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.

Tenofovir disoproxil fumarate and coronavirus disease 2019 outcomes in men with HIV.

OBJECTIVE: To compare the risk of coronavirus disease 2019 (COVID-19) outcomes by antiretroviral therapy (ART) regimens among men with HIV. DESIGN: We included men with HIV on ART in the Veterans Aging Cohort Study who, between February 2020 and October 2021, were 18 years or older and had adequate virological control, CD4 + cell count, and HIV viral load measured in the previous 12 months, and no previous COVID-19 diagnosis or vaccination. METHODS: We compared the adjusted risks of documented severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, COVID-19-related hospitalization, and intensive care unit (ICU) admission by baseline ART regimen: tenofovir alafenamide (TAF)/emtricitabine (FTC), tenofovir disoproxil fumarate (TDF)/FTC, abacavir (ABC)/lamivudine (3TC), and other. We fit pooled logistic regressions to estimate the 18-month risks standardized by demographic and clinical factors. RESULTS: Among 20 494 eligible individuals, the baseline characteristics were similar across regimens, except that TDF/FTC and TAF/FTC had lower prevalences of chronic kidney disease and estimated glomerular filtration rate <60 ml/min. Compared with TAF/FTC, the estimated 18-month risk ratio (95% confidence interval) of documented SARS-CoV-2 infection was 0.65 (0.43, 0.89) for TDF/FTC, 1.00 (0.85, 1.18) for ABC/3TC, and 0.87 (0.70, 1.04) for others. The corresponding risk ratios for COVID-19 hospitalization were 0.43 (0.07, 0.87), 1.09 (0.79, 1.48), and 1.21 (0.88, 1.62). The risk of COVID-19 ICU admission was lowest for TDF/FTC, but the estimates were imprecise. CONCLUSION: Our study suggests that, in men living with HIV, TDF/FTC may protect against COVID-19-related events. Randomized trials are needed to investigate the effectiveness of TDF as prophylaxis for, and early treatment of, COVID-19 in the general population.

Predicting counterfactual risks under hypothetical treatment strategies: an application to HIV.

The accuracy of a prediction algorithm depends on contextual factors that may vary across deployment settings. To address this inherent limitation of prediction, we propose an approach to counterfactual prediction based on the g-formula to predict risk across populations that differ in their distribution of treatment strategies. We apply this to predict 5-year risk of mortality among persons receiving care for HIV in the U.S. Veterans Health Administration under different hypothetical treatment strategies. First, we implement a conventional approach to develop a prediction algorithm in the observed data and show how the algorithm may fail when transported to new populations with different treatment strategies. Second, we generate counterfactual data under different treatment strategies and use it to assess the robustness of the original algorithm's performance to these differences and to develop counterfactual prediction algorithms. We discuss how estimating counterfactual risks under a particular treatment strategy is more challenging than conventional prediction as it requires the same data, methods, and unverifiable assumptions as causal inference. However, this may be required when the alternative assumption of constant treatment patterns across deployment settings is unlikely to hold and new data is not yet available to retrain the algorithm.

Hypothetical blood-pressure-lowering interventions and risk of stroke and dementia.

We aimed to study the effects of hypothetical interventions on systolic blood pressure (SBP) and smoking on risk of stroke and dementia using data from 15 years of follow-up in the Rotterdam Study. We used data from 4930 individuals, aged 55-80 years, with no prior history of stroke, dementia or cognitive impairment, followed for 15 years within the Rotterdam Study, a population-based cohort. We defined the following sustained interventions on SBP: (1) maintaining SBP below 120 mmHg, (2) maintaining SBP below 140 mmHg, (3) reducing SBP by 10% if above 140 mmHg, (4) reducing SBP by 20% if above 140 mmHg, and a combined intervention of quitting smoking with each of these SBP-lowering strategies. We considered incident stroke and incident dementia diagnoses as outcomes. We applied the parametric g-formula to adjust for baseline and time-varying confounding. The observed 15-year risk for stroke was 10.7%. Compared to no specified intervention (i.e., the "natural course"), all interventions that involved reducing SBP were associated with a stroke risk reduction of about 10% (e.g., reducing SBP by 20% if above 140 mmHg risk ratio: 0.89; 95% CI 0.76, 1). Jointly intervening on SBP and smoking status further decreased the risk of stroke (e.g., risk ratio: 0.83; 95% CI 0.71, 0.94). None of the specified interventions were associated with a substantive change in dementia risk. Our study suggests that a joint intervention on SBP and smoking cessation during later life may reduce stroke risk, while the potential for reducing dementia risk were not observed.

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.

gfoRmula: An R Package for Estimating the Effects of Sustained Treatment Strategies via the Parametric g-formula.

Researchers are often interested in estimating the causal effects of sustained treatment strategies, i.e., of (hypothetical) interventions involving time-varying treatments. When using observational data, estimating those effects requires adjustment for confounding. However, conventional regression methods cannot appropriately adjust for confounding in the presence of treatment-confounder feedback. In contrast, estimators derived from Robins's g-formula may correctly adjust for confounding even if treatment-confounder feedback exists. The package gfoRmula implements in R one such estimator: the parametric g-formula. This estimator can be used to estimate the effects of binary or continuous time-varying treatments as well as contrasts defined by static or dynamic, deterministic, or random interventions, as well as interventions that depend on the natural value of treatment. The package accommodates survival outcomes as well as binary or continuous outcomes measured at the end of follow-up. This paper describes the gfoRmula package, along with motivating background, features, and examples.

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.

Inverse probability weighted estimation of risk under representative interventions in observational studies.

Researchers are often interested in using observational data to estimate the effect on a health outcome of maintaining a continuous treatment within a pre-specified range over time; e.g. "always exercise at least 30 minutes per day". There may be many precise interventions that could achieve this range. In this paper we consider representative interventions. These are special cases of random dynamic interventions; interventions under which treatment at each time is assigned according to a random draw from a distribution that may depend on a subject's measured past. Estimators of risk under representative interventions on a time-varying treatment have previously been described based on g-estimation of structural nested cumulative failure time models. In this paper, we consider an alternative approach based on inverse probability weighting (IPW) of marginal structural models. In particular, we show that the risk under a representative intervention on a time-varying continuous treatment can be consistently estimated via computationally simple IPW methods traditionally used for deterministic static (i.e. "nonrandom" and "nondynamic") interventions for binary treatments. We present an application of IPW in this setting to estimate the 28-year risk of coronary heart disease under various representative interventions on lifestyle behaviors in the Nurses Health Study.

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.

Examining Bias in Studies of Statin Treatment and Survival in Patients With Cancer.

IMPORTANCE: Patients with cancer who use statins appear to have a substantially better survival than nonusers in observational studies. However, this inverse association between statin use and mortality may be due to selection bias and immortal-time bias. OBJECTIVE: To emulate a randomized trial of statin therapy initiation that is free of selection bias and immortal-time bias. DESIGN, SETTING, AND PARTICIPANTS: We used observational data on 17 372 patients with cancer from the Surveillance, Epidemiology, and End Results (SEER)-Medicare database (2007-2009) with complete follow-up until 2011. The SEER-Medicare database links 17 US cancer registries and claims files from Medicare and Medicaid in 12 US states. We included individuals with a new diagnosis of colorectal, breast, prostate, or bladder cancer who had not been prescribed statins for at least 6 months before the cancer diagnosis. Individuals were duplicated, and each replicate was assigned to either the strategy "statin therapy initiation within 6 months after diagnosis" or "no statin therapy initiation." Replicates were censored when they stopped following their assigned strategy, and the potential selection bias was adjusted for via inverse-probability weighting. Hazard ratios (HRs), cumulative incidences, and risk differences were calculated for all-cause mortality and cancer-specific mortality. We then compared our estimates with those obtained using the same analytic approaches used in previous observational studies. EXPOSURES: Statin therapy initiation within 6 months after cancer diagnosis. MAIN OUTCOMES AND MEASURES: Cancer-specific and all-cause mortality using SEER-Medicare data and data from previous studies. RESULTS: Of the 17 372 patients whose data were analyzed, 8440 (49%) were men, and 8932 (51%) were women (mean [SD] age, 76.4 [7.4] years; range, 66-115 years). The adjusted HR (95% CI) comparing statin therapy initiation vs no initiation was 1.00 (0.88-1.15) for cancer-specific mortality and 1.07 (0.93-1.21) for overall mortality. Cumulative incidence curves for both groups were almost overlapping (the risk difference never exceeded 0.8%). In contrast, the methods used by prior studies resulted in an inverse association between statin use and mortality (pooled hazard ratio 0.69). CONCLUSION AND RELEVANCE: After using methods that are not susceptible to selection bias from prevalent users and to immortal time bias, we found that initiation of therapy with statins within 6 months after cancer diagnosis did not appear to improve 3-year cancer-specific or overall survival.

Electronic medical records can be used to emulate target trials of sustained treatment strategies.

OBJECTIVE: To emulate three target trials: single treatment vs. no treatment, joint treatment vs. no treatment, and head-to-head comparison of two treatments, we explain how to estimate the observational analogs of intention-to-treat and per-protocol effects, using hazard ratios and survival curves. For per-protocol effects, we describe two methods for adherence adjustment via inverse-probability weighting. STUDY DESIGN AND SETTING: Prospective observational study using electronic medical records of individuals aged 55-84 with coronary heart disease from >500 practices in the United Kingdom between 2000 and 2010. RESULTS: The intention-to-treat mortality hazard ratio (95% confidence interval) was 0.90 (0.84, 0.97) for statins vs. no treatment, 0.88 (0.73, 1.06) for statins plus antihypertensives vs. no treatment, and 0.91 (0.77, 1.06) for atorvastatin vs. simvastatin. When censoring nonadherent person-times, the per-protocol mortality hazard ratio was 0.74 (0.64, 0.85) for statins vs. no treatment, 0.55 (0.35, 0.87) for statins plus antihypertensives vs. no treatment, and 1.13 (0.88, 1.45) for atorvastatin vs. simvastatin. We estimated per-protocol hazard ratios for a 5-year treatment using different dose-response marginal structural models and standardized survival curves for each target trial using intention-to-treat and per-protocol analyses. CONCLUSION: When randomized trials are not available or feasible, observational analyses can emulate a variety of target trials.

Infective endocarditis and cancer in the elderly.

Little is known about the magnitude of the association between infective endocarditis and cancer, and about the natural history of cancer patients with concomitant diagnosis of infective endocarditis. We used the SEER-Medicare linked database to identify individuals aged 65 years or more diagnosed with colorectal, lung, breast, or prostate cancer, and without any cancer diagnosis (5% random Medicare sample from SEER areas) between 1992 and 2009. We identified infective endocarditis from the ICD-9 diagnosis of each admission recorded in the Medpar file and its incidence rate 90 days around cancer diagnosis. We also estimated the overall survival and CRC-specific survival after a concomitant diagnosis of infective endocarditis. The peri-diagnostic incidence of infective endocarditis was 19.8 cases per 100,000 person-months for CRC, 5.7 cases per 100,000 person-months for lung cancer, 1.9 cases per 100,000 person-months for breast cancer, 4.1 cases per 100,000 person-months for prostate cancer and 2.4 cases per 100,000 person-months for individuals without cancer. Two-year overall survival was 46.4% (95% CI 39.5, 54.5%) for stage I-III CRC patients with concomitant endocarditis and 73.1% (95 % CI 72.9, 73.3%) for those without it. In this elderly population, the incidence of infective endocarditis around CRC diagnosis was substantially higher than around the diagnosis of lung, breast and prostate cancers. A concomitant diagnosis of infective endocarditis in patients with CRC diagnosis is associated with shorter survival.

Ensemble learning of inverse probability weights for marginal structural modeling in large observational datasets.

Inverse probability weights used to fit marginal structural models are typically estimated using logistic regression. However, a data-adaptive procedure may be able to better exploit information available in measured covariates. By combining predictions from multiple algorithms, ensemble learning offers an alternative to logistic regression modeling to further reduce bias in estimated marginal structural model parameters. We describe the application of two ensemble learning approaches to estimating stabilized weights: super learning (SL), an ensemble machine learning approach that relies on V-fold cross validation, and an ensemble learner (EL) that creates a single partition of the data into training and validation sets. Longitudinal data from two multicenter cohort studies in Spain (CoRIS and CoRIS-MD) were analyzed to estimate the mortality hazard ratio for initiation versus no initiation of combined antiretroviral therapy among HIV positive subjects. Both ensemble approaches produced hazard ratio estimates further away from the null, and with tighter confidence intervals, than logistic regression modeling. Computation time for EL was less than half that of SL. We conclude that ensemble learning using a library of diverse candidate algorithms offers an alternative to parametric modeling of inverse probability weights when fitting marginal structural models. With large datasets, EL provides a rich search over the solution space in less time than SL with comparable results.

Evaluation of the duplication of staging CT scans for localized colon cancer in a Medicare population.

BACKGROUND: To quantify and characterize duplicated tests performed during the staging of localized colon cancer in the Medicare population. METHODS: We used the SEER-Medicare linked database to select patients diagnosed with localized colon cancer between the years 1996 and 2009. We considered a patient as adequately staged after having received a colonoscopy, an abdominal computed tomography (CT) scan, and a pelvic CT scan. Abdominal and pelvic CT scans performed between complete staging and first cancer-directed treatment, if not ordered due to an acute condition, were considered duplicates. We characterized the institutions providing the tests and evaluated the association with survival using a weighted pooled logistic regression adjusted by baseline and time-varying confounders. RESULTS: Of 36,291 patients with a complete staging, 2680 (7.4%) had at least 1 duplicated test. Patients receiving a duplicate had a higher comorbidity score, were more symptomatic, and had more visits to the emergency department and clinical evaluations. They also were treated with surgery less frequently and had worse survival (hazard ratio 1.22, 95% confidence interval, 1.16-1.28). The type of institution involved in the staging (nonprofit/government centers, proprietary centers, free-standing facilities) was not associated with receiving duplicated tests. CONCLUSIONS: We found a low frequency of duplicated abdominal or pelvic CT scans in the staging of colon cancer in the Medicare population.