A marginal structural model for normal tissue complication probability.

The goal of radiation therapy for cancer is to deliver prescribed radiation dose to the tumor while minimizing dose to the surrounding healthy tissues. To evaluate treatment plans, the dose distribution to healthy organs is commonly summarized as dose-volume histograms (DVHs). Normal tissue complication probability (NTCP) modeling has centered around making patient-level risk predictions with features extracted from the DVHs, but few have considered adapting a causal framework to evaluate the safety of alternative treatment plans. We propose causal estimands for NTCP based on deterministic and stochastic interventions, as well as propose estimators based on marginal structural models that impose bivariable monotonicity between dose, volume, and toxicity risk. The properties of these estimators are studied through simulations, and their use is illustrated in the context of radiotherapy treatment of anal canal cancer patients.

Resilience and associated factors in orphaned and separated adolescents in Kenya: Understanding the relationship with care environment and HIV risks.

Orphans are at higher risk of HIV infection and several important HIV risk factors than non-orphans; however, this may be due to a combination of related social, psychological, and economic factors, as well as care environment, rather than orphan status alone. Understanding these complex relationships may aid policy makers in supporting evidence-based, cost-effective programming for this vulnerable population. This longitudinal study uses a causal effect model to examine, through decomposition, the relationship between care environment and HIV risk factors in orphaned and separated adolescents and youths (OSAY) in Uasin Gishu County, Kenya; considering resilience, social, peer, or family support, volunteering, or having one's material needs met as potential mediators. We analysed survey responses from 1105 OSAY age 10-26 living in Charitable Children's Institutions (CCI) (orphanages) and family-based care settings (FBS). Follow-up time was 7-36 months. Care in CCIs (vs. FBS) was associated with a decreased likelihood of engaging in forced, exchange, and consensual sex. Excess relative risks (ERR) attributable to the indirect pathway, mediation, or interaction were not significant in any model. Care environment was not statistically associated with differences in substance use. Our findings support the direct, unmediated, association between institutional care and HIV risk factors.

An interrupted time series evaluation of the effect of cannabis legalization on intentional self-harm in two Canadian provinces: Ontario and Alberta. / Évaluation, à l'aide de séries chronologiques interrompues, de l'effet de la légalisation du cannabis sur les lésions auto-infligées dans deux provinces canadiennes : Ontario et Alberta.

INTRODUCTION: Despite the association between cannabis use and higher prevalence of suicidal ideation and attempt, the effect of cannabis legalization and regulation in Canada on intentional self-harm has not been determined. METHODS: We used an interrupted time series of population-based rates of emergency department (ED) visits and hospitalizations for intentional self-harm per 100 000 in Ontario and Alberta from January/April 2010 to February 2020. Aggregate monthly counts of ED visits and hospitalizations for intentional self-harm (ICD-10 codes X60-X84, R45.8) were obtained from the National Ambulatory Care Reporting System and Discharge Abstract Database, respectively. RESULTS: The legalization and regulation of cannabis in Canada was not significantly associated with a change in rates of ED visits for intentional self-harm in Ontario (level = 0.58, 95% CI: -1.14 to 2.31; trend = -0.17, 95% CI: -0.35 to 0.01) or Alberta (level = -0.06, 95% CI: -2.25 to 2.12; trend = -0.07, 95% CI: -0.27 to 0.13). Hospitalizations for intentional self-harm also remained unchanged in Ontario (level = -0.14, 95% CI: -0.48 to 0.20; trend = 0.01, 95% CI: -0.03 to 0.04) and Alberta (level = -0.41, 95% CI: -1.03 to 0.21; trend = -0.03, 95% CI: -0.08 to 0.03). CONCLUSION: Legalization and regulation of cannabis in Canada has not increased rates of ED visits or hospitalizations for intentional self-harm in Ontario and Alberta. Individual-level analyses that account for demographic characteristics and include other provinces and territories are needed.

Surgeon-level versus hospital-level quality variance in kidney cancer surgery.

PURPOSE: To determine whether variance in kidney cancer surgery quality indicators (QIs) is most impacted by surgeon-level or hospital-level factors in order to inform quality improvement initiatives. MATERIALS AND METHODS: The ICES and Veterans Affairs (VA) databases were queried for patients undergoing surgery for localized kidney cancer. Kidney cancer surgery QIs were defined within each cohort. Quality of care was benchmarked at a surgeon- vs. hospital-level to identify statistical outliers, using available clinicopathological data to adjust for differences in case-mix. Variance between surgeons and hospitals was calculated for each QI using a random-effects model. RESULTS: The QI with the greatest amount of variance explained by hospital and surgeon-level factors was proportion of cases performed with minimally invasive surgery (MIS). The majority of this variance was due to surgeon-level factors for both the VA and ICES cohorts. The proportion of cases performed using an MIS approach was also the QI with the greatest number of outlier hospitals and surgeons compared to the average performance. The proportion of partial nephrectomies performed for patients at risk of chronic kidney disease was the QI with the greatest amount of variance due to hospital-level factors for the ICES cohort. CONCLUSIONS: The proportion of localized kidney cancer cases performed using an MIS approach is the QI requiring the greatest attention. Quality improvement initiatives should focus on surgeon-level factors to increase the number of MIS cases being performed for patients with localized renal masses.

The effect of recreational cannabis legalization on rates of traffic injury in Canada.

AIMS: To measure the impact of Canada's recreational cannabis legalization (RCL) in October 2018 and the subsequent impact of the coronavirus disease 2019 (COVID-19) lockdowns from March 2020 on rates of emergency department (ED) visits and hospitalizations for traffic injury. DESIGN: An interrupted time series analysis of rates of ED visits and hospitalizations in Canada recorded in population-based databases from January/April 2010 to March 2021. SETTING: ED visits in Ontario and Alberta and hospitalizations in Ontario, Alberta, British Columbia, the Prairies (Manitoba and Saskatchewan) and the Maritimes (Nova Scotia, New Brunswick, Newfoundland and Prince Edward Island). PARTICIPANTS: Monthly counts of presentations to the ED or hospital for motor vehicle injury or pedestrian/cyclist injury, used to calculate monthly rates per 100 000 population. MEASUREMENTS: An occurrence of one or more International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Canada (ICD-10-CA) code for motor vehicle injury (V20-V29, V40-V79, V30-V39 and V86) and pedestrian/cyclist injury (V01-V09 and V10-V19) within the National Ambulatory Care Reporting System and Discharge Abstract Database. FINDINGS: There were no statistically significant changes in rates of ED visits and hospitalizations for motor vehicle or pedestrian/cyclist injury after RCL after accounting for multiple testing. After COVID-19, there was an immediate decrease in the rate of ED visits for motor vehicle injury that was statistically significant only in Ontario (level change ß = -16.07 in Ontario, 95% CI = -20.55 to -11.60, P = 0.000; ß = -10.34 in Alberta, 95% CI = -17.80 to -2.89, P = 0.008; α of 0.004) and no changes in rates of hospitalizations. CONCLUSIONS: Canada's recreational cannabis legalization did not notably impact motor vehicle and pedestrian/cyclist injury. The rate of emergency department visits for motor vehicle injury decreased immediately after COVID-19 lockdowns, resulting in rates below post-recreational cannabis legalization levels in the year after COVID-19.

Estimation of marginal structural models under irregular visits and unmeasured confounder: calibrated inverse probability weights.

Clinical information collected in electronic health records (EHRs) is becoming an essential source to emulate randomized experiments. Since patients do not interact with the healthcare system at random, the longitudinal information in large observational databases must account for irregular visits. Moreover, we need to also account for subject-specific unmeasured confounders which may act as a common cause for treatment assignment mechanism (e.g. glucose-lowering medications) while also influencing the outcome (e.g. Hemoglobin A1c). We used the calibration of longitudinal weights to improve the finite sample properties and to account for subject-specific unmeasured confounders. A Monte Carlo simulation study is conducted to evaluate the performance of calibrated inverse probability estimators using time-dependent treatment assignment and irregular visits with subject-specific unmeasured confounders. The simulation study showed that the longitudinal weights with calibrated restrictions improved the finite sample bias when compared to the stabilized weights. The application of the calibrated weights is demonstrated using the exposure of glucose lowering medications and the longitudinal outcome of Hemoglobin A1c. Our results support the effectiveness of glucose lowering medications in reducing Hemoglobin A1c among type II diabetes patients with elevated glycemic index ([Formula: see text]) using stabilized and calibrated weights.

Emulating a Target Trial Using Primary-Care Electronic Health Records: Sodium-Glucose Cotransporter 2 Inhibitor Medications and Hemoglobin A1c.

Substantial effort has been dedicated to conducting randomized controlled experiments to generate clinical evidence for diabetes treatment. Randomized controlled experiments are the gold standard for establishing cause and effect. However, due to their high cost and time commitment, large observational databases such as those comprised of electronic health record (EHR) data collected in routine primary care may provide an alternative source with which to address such causal objectives. We used a Canadian primary-care data repository housed at the University of Toronto (Toronto, Ontario, Canada) to emulate a randomized experiment. We estimated the effectiveness of sodium-glucose cotransporter 2 inhibitor (SGLT-2i) medications for patients with diabetes using hemoglobin A1c (HbA1c) as a primary outcome and marker for glycemic control from 2018 to 2021. We assumed an intention-to-treat analysis for prescribed treatment, with analyses based on the treatment assigned rather than the treatment eventually received. We defined the causal contrast of interest as the net change in HbA1c (percent) between the group receiving the standard of care versus the group receiving SGLT-2i medication. Using a counterfactual framework, marginal structural models demonstrated a reduction in mean HbA1c level with the initiation of SGLT-2i medications. These findings provided effect sizes similar to those from earlier clinical trials on assessing the effectiveness of SGLT-2i medications.

Suboptimal oral health and the risk of cardiovascular disease in the presence of competing death: a data linkage analysis.

OBJECTIVE: The objective of this study is to simultaneously assess the associations between suboptimal oral health (SOH) and cardiovascular disease (CVD) and competing death (CD). METHODS: Ontario residents aged 40 years and over who participated in the Canadian Community Health Survey 2003 and 2007-2008 were followed until December 31, 2016 for the incidence of CVD or CD. SOH was assessed based on self-rated oral health and inability to chew. Multivariable competing risk analysis was adjusted for socioeconomic characteristics, behavioural factors and intermediate health outcomes. RESULTS: The study sample included 36,176 participants. Over a median follow-up of 9.61 years, there were 2077 CVD events and 3180 CD events. The fully adjusted models indicate 35% (HR = 1.35, 95% CI: 1.12-1.64) increase in the risk of CVD and 57% (HR = 1.57, 95% CI: 1.33-1.85) increase in the risk of CD among those who reported poor oral health as compared to those who reported excellent oral health. The fully adjusted models also indicate 11% (HR = 1.11, 95% CI: 0.97-1.27) increase in the hazard of CVD and 37% (HR = 1.37, 95% CI: 1.24-1.52) increase in the hazard of CD among those who reported inability to chew. CONCLUSION: This study provides important information to contextualize CVD risk among those with SOH. The competing risk analysis indicates that those with SOH may benefit from additional interventions to prevent CVD and CD. Accordingly, managing the risk of CVD among those with SOH should fall under a more comprehensive approach that aims at improving their overall health and well-being.

RéSUMé: OBJECTIF: L'objectif de la présente étude est d'évaluer simultanément les liens entre la santé bucco-dentaire sous-optimale et les maladies cardiovasculaires (MCV) et le décès concurrent (DC). MéTHODES: Les résidents de l'Ontario de 40 ans et plus ayant participé à l'Enquête sur la santé dans les collectivités canadiennes 2003 et 2007-2008 ont fait l'objet d'un suivi évaluant les risques de MCV ou de DC. La santé bucco-dentaire sous-optimale a fait l'objet d'une évaluation axée sur l'autoévaluation de l'état de santé bucco-dentaire et l'incapacité à mastiquer. L'analyse multivariable des risques concurrents a été adaptée aux caractéristiques socioéconomiques, aux facteurs comportementaux et aux résultats intermédiaires en matière de santé. RéSULTATS: L'échantillon à l'étude comprenait 36 176 participants. Après un suivi médian de 9,61 ans, 2 077 incidents de MCV et 3 180 DC ont été recensés. La modélisation complète indique une hausse des risques de MCV de 35 % (indice de risque (IR) = 1,35, intervalle de confiance (IC) à 95 % : 1,12-1,64) et une hausse des risques de DC de 57 % (IR = 1,57, IC à 95 % : 1,33-1,85) parmi les participants ayant signalé une piètre santé bucco-dentaire comparativement aux personnes ayant déclaré une excellente santé bucco-dentaire. La modélisation complète indique également une hausse des risques de MCV de 11 % (IR = 1,11, IC à 95 % : 0,97-1,27) et une hausse des risques de DC de 37 % (IR = 1,37, IC à 95 % : 1,24-1,52) parmi les participants ayant déclaré une incapacité à mastiquer. CONCLUSION: La présente étude fournit d'importants renseignements nous permettant de contextualiser les risques de MCV chez les personnes ayant une piètre santé bucco-dentaire. L'analyse des risques concurrents indique que les personnes ayant une santé bucco-dentaire sous-optimale pourraient bénéficier d'interventions supplémentaires afin de prévenir les MCV et les DC. Par conséquent, la gestion des risques de MCV chez les personnes ayant une santé bucco-dentaire sous-optimale devrait relever d'une approche plus globale visant à améliorer la santé et le bien-être en général.

Influence of previous experience with and beliefs regarding anal cancer screening on willingness to be screened among men living with HIV.

BACKGROUND: Implementation of anal cancer screening requires the procedure to be acceptable to the target population. Our objective was to assess the beliefs of men living with HIV regarding anal cancer screening and identify factors associated with their willingness to participate in screening. METHODS: We developed a cross-sectional questionnaire using the Theory of Planned Behavior to examine beliefs regarding prevention of human papillomavirus (HPV)-related diseases, administered to men living with HIV in 2016-2017 in a multi-site HIV clinical cohort. Correspondence analysis was used to examine the interrelationships between men's beliefs and willingness to undergo anal cancer screening. We used multivariable proportional odds models to identify factors associated with increasing willingness. Results were reported as adjusted odds ratios (aOR) with 95% confidence intervals (CI). RESULTS: Among 1677 male participants, the vast majority (90%) would be willing to undergo screening by "anal Pap test"; willingness clustered with positive beliefs (e.g. confident they can get screened; disagree that they will feel pain) in the correspondence analysis. Higher self-perceived risk for anal cancer and positive beliefs regarding screening were associated with higher willingness to be screened. Gay, bisexual and other men who have sex with men had higher willingness (aOR = 1.62; 95% CI: 1.15, 2.29) than heterosexual men. Racialized men reported lower willingness (aOR = 0.68; 95% CI: 0.54, 0.89) than white men. CONCLUSIONS: Men generally had positive beliefs and were willing to undergo screening, though there were differences by sexual orientation and racial identity. Tailored community-led initiatives could focus on men's understanding of their risk and expectations of anal cancer screening to facilitate participation.

Using scenario videos with Theatre Testing method to adapt a peer navigation model to improve street-connected youth's access to HIV care in Kenya and Canada.

Theatre testing (TT) method demonstrates whole or portions of an evidence-based intervention to stakeholders to elicit feedback on context-specific adaptations and future implementation. The Peer Navigator Project (PNP) studied the adaptation and implementation of Peer Navigators in five urban sites to increase street-connected youth (SCY) access to HIV prevention, testing, and treatment in Canada and Kenya. TT was used with SCY, healthcare providers, and community stakeholders to collect feedback on the optimal characteristics of the PNs (e.g., social identities) and their professional activities and responsibilities in each site. Sites scripted unique scenarios of PNs supporting SCY and interacting with social service providers. Local actors were employed, and the scenarios were filmed and edited into videos alongside audience discussion questions. Videos were screened to separate audiences of SCY (n = 40), healthcare providers (n = 12), and community stakeholders (n = 59). Facilitated discussion about the scenarios were recorded as data, and transcripts were analyzed thematically by the research team. The scenario videos are presented as a unique adaptation to the TT method. The adaptations were time-consuming and limited the ability to present responsive changes while presenting the method to different audiences. They were also effective at maintaining presentation fidelity and eliciting diverse and meaningful responses from different stakeholder groups. One site successfully adapted the method for use in a physically distanced manner that complied with COVID-19 public health regulations. TT using video scenarios is an engaging approach that garners rich responses from diverse stakeholder groups about the adaptation of evidence-based interventions preparing for implementation in international settings.

Targeted L1-Regularization and Joint Modeling of Neural Networks for Causal Inference.

The calculation of the Augmented Inverse Probability Weighting (AIPW) estimator of the Average Treatment Effect (ATE) is carried out in two steps, where in the first step, the treatment and outcome are modeled, and in the second step, the predictions are inserted into the AIPW estimator. The model misspecification in the first step has led researchers to utilize Machine Learning algorithms instead of parametric algorithms. However, the existence of strong confounders and/or Instrumental Variables (IVs) can lead the complex ML algorithms to provide perfect predictions for the treatment model which can violate the positivity assumption and elevate the variance of AIPW estimators. Thus the complexity of ML algorithms must be controlled to avoid perfect predictions for the treatment model while still learning the relationship between the confounders and the treatment and outcome. We use two NN architectures with an L1-regularization on specific NN parameters and investigate how their certain hyperparameters should be tuned in the presence of confounders and IVs to achieve a low bias-variance tradeoff for ATE estimators such as AIPW estimator. Through simulation results, we will provide recommendations as to how NNs can be employed for ATE estimation.

The relationships between resilience, care environment, and social-psychological factors in orphaned and separated adolescents in western Kenya.

The relationships between care environment, resilience, and social factors in orphaned and separated adolescents and youths (OSAY) in western Kenya are complex and under-studied. This study examines these relationships through the analysis of survey responses from OSAY living in Charitable Children's Institutes (CCI) and family-based care settings (FBS) in Uasin Gishu County, Kenya. The associations between 1) care environment and resilience (measured using the 14-item Resilience Scale); 2) care environment and factors thought to promote resilience (e.g. social, family, and peer support); and 3) resilience and these same resilience-promoting factors, were examined using multivariable linear and logistic regressions. This cross-sectional study included 1202 OSAY (50.4% female) aged 10-26 (mean=16; SD=3.5). The mean resilience score in CCIs was 71 (95%CI=69-73) vs. 64 (95%CI=62-66) in FBS. OSAY in CCIs had higher resilience (ß=7.67; 95%CI=5.26-10.09), social support (ß=0.26; 95%CI=0.14-0.37), and peer support (ß=0.90; 95%CI=0.64-1.17) than those in FBS. OSAY in CCIs were more likely to volunteer than those in FBS (OR=3.72; 95%CI=1.80-7.68), except in the male subgroup. Family (ß=0.42; 95%CI=0.24-0.60), social (ß=4.19; 95%CI=2.53-5.85), and peer (ß=2.13; 95%CI=1.44-2.83) relationships were positively associated with resilience in all analyses. Volunteering was positively associated with resilience (ß=5.85; 95%CI=1.51-10.19). The factor most strongly related to resilience in both fully adjusted models was peer support. This study found a strong relationship between care environment and resilience. Care environment and resilience each independently demonstrated strong relationships with peer support, social support, and participating in volunteer activities. Resilience also had a strong relationship with familial support. These data suggest that resilience can be developed through strategic supports to this vulnerable population.

Marginal Structural Models Using Calibrated Weights With SuperLearner: Application to Type II Diabetes Cohort.

As different scientific disciplines begin to converge on machine learning for causal inference, we demonstrate the application of machine learning algorithms in the context of longitudinal causal estimation using electronic health records. Our aim is to formulate a marginal structural model for estimating diabetes care provisions in which we envisioned hypothetical (i.e. counterfactual) dynamic treatment regimes using a combination of drug therapies to manage diabetes: metformin, sulfonylurea and SGLT-2i. The binary outcome of diabetes care provisions was defined using a composite measure of chronic disease prevention and screening elements [27] including (i) primary care visit, (ii) blood pressure, (iii) weight, (iv) hemoglobin A1c, (v) lipid, (vi) ACR, (vii) eGFR and (viii) statin medication. We used several statistical learning algorithms to describe causal relationships between the prescription of three common classes of diabetes medications and quality of diabetes care using the electronic health records contained in National Diabetes Repository. In particular, we generated an ensemble of statistical learning algorithms using the SuperLearner framework based on the following base learners: (i) least absolute shrinkage and selection operator, (ii) ridge regression, (iii) elastic net, (iv) random forest, (v) gradient boosting machines, and (vi) neural network. Each statistical learning algorithm was fitted using the pseudo-population generated from the marginalization of the time-dependent confounding process. Covariate balance was assessed using the longitudinal (i.e. cumulative-time product) stabilized weights with calibrated restrictions. Our results indicated that the treatment drop-in cohorts (with respect to metformin, sulfonylurea and SGLT-2i) may have improved diabetes care provisions in relation to treatment naïve (i.e. no treatment) cohort. As a clinical utility, we hope that this article will facilitate discussions around the prevention of adverse chronic outcomes associated with type II diabetes through the improvement of diabetes care provisions in primary care.

Normalized Augmented Inverse Probability Weighting with Neural Network Predictions.

The estimation of average treatment effect (ATE) as a causal parameter is carried out in two steps, where in the first step, the treatment and outcome are modeled to incorporate the potential confounders, and in the second step, the predictions are inserted into the ATE estimators such as the augmented inverse probability weighting (AIPW) estimator. Due to the concerns regarding the non-linear or unknown relationships between confounders and the treatment and outcome, there has been interest in applying non-parametric methods such as machine learning (ML) algorithms instead. Some of the literature proposes to use two separate neural networks (NNs) where there is no regularization on the network's parameters except the stochastic gradient descent (SGD) in the NN's optimization. Our simulations indicate that the AIPW estimator suffers extensively if no regularization is utilized. We propose the normalization of AIPW (referred to as nAIPW) which can be helpful in some scenarios. nAIPW, provably, has the same properties as AIPW, that is, the double-robustness and orthogonality properties. Further, if the first-step algorithms converge fast enough, under regulatory conditions, nAIPW will be asymptotically normal. We also compare the performance of AIPW and nAIPW in terms of the bias and variance when small to moderate L1 regularization is imposed on the NNs.

A Novel Metric for Hospital Quality in Kidney Cancer Surgery: A Veterans Affairs National Health System Validation of Concept.

INTRODUCTION: We aimed to develop and validate a Compound Quality Score (CQS) as a metric for hospital-level quality of surgical care in kidney cancer at the Veterans Affairs National Health System. METHODS: A retrospective review of 8,965 patients with kidney cancer treated at Veterans Affairs (2005-2015) was performed. Two previously validated process quality indicators (QIs) were explored: the proportion of patients with 1) T1a tumors undergoing partial nephrectomy and 2) T1-T2 tumors undergoing minimally invasive radical nephrectomy. Demographics/comorbidity/tumor characteristics/treatment year were used for case mix adjustments at hospital level. The predicted versus observed ratio of cases was calculated per hospital to generate QI scores using indirect standardization and multivariable regression models. CQS represents the sum of both scores. A total of 96 hospitals were grouped by CQS, and short-term patient-level outcomes were regressed on CQS levels to assess for length of stay (LOS), 30-day complications/readmission, 90-day mortality and total cost of surgical admission. RESULTS: CQS identified 25/33/38 hospitals with higher/lower/average performance, respectively. High performance hospitals had higher nephrectomy volumes (p <0.01). Total CQS independently associated with LOS (ß=-0.04, p <0.01, predicted LOS 0.84 days shorter for CQS=2 versus CQS=-2), 30-day surgical complications (OR=0.88, p <0.01) or 30-day medical complications (OR=0.93, p <0.01) and total cost of surgical admission (ß =-0.014, p <0.01, predicted 12% lower cost for CQS=2 versus CQS=-2). No association was found between CQS and 30-day readmissions or 90-day mortality (all p >0.05), although low event rates were observed (8.9% and 1.7%, respectively). CONCLUSIONS: Variability in quality of surgical care at hospital level can be captured with the CQS among patients with kidney cancer. CQS is associated with relevant short-term perioperative outcomes and surgical cost. QIs should be used to identify, audit and implement quality improvement strategies across health systems.

Textbook Outcome and Survival in Patients With Gastric Cancer: An Analysis of the Population Registry of Esophageal and Stomach Tumours in Ontario (PRESTO).

OBJECTIVE: To examine the association between Textbook Outcome (TO)-a new composite quality measurement-and long-term survival in gastric cancer surgery. BACKGROUND: Single-quality indicators do not sufficiently reflect the complex and multifaceted nature of perioperative care in patients with gastric adenocarcinoma. METHODS: All patients undergoing gastrectomy for nonmetastatic gastric adenocarcinoma registered in the Population Registry of Esophageal and Stomach Tumours of Ontario (PRESTO) between 2004 and 2015 were included. TO was defined according to negative margins; >15 lymph nodes sampled; no severe complications; no re-interventions; no unplanned ICU admission; length of stay ≤21 days; no 30-day readmission; and no 30-day mortality. Three-year survival was estimated using the Kaplan-Meier method. A marginal multivariable Cox proportional-hazards model was used to estimate the association between achieving TO metrics and long-term survival. E-value methodology was used to assess for risk of residual confounding. RESULTS: Of the 1836 patients included in this study, 402 (22%) achieved all TO metrics. TO patients had a higher 3-year survival rate compared to non-TO patients (75% vs 55%, log-rank P < 0.001). After adjustments for covariates and clustering within hospitals, TO was associated with a 41% reduction in mortality (adjusted hazards ratio 0.59, 95% confidence interval 0.48, 0.72, P < 0.001). These results were robust to potential residual confounding. CONCLUSIONS: Achieving TO is strongly associated with improved long-term survival in gastric cancer patients and merits further focus in surgical quality improvement efforts.

The association of statin subgroups with lower urinary tract symptoms following a prostate biopsy.

INTRODUCTION: This was a secondary analysis aiming to assess whether hydrophilic or hydrophobic statins have a differential effect on urinary retention (UR) and lower urinary tract symptoms (LUTS) in men following a prostate biopsy (PBx), who were at risk for prostate cancer development. METHODS: This was a population-based cohort study with data incorporated from the Institute for Clinical and Evaluative Sciences database to identify all Ontarian men aged 66 and above with a history of a single negative PBx between 1994 and 2016, with no drug prescription history of any of several putative chemo-preventative medications (statins, proton pump inhibitors, five-alpha-reductase inhibitors, and alpha-blockers). Multivariable Cox regression models with time-dependent covariates were used to assess the association of hydrophilic and hydrophobic statins with UR and LUTS within 30 days of a PBx. All models were adjusted for other known putative chemopreventive medications, age, rurality, pharmacologically treated diabetes, comorbidity score, and study inclusion year. RESULTS: Overall, 21 512 men were included, with a median followup time of 9.4 years (interquartile range [IQR] 5.4-13.4 years). Hydrophobic and hydrophilic statins were initiated by 30.7% and 19.6% of men, respectively, after the first negative PBx. UR and LUTS were experienced by 2.2% and 10% of men, respectively. Cox models demonstrated hydrophilic statins were associated with a lower risk of UR (hazard ratio [HR] 0.56, 95% confidence interval [CI] 0.38-0.83, p=0.0038) and LUTS (HR 0.86, 95% CI 0.76-0.98, p=0.022), while no such association was shown for hydrophobic statins. CONCLUSIONS: Initiation of hydrophilic statins in men older than 66 appears to be inversely associated with the risk of UR and LUTS within 30 days of a PBx.

Instrumental variable estimation of early treatment effect in randomized screening trials.

The primary analysis of randomized screening trials for cancer typically adheres to the intention-to-screen principle, measuring cancer-specific mortality reductions between screening and control arms. These mortality reductions result from a combination of the screening regimen, screening technology and the effect of the early, screening-induced, treatment. This motivates addressing these different aspects separately. Here we are interested in the causal effect of early versus delayed treatments on cancer mortality among the screening-detectable subgroup, which under certain assumptions is estimable from conventional randomized screening trial using instrumental variable type methods. To define the causal effect of interest, we formulate a simplified structural multi-state model for screening trials, based on a hypothetical intervention trial where screening detected individuals would be randomized into early versus delayed treatments. The cancer-specific mortality reductions after screening detection are quantified by a cause-specific hazard ratio. For this, we propose two estimators, based on an estimating equation and a likelihood expression. The methods extend existing instrumental variable methods for time-to-event and competing risks outcomes to time-dependent intermediate variables. Using the multi-state model as the basis of a data generating mechanism, we investigate the performance of the new estimators through simulation studies. In addition, we illustrate the proposed method in the context of CT screening for lung cancer using the US National Lung Screening Trial data.