a new diagnosis of stage II colorectal cancer (2008-2012) and 940 patients who received a new diagnosis of advanced pancreatic adenocarcinoma (2007-2012), with follow-up to December 31, 2013 (SEER-Medicare data released in 2015). Two (hypothetical) target trials were designed and emulated based on 2 existing randomized clinical trials: (1) adjuvant fluorouracil after curative surgery for individuals with stage II colorectal cancer and (2) erlotinib added to gemcitabine for individuals with advanced pancreatic adenocarcinoma. Data were analyzed January 2018 to March 2019. Exposures: The following treatment strategies were compared: (1) fluorouracil initiation vs no initiation within 3 months of tumor resection and (2) erlotinib initiation vs no initiation within 12 weeks of gemcitabine initiation. Main Outcomes and Measures: All-cause mortality within 60 months of baseline for the fluorouracil trial and within 72 weeks for the erlotinib trial. Results: Compared with 3293 individuals in the existing fluorouracil trial, 9549 eligible individuals included in the present analyses were more likely to have colon cancer (8565 [90%] vs 2291 [71%]) and were older (median [interquartile range], 79 [73-84] vs 63 [56-68] years). The 5-year risk difference for initiation vs noninitiation of fluorouracil after surgery was -3.8% (95% CI, -14.8% to 12.6%), and the mortality hazard ratio (HR) was 0.95 (95% CI, 0.85-1.04). Compared with 569 individuals in the existing erlotinib trial, 940 eligible patients included in the present analysis were older (median [range], 74 [66-93] vs 64 [36-92] years) and more likely to be male (547 [58%] vs 298 [52%]). The 1-year risk difference for initiation vs noninitiation of erlotinib was 4.7% (95% CI, -9.4% to 18.0%), and the corresponding mortality HR was 1.04 (95% CI, 0.86-1.42). In naive analyses, the mortality HR estimate was 1.14 (95% CI, 0.95-1.36) for the fluorouracil emulation and 0.68 (95% CI, 0.54-0.87) for the erlotinib emulation. Conclusions and Relevance: The present estimates were similar to those from randomized clinical trials that studied adding the same cancer drugs to existing regimens. The published HR was 1.02 (95% CI, 0.70-1.48) in the fluorouracil trial for individuals aged 70 or older and 0.96 (95% CI, 0.74-1.24) in the erlotinib trial for individuals aged 65 years or older. The SEER-Medicare database may be adequate for studying the real-world effectiveness of adding a drug to treatment regimens used for elderly individuals with cancer.

Continuation of Annual Screening Mammography and Breast Cancer Mortality in Women Older Than 70 Years.

Background: Randomized trials have shown that initiating breast cancer screening between ages 50 and 69 years and continuing it for 10 years decreases breast cancer mortality. However, no trials have studied whether or when women can safely stop screening mammography. An estimated 52% of women aged 75 years or older undergo screening mammography in the United States. Objective: To estimate the effect of breast cancer screening on breast cancer mortality in Medicare beneficiaries aged 70 to 84 years. Design: Large-scale, population-based, observational study of 2 screening strategies: continuing annual mammography, and stopping screening. Setting: U.S. Medicare program, 2000 to 2008. Participants: 1 058 013 beneficiaries aged 70 to 84 years who had a life expectancy of at least 10 years, had no previous breast cancer diagnosis, and underwent screening mammography. Measurements: Eight-year breast cancer mortality, incidence, and treatments, plus the positive predictive value of screening mammography by age group. Results: In women aged 70 to 74 years, the estimated difference in 8-year risk for breast cancer death between continuing and stopping screening was -1.0 (95% CI, -2.3 to 0.1) death per 1000 women (hazard ratio, 0.78 [CI, 0.63 to 0.95]) (a negative risk difference favors continuing). In those aged 75 to 84 years, the corresponding risk difference was 0.07 (CI, -0.93 to 1.3) death per 1000 women (hazard ratio, 1.00 [CI, 0.83 to 1.19]). Limitations: The available Medicare data permit only 8 years of follow-up after screening. As with any study using observational data, the estimates could be affected by residual confounding. Conclusion: Continuing annual breast cancer screening past age 75 years did not result in substantial reductions in 8-year breast cancer mortality compared with stopping screening. Primary Funding Source: National Institutes of Health.

A causal framework for classical statistical estimands in failure-time settings with competing events.

In failure-time settings, a competing event is any event that makes it impossible for the event of interest to occur. For example, cardiovascular disease death is a competing event for prostate cancer death because an individual cannot die of prostate cancer once he has died of cardiovascular disease. Various statistical estimands have been defined as possible targets of inference in the classical competing risks literature. Many reviews have described these statistical estimands and their estimating procedures with recommendations about their use. However, this previous work has not used a formal framework for characterizing causal effects and their identifying conditions, which makes it difficult to interpret effect estimates and assess recommendations regarding analytic choices. Here we use a counterfactual framework to explicitly define each of these classical estimands. We clarify that, depending on whether competing events are defined as censoring events, contrasts of risks can define a total effect of the treatment on the event of interest or a direct effect of the treatment on the event of interest not mediated by the competing event. In contrast, regardless of whether competing events are defined as censoring events, counterfactual hazard contrasts cannot generally be interpreted as causal effects. We illustrate how identifying assumptions for all of these counterfactual estimands can be represented in causal diagrams, in which competing events are depicted as time-varying covariates. We present an application of these ideas to data from a randomized trial designed to estimate the effect of estrogen therapy on prostate cancer mortality.

Weight Gain After Smoking Cessation and Lifestyle Strategies to Reduce it.

BACKGROUND: Weight gain following smoking cessation reduces the incentive to quit, especially among women. Exercise and diet interventions may reduce postcessation weight gain, but their long-term effect has not been estimated in randomized trials. METHODS: We estimated the long-term reduction in postcessation weight gain among women under smoking cessation alone or combined with (1) moderate-to-vigorous exercise (15, 30, 45, 60 minutes/day), and (2) exercise and diet modification (≤2 servings/week of unprocessed red meat; ≥5 servings/day of fruits and vegetables; minimal sugar-sweetened beverages, sweets and desserts, potato chips or fried potatoes, and processed red meat). RESULTS: Among 10,087 eligible smokers in the Nurses' Health Study and 9,271 in the Nurses' Health Study II, the estimated 10-year mean weights under smoking cessation were 75.0 (95% CI = 74.7, 75.5) kg and 79.0 (78.2, 79.6) kg, respectively. Pooling both cohorts, the estimated postcessation mean weight gain was 4.9 (7.3, 2.6) kg lower under a hypothetical strategy of exercising at least 30 minutes/day and diet modification, and 5.9 (8.0, 3.8) kg lower under exercising at least 60 minutes/day and diet modification, compared with smoking cessation without exercising. CONCLUSIONS: In this study, substantial weight gain occurred in women after smoking cessation, but we estimate that exercise and dietary modifications could have averted most of it.

Avoidable flaws in observational analyses: an application to statins and cancer.

The increasing availability of large healthcare databases is fueling an intense debate on whether real-world data should play a role in the assessment of the benefit-risk of medical treatments. In many observational studies, for example, statin users were found to have a substantially lower risk of cancer than in meta-analyses of randomized trials. Although such discrepancies are often attributed to a lack of randomization in the observational studies, they might be explained by flaws that can be avoided by explicitly emulating a target trial (the randomized trial that would answer the question of interest). Using the electronic health records of 733,804 UK adults, we emulated a target trial of statins and cancer and compared our estimates with those obtained using previously applied analytic approaches. Over the 10-yr follow-up, 28,408 individuals developed cancer. Under the target trial approach, estimated observational analogs of intention-to-treat and per-protocol 10-yr cancer-free survival differences were -0.5% (95% confidence interval (CI) -1.0%, 0.0%) and -0.3% (95% CI -1.5%, 0.5%), respectively. By contrast, previous analytic approaches yielded estimates that appeared to be strongly protective. Our findings highlight the importance of explicitly emulating a target trial to reduce bias in the effect estimates derived from observational analyses.