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Supplementary Figure 1. Unadjusted Kaplan-Meier curve for overall survival among all CRC patients by diabetes and diabetic treatment status (n=21292). Supplementary Table S1. Diabetes treatment and overall survival among patients with diabetes, stratified by BMI. Supplementary Table S2. Diabetes treatment and overall survival among patients with diabetes, stratified by primary site

Background: Metformin has been associated with improved colorectal cancer survival, but investigations are limited by small numbers of patients and confounding by diabetic severity. We examined the association between metformin use and overall survival (OS) in patients with diabetes and colorectal cancer in a large population of U.S. veterans, while adjusting for measures of diabetic severity.Methods: Patients diagnosed with colorectal cancer from January 2001 to December 2008 were identified from the Veterans Affairs Central Cancer Registry. Multivariable models were used to examine the adjusted association of OS with diabetes and use of antidiabetic medications.Results: There were 21,352 patients diagnosed with colorectal cancer identified (n = 16,355 nondiabetic patients, n = 2,038 diabetic patients on metformin, n = 2,136 diabetic patients on medications other than metformin, n = 823 diabetic patients not on antidiabetic medication). Diabetic patients had a significantly worse OS than nondiabetic patients, but metformin users had only a 10% increase in death (HRadj 1.10; 95% CI, 1.03–1.17, P = 0.004), as compared with 22% for users of other antidiabetic medications (HRadj 1.22; 95% CI, 1.15–1.29, P < 0.0001). Among colorectal cancer patients with diabetes, metformin users had a 13% improved OS versus patients taking other antidiabetic medications (HRadj 0.87; 95% CI, 0.79–0.95, P = 0.003), while diabetic patients not on any antidiabetic medications did not differ with respect to OS (HRadj 1.02; 95% CI, 0.90–1.15, P = 0.76).Conclusions: Among diabetics with colorectal cancer, metformin use is associated with improved survival, despite adjustments for diabetes severity and other risk factors.Impact: These data lend further support to the conduct of randomized studies of possible anticancer effects of metformin among patients with colorectal cancer. Cancer Epidemiol Biomarkers Prev; 25(10); 1418–25. ©2016 AACR.

Prognostic tools, such as risk calculators, improve the patient–physician informed decision-making process. These tools are limited for breast cancer patients when assessing surgical complication risk preoperatively. In this study, we aimed to assess predictors associated with acute postoperative complications for breast cancer patients and then develop a predictive model that calculates a complication probability using patient risk factors. We performed a retrospective cohort study using the National Surgical Quality Improvement Program (NSQIP) database from 2005 to 2017. Women diagnosed with ductal carcinoma in situ or invasive breast cancer who underwent either breast conservation or mastectomy procedures were included in this predictive modeling scheme. Four models were built using logistic regression methods to predict the following composite outcomes: overall, infectious, hematologic, and internal organ complications. Model performance, accuracy and calibration measures during internal/external validation included area under the curve, Brier score, and Hosmer–Lemeshow statistic, respectively. A total of 163,613 women met the inclusion criteria. The area under the curve for each model was as follows: overall, 0.70; infectious, 0.67; hematologic, 0.84; and internal organ, 0.74. Brier scores were all between 0.04 and 0.003. Model calibration using the Hosmer–Lemeshow statistic found all p-values to be > 0.05. Using model coefficients, individualized risk can be calculated on the web-based Breast Cancer Surgery Risk Calculator (BCSRc) platform ( www.breastcalc.org ). We developed an internally and externally validated risk calculator that estimates a breast cancer patient’s unique risk of acute complications following each surgical intervention. Preoperative use of the BCSRc can potentially help stratify patients with an increased complication risk and improve expectations during the decision-making process.

Objective: To assess whether the Prediction model Risk Of Bias ASsessment Tool (PROBAST) and a shorter version of this tool can identify clinical prediction models (CPMs) that perform poorly at external validation. Study Design and Setting: We evaluated risk of bias (ROB) on 102 CPMs from the Tufts CPM Registry, comparing PROBAST to a short form consisting of six PROBAST items anticipated to best identify high ROB. We then applied the short form to all CPMs in the Registry with at least 1 validation (n = 556) and assessed the change in discrimination (dAUC) in external validation cohorts (n = 1,147). Results: PROBAST classified 98/102 CPMS as high ROB. The short form identified 96 of these 98 as high ROB (98% sensitivity), with perfect specificity. In the full CPM registry, 527 of 556 CPMs (95%) were classified as high ROB, 20 (3.6%) low ROB, and 9 (1.6%) unclear ROB. Only one model with unclear ROB was reclassified to high ROB after full PROBAST assessment of all low and unclear ROB models. Median change in discrimination was significantly smaller in low ROB models (dAUC -0.9%, IQR -6.2-4.2%) compared to high ROB models (dAUC -11.7%, IQR -33.3-2.6%; P < 0.001). Conclusion: High ROB is pervasive among published CPMs. It is associated with poor discriminative performance at validation, supporting the application of PROBAST or a shorter version in CPM reviews. (c) 2021 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license ( http:// creativecommons.org/ licenses/ by- nc- nd/ 4.0/ )

Supplemental Digital Content is available in the text., Background: There are many clinical prediction models (CPMs) available to inform treatment decisions for patients with cardiovascular disease. However, the extent to which they have been externally tested, and how well they generally perform has not been broadly evaluated. Methods: A SCOPUS citation search was run on March 22, 2017 to identify external validations of cardiovascular CPMs in the Tufts Predictive Analytics and Comparative Effectiveness CPM Registry. We assessed the extent of external validation, performance heterogeneity across databases, and explored factors associated with model performance, including a global assessment of the clinical relatedness between the derivation and validation data. Results: We identified 2030 external validations of 1382 CPMs. Eight hundred seven (58%) of the CPMs in the Registry have never been externally validated. On average, there were 1.5 validations per CPM (range, 0–94). The median external validation area under the receiver operating characteristic curve was 0.73 (25th–75th percentile [interquartile range (IQR)], 0.66–0.79), representing a median percent decrease in discrimination of −11.1% (IQR, −32.4% to +2.7%) compared with performance on derivation data. 81% (n=1333) of validations reporting area under the receiver operating characteristic curve showed discrimination below that reported in the derivation dataset. 53% (n=983) of the validations report some measure of CPM calibration. For CPMs evaluated more than once, there was typically a large range of performance. Of 1702 validations classified by relatedness, the percent change in discrimination was −3.7% (IQR, −13.2 to 3.1) for closely related validations (n=123), −9.0 (IQR, −27.6 to 3.9) for related validations (n=862), and −17.2% (IQR, −42.3 to 0) for distantly related validations (n=717; P

The liver is critically involved in drug metabolism pathways and the potential for hepatic toxicity is significant with specific cancer therapeutics. Variations in the definition of liver function thresholds that may generate heterogeneity of toxicity and efficacy outcomes across therapeutics trials in cancer require assessment. A random sample of therapeutic trials in cancer (n = 500, general category), trials using hepatotoxic drugs (abiraterone, pazopanib: n = 181), trials using drugs metabolized by the liver (doxorubicin, vincristine: n = 606), and therapeutic trials in hepatic dysfunction (n = 49) were each identified on clinicaltrials.gov. Definitions of liver function thresholds and their distribution were collated and categorized in each group. A third of all trials listed on clinicaltrials.gov across the four categories failed to provide an explicit definition of liver function. Among trials with an explicit definition, a combination of bilirubin and transaminase levels was used in 33–64%, whereas a miscellaneous combination of definitions (in the general category consisting of 11 unique liver function parameters creating 17 unique combinations) was used 29–58% of the time across the four categories of studies. The Child–Pugh or National Cancer Institute Organ Dysfunction Working Group (NCI-ODWG) criteria were rarely employed (0–12% studies). Allowance for Gilbert’s disease in bilirubin thresholds was identified in only 6–23% studies and for liver metastases in 2–15% of studies. There is a marked heterogeneity in the liver function definitions used across cancer clinical trials even when the potential for drug toxicity and altered drug metabolism is significant. Harmonization of criteria will streamline eligibility and mitigate variations in key outcomes across trials.

Existing literature on traumatic injury of the esophagus (TIE) is limited. We aimed to describe the clinical characteristics and outcomes of TIE. We reviewed the National Trauma Data Bank for the years 2010–2015. We described the demographics, characteristics, and outcomes of adult (age ≥16 years) TIE patients and also compared those factors in blunt versus penetrating TIE. The association between TIE and mortality was analyzed using multivariable logistic regression. Thousand four hundred eleven adult TIE patients were identified (37 per 100,000 trauma patients, 95% confidence intervals (CI): 35, 39). TIE patients were younger (38 vs 52 years), more likely to be male (81% vs 62%), and more severely injured (Injury Severity Score ≥ 25: 45% vs 7%) than patients without TIE (all P < 0.001). TIE was observed 16 times more frequently with penetrating injuries (257 per 100,000, 95% CI: 240, 270) than with blunt injuries (16 per 100,000, 95% CI: 15, 18). Inhospital TIE mortality was 19 per cent. TIE patients had greater risk of mortality than other trauma patients, after adjusting for age, gender, and Injury Severity Score (odds ratio = 1.4, 95% CI: 1.1, 1.7). Mortality in blunt and penetrating TIE did not differ. Although extremely rare, TIE is independently associated with a marked increase in mortality, even after adjusting for other risk factors.

ObjectiveTo assess whether the Prediction model Risk Of Bias ASsessment Tool (PROBAST) and a shorter version of this tool can identify clinical prediction models (CPMs) that perform poorly at external validation.Study Design and SettingWe evaluated risk of bias (ROB) on 102 CPMs from the Tufts CPM Registry, comparing PROBAST to a short form consisting of six PROBAST items anticipated to best identify high ROB. We then applied the short form to all CPMs in the Registry with at least 1 validation and assessed the change in discrimination (dAUC) between the derivation and the validation cohorts (n=1,147).ResultsPROBAST classified 98/102 CPMS as high ROB. The short form identified 96 of these 98 as high ROB (98% sensitivity), with perfect specificity. In the full CPM registry, 529/556 CPMs (95%) were classified as high ROB, 20 (4%) low ROB, and 7 (1%) unclear ROB. Median change in discrimination was significantly smaller in low ROB models (dAUC −0.9%, IQR −6.2%–4.2%) compared to high ROB models (dAUC −11.7%, IQR −33.3%–2.6%; pConclusionHigh ROB is pervasive among published CPMs. It is associated with poor performance at validation, supporting the application of PROBAST or a shorter version in CPM reviews.What is newHigh risk of bias is pervasive among published clinical prediction modelsHigh risk of bias identified with PROBAST is associated with poorer model performance at validationA subset of questions can distinguish between models with high and low risk of bias

Background Recent evidence suggests that there is often substantial variation in the benefits and harms across a trial population. We aimed to identify regression modeling approaches that assess heterogeneity of treatment effect within a randomized clinical trial. Methods We performed a literature review using a broad search strategy, complemented by suggestions of a technical expert panel. Results The approaches are classified into 3 categories: 1) Risk-based methods (11 papers) use only prognostic factors to define patient subgroups, relying on the mathematical dependency of the absolute risk difference on baseline risk; 2) Treatment effect modeling methods (9 papers) use both prognostic factors and treatment effect modifiers to explore characteristics that interact with the effects of therapy on a relative scale. These methods couple data-driven subgroup identification with approaches to prevent overfitting, such as penalization or use of separate data sets for subgroup identification and effect estimation. 3) Optimal treatment regime methods (12 papers) focus primarily on treatment effect modifiers to classify the trial population into those who benefit from treatment and those who do not. Finally, we also identified papers which describe model evaluation methods (4 papers). Conclusions Three classes of approaches were identified to assess heterogeneity of treatment effect. Methodological research, including both simulations and empirical evaluations, is required to compare the available methods in different settings and to derive well-informed guidance for their application in RCT analysis.

Prognostic tools, such as risk calculators, improve the patient-physician informed decision-making process. These tools are limited for breast cancer patients when assessing surgical complication risk preoperatively.In this study, we aimed to assess predictors associated with acute postoperative complications for breast cancer patients and then develop a predictive model that calculates a complication probability using patient risk factors.We performed a retrospective cohort study using the National Surgical Quality Improvement Program (NSQIP) database from 2005 to 2017. Women diagnosed with ductal carcinoma in situ or invasive breast cancer who underwent either breast conservation or mastectomy procedures were included in this predictive modeling scheme. Four models were built using logistic regression methods to predict the following composite outcomes: overall, infectious, hematologic, and internal organ complications. Model performance, accuracy and calibration measures during internal/external validation included area under the curve, Brier score, and Hosmer-Lemeshow statistic, respectively.A total of 163,613 women met the inclusion criteria. The area under the curve for each model was as follows: overall, 0.70; infectious, 0.67; hematologic, 0.84; and internal organ, 0.74. Brier scores were all between 0.04 and 0.003. Model calibration using the Hosmer-Lemeshow statistic found all p-values to be 0.05. Using model coefficients, individualized risk can be calculated on the web-based Breast Cancer Surgery Risk Calculator (BCSRc) platform ( www.breastcalc.org ).We developed an internally and externally validated risk calculator that estimates a breast cancer patient's unique risk of acute complications following each surgical intervention. Preoperative use of the BCSRc can potentially help stratify patients with an increased complication risk and improve expectations during the decision-making process.

Background Cell-mediated immunity is a specific target of several medications used to prevent or treat rejection in orthotopic heart transplantation. Low absolute lymphocyte count (ALC) has potential to be a useful and accessible clinical indicator of overall infection risk. Though some studies have demonstrated this association in other transplant populations, it has not been assessed in heart transplant recipients. Methods A single-center retrospective cohort study examined adult heart transplant recipients transplanted between 2000 and 2018. The exposure of interest was ALC ≤0.75 × 103 cells/µL at 1 month posttransplant, and the primary endpoint was a composite outcome of infection (including cytomegalovirus [CMV], herpes simplex I/II or varicella zoster virus [HSV/VZV], bloodstream infection [BSI], invasive fungal infection [IFI]) or death occurring after 1 month and before 1 year posttransplant. A multivariable Cox proportional hazards model was created to control for confounders identified using clinical judgment and statistical criteria. Results Of 375 subjects analyzed, 101 (27%) developed the composite outcome (61 CMV, 3 HSV/VZV, 19 BSI, 10 IFI, 8 deaths). Lymphopenia (ALC ≤0.75 × 103 cells/µL) at 1 month was associated with a >2-fold higher rate of the composite outcome (hazard ratio [HR], 2.26 [95% confidence interval {CI}, 1.47–3.46]; P < .001) compared to patients without lymphopenia at 1 month. After adjustment for confounding variables, the presence of lymphopenia remained statistically significantly associated with the composite outcome (HR, 1.72 [95% CI, 1.08–2.75]; P = .02). Conclusions ALC measured at 1 month after heart transplant is associated with an increased risk of infectious outcomes or death in the ensuing 11 months. This is a simple, accessible laboratory measure.

Aim: Despite broad interest in advancing personalized medicine, most evidence is currently derived from average results of clinical trials that may obscure heterogeneity of trial participants. Little is known currently about how patients view heterogeneity in trials and whether they can participate in methodological discussions about this concept. Materials & methods: In structured discussions with three focus groups involving 22 participants, we assessed how representatives of patient communities have used research to guide individual treatment decisions. Discussion themes were organized into a framework describing patient decision-making in four steps: decisions patients make in the course of care; information used to make decisions; sources for information; and quality of information. Results/conclusion: Patients prioritize information that reflects their own characteristics, preferences and values. They struggle applying clinical research to their own case.

Heterogeneity of treatment effect (HTE) refers to the nonrandom variation in the magnitude or direction of a treatment effect across levels of a covariate, as measured on a selected scale, against a clinical outcome. In randomized controlled trials (RCTs), HTE is typically examined through a subgroup analysis that contrasts effects in groups of patients defined "1 variable at a time" (for example, male vs. female or old vs. young). The authors of this statement present guidance on an alternative approach to HTE analysis, "predictive HTE analysis." The goal of predictive HTE analysis is to provide patient-centered estimates of outcome risks with versus without the intervention, taking into account all relevant patient attributes simultaneously. The PATH (Predictive Approaches to Treatment effect Heterogeneity) Statement was developed using a multidisciplinary technical expert panel, targeted literature reviews, simulations to characterize potential problems with predictive approaches, and a deliberative process engaging the expert panel. The authors distinguish 2 categories of predictive HTE approaches: a "risk-modeling" approach, wherein a multivariable model predicts the risk for an outcome and is applied to disaggregate patients within RCTs to define risk-based variation in benefit, and an "effect-modeling" approach, wherein a model is developed on RCT data by incorporating a term for treatment assignment and interactions between treatment and baseline covariates. Both approaches can be used to predict differential absolute treatment effects, the most relevant scale for clinical decision making. The authors developed 4 sets of guidance: criteria to determine when risk-modeling approaches are likely to identify clinically important HTE, methodological aspects of risk-modeling methods, considerations for translation to clinical practice, and considerations and caveats in the use of effect-modeling approaches. The PATH Statement, together with its explanation and elaboration document, may guide future analyses and reporting of RCTs.

The PATH (Predictive Approaches to Treatment effect Heterogeneity) Statement was developed to promote the conduct of, and provide guidance for, predictive analyses of heterogeneous treatment effects (HTE) in clinical trials. The goal of predictive HTE analysis is to provide patient-centered estimates of outcome risks with versus without the intervention, taking into account all relevant patient attributes simultaneously, to support more personalized clinical decision making than can be made based only on an overall average treatment effect. We distinguished two categories of predictive HTE approaches (a “risk modeling” and an “effect modeling” approach) and developed four sets of guidance statements: 1) criteria to determine when risk modeling approaches are likely to identify clinically meaningful HTE; 2) methodological aspects of risk modeling methods; 3) considerations for translation to clinical practice; and 4) considerations and caveats in the use of effect modeling approaches. We also discuss limitations of these methods and enumerate research priorities for advancing methods designed to generate more personalized evidence. This explanation and elaboration document describes the intent and rationale of each recommendation; and discusses related analytic considerations, caveats, and reservations.

Background While many clinical prediction models ( CPM s) exist to guide valvular heart disease treatment decisions, the relative performance of these CPM s is largely unknown. We systematically describe the CPM s available for patients with valvular heart disease with specific attention to performance in external validations. Methods and Results A systematic review identified 49 CPM s for patients with valvular heart disease treated with surgery (n=34), percutaneous interventions (n=12), or no intervention (n=3). There were 204 external validations of these CPM s. Only 35 (71%) CPM s have been externally validated. Sixty‐five percent (n=133) of the external validations were performed on distantly related populations. There was substantial heterogeneity in model performance and a median percentage change in discrimination of −27.1% ( interquartile range , −49.4%–−5.7%). Nearly two‐thirds of validations (n=129) demonstrate at least a 10% relative decline in discrimination. Discriminatory performance of Euro SCORE II and Society of Thoracic Surgeons (2009) models (accounting for 73% of external validations) varied widely: Euro SCORE II validation c‐statistic range 0.50 to 0.95; Society of Thoracic Surgeons (2009) Models validation c‐statistic range 0.50 to 0.86. These models performed well when tested on related populations (median related validation c‐statistics: Euro SCORE II , 0.82 [0.76, 0.85]; Society of Thoracic Surgeons [2009], 0.72 [0.67, 0.79]). There remain few (n=9) external validations of transcatheter aortic valve replacement CPM s. Conclusions Many CPM s for patients with valvular heart disease have never been externally validated and isolated external validations appear insufficient to assess the trustworthiness of predictions. For surgical valve interventions, there are existing predictive models that perform reasonably well on related populations. For transcatheter aortic valve replacement (CPM s additional external validations are needed to broadly understand the trustworthiness of predictions.

Background Foregut duplication cysts are rare congenital anomalies that require surgical intervention with approximately 10%-15% of all gastrointestinal duplication cysts originating from the esophagus. Consensus is lacking among surgeons regarding closure of the esophageal muscle layer after resection of an esophageal duplication cyst and long-term outcomes are poorly documented. Therefore, we conducted the first study comparing complication rates in patients undergoing closure versus nonclosure of the esophageal muscle layer after esophageal duplication cyst resection. Materials and methods A retrospective cohort study at Boston Children's Hospital, Massachusetts General Hospital, Brigham and Women's Hospital, and the Floating Hospital for Children at Tufts Medical Center was conducted. Patients undergoing resection of esophageal duplication cysts between 1990 and 2012 were classified according to whether the esophageal muscle layer was closed or left open. Demographic data, surgical technique, preoperative symptoms, and both short-term (

Background: Metformin has been associated with improved colorectal cancer survival, but investigations are limited by small numbers of patients and confounding by diabetic severity. We examined the association between metformin use and overall survival (OS) in patients with diabetes and colorectal cancer in a large population of U.S. veterans, while adjusting for measures of diabetic severity. Methods: Patients diagnosed with colorectal cancer from January 2001 to December 2008 were identified from the Veterans Affairs Central Cancer Registry. Multivariable models were used to examine the adjusted association of OS with diabetes and use of antidiabetic medications. Results: There were 21,352 patients diagnosed with colorectal cancer identified (n = 16,355 nondiabetic patients, n = 2,038 diabetic patients on metformin, n = 2,136 diabetic patients on medications other than metformin, n = 823 diabetic patients not on antidiabetic medication). Diabetic patients had a significantly worse OS than nondiabetic patients, but metformin users had only a 10% increase in death (HRadj 1.10; 95% CI, 1.03–1.17, P = 0.004), as compared with 22% for users of other antidiabetic medications (HRadj 1.22; 95% CI, 1.15–1.29, P < 0.0001). Among colorectal cancer patients with diabetes, metformin users had a 13% improved OS versus patients taking other antidiabetic medications (HRadj 0.87; 95% CI, 0.79–0.95, P = 0.003), while diabetic patients not on any antidiabetic medications did not differ with respect to OS (HRadj 1.02; 95% CI, 0.90–1.15, P = 0.76). Conclusions: Among diabetics with colorectal cancer, metformin use is associated with improved survival, despite adjustments for diabetes severity and other risk factors. Impact: These data lend further support to the conduct of randomized studies of possible anticancer effects of metformin among patients with colorectal cancer. Cancer Epidemiol Biomarkers Prev; 25(10); 1418–25. ©2016 AACR.

Existing literature on traumatic injury of the esophagus (TIE) is limited. We aimed to describe the clinical characteristics and outcomes of TIE. We reviewed the National Trauma Data Bank for the years 2010-2015. We described the demographics, characteristics, and outcomes of adult (age ≥16 years) TIE patients and also compared those factors in blunt

Distribution and outcomes of traumatic injury of the esophagus (TIE) in pediatric versus adult populations are unknown. Our study sought to perform a descriptive analysis of TIE in children and adults. We reviewed the National Trauma Data Bank (NTDB) for the years 2010–2015. Demographics, characteristics, and outcomes of pediatric (age

Background: Clinical prediction models (CPMs) hold the potential to improve decision-making and individualize care for patients with cardiovascular disease (CVD); however, it is increasingly recognized that CPM performance may decrease when validated externally. Here we systematically describe published external validations of CPMs for patients with CVD, with specific attention to changes in CPM performance. Methods: A systematic review was conducted using a citation search to identify external validations of CPMs in the Tufts Predictive Analytics and Comparative Effectiveness (PACE) CPM Registry, a comprehensive database of CPMs for patients with CVD published between 1990 and May 2015. Information on CPM performance in the original derivation database as well as during subsequent external validations (through March 2017) was extracted. The percent change in discrimination was calculated as [(Validation AUC - 0.5) - (Derivation AUC - 0.5) / (Derivation AUC - 0.5) * 100]. Results: The Registry includes 1083 CPMs for CVD. 1555 external validations were identified. On average there were 1.4 validations/ de novo CPM (range 0-83). 758 (70%) of the CPMs have never been externally validated. The median external validation sample size was 1215 (IQR 430, 6509) and the median number of events 59 (21, 209). 88% (1368) of the external validations report area under the receiver operating characteristic curve (AUROC). 59% (917) report some measure of CPM calibration. The median external validation AUROC was 0.74 (0.69-0.81) and the median percent change in discrimination was -14.7% (-34.1%, +0.8%). 29.3% (455) of model validations showed CPM discrimination at or above the performance reported in the derivation dataset. Conclusion: While numerous CPMs exist for patients with CVD, most have never been externally validated. CPMs generally show substantially worse discrimination in external validations compared to the derivation datasets.

Background: Current strategies for ensuring the postmarket safety of medical devices are limited by small sample size and reliance on voluntary reporting of adverse events. Prospective, active surveillance of clinical registries may provide early warnings in the postmarket evaluation of medical device safety but has not been demonstrated in national clinical data registries. Methods and Results: The CathPCI DELTA (Data Extraction and Longitudinal Trend Analysis) study was designed to assess the feasibility of prospective, active safety surveillance of medical devices within a national cardiovascular registry. We sought to assess the ability of our surveillance strategy to avoid false safety alerts by conducting an active safety surveillance study of aspiration thrombectomy catheters using data within the National Cardiovascular Data Registry CathPCI registry, where no difference in safety outcomes were anticipated for the primary in-hospital safety outcome of death and major adverse cardiovascular events (MACE). We performed a propensity-matched analysis of 5 aspiration thrombectomy catheter devices used during percutaneous coronary intervention among 95 925 patients presenting with ST-segment–elevation myocardial infarction between January 1, 2011 and September 30, 2013. After 33 months of surveillance, no safety alerts were triggered for the primary safety endpoints of death or MACE, with no between-catheter differences observed. The absolute risk of death during acute hospitalization ranged from 5.11% to 5.32% among the most commonly used aspiration thrombectomy catheter devices, with relative risks for death ranging from 0.96 to 1.03. The absolute risk of MACE ranged from 9.78% to 10.18%, with relative risks for MACE ranging from 0.99 to 1.02. There were no statistically significant differences in the rates of death or MACE between any of the aspiration thrombectomy catheter devices analyzed. Conclusions: The CathPCI DELTA study demonstrates that prospective, active safety surveillance of national clinical registries is feasible to provide near-real-time safety assessments of new medical devices.

Current guidance for evaluation of kidney function and drug dosing emphasize using measured or estimated glomerular filtration rate (GFR) rather than measured or estimated creatinine clearance or serum creatinine (Scr) alone. We assessed the definitions of kidney function thresholds for eligibility in cancer clinical trials. A random sample of active Phase I–III trials with cisplatin (n = 465) and studies in cancer with decreased kidney function (n = 74) were identified from clinicaltrials.gov. Among cisplatin trials, kidney function thresholds were defined by Scr alone or a composite of Scr or creatinine clearance in 46% (212/465) of studies. Only 2% (n = 11) used GFR. Among trials in participants with decreased kidney function, the proportion utilizing GFR (14%, 10/74) was modestly higher. Imprecise and logically inconsistent kidney function thresholds are in frequent use in clinical trials in cancer and may cause harm from either toxicity or impaired efficacy. We recommend the adoption and harmonization of recommended standards.

ObjectivesThe CathPCI Data Extraction and Longitudinal Trend Analysis study was designed to determine the feasibility of conducting prospective surveillance of a large national registry to perform comparative safety analyses of medical devices. We sought to determine whether the complementary use of retrospective case data could improve safety signal detection time.DesignWe performed a simulated surveillance study of the comparative safety of the Mynx vascular closure device (VCD) with propensity score matched alternate VCD recipients, using both retrospective and prospective cohort data.SettingCenters within the USA using the National Cardiovascular Data Registry (NCDR) CathPCI Registry.ParticipantsPercutaneous coronary intervention cases captured within the NCDR CathPCI Registry from July 1, 2009 to September 30, 2013 were included in the analysis.InterventionsNone.Main outcome measuresAbsolute and relative risk (RR) of any vascular complication (a composite of bleeding at access site, hematoma at access site, retroperitoneal bleeding, and other vascular complications requiring treatment); time to signal detection.ResultsA safety alert was detected for the primary outcome of “any vascular complication” after 15 months of surveillance and was sustained for the study duration (absolute risk of any vascular complication, 1.20% vs 0.73%, RR, 1.63; 95% CI 1.50 to 1.79; pConclusionsProspective, active surveillance of cardiovascular registries is feasible to perform comparative analyses of medical devices. Retrospective data may complement prospective surveillance to improve time to signal detection, indicating the need for earlier prospective application of safety surveillance for devices new to the market.

Background Women are still under-represented in the senior ranks of academic medicine. As local surveys represent a critical initial step in addressing the challenges of gender disparities in academic promotion within institutions, we surveyed faculty at an academic medical centre to identify factors to improve the academic advancement of women. Methods We conducted an electronic survey of all full-time faculty members in a Department of Medicine assessing academic rank and factors important in consideration for promotion. Results 106 faculty members (46 %) responded to the survey; 40 % of the respondents were women. There was a statistically significant gender gap in faculty rank (p = 0.002), with only 2 of 17 full professor positions occupied by women. Among faculty who had not yet requested promotion, women were more likely to report that they did not think an academic promotion would benefit them (69 vs. 32 % in men, p = 0.01), and to report a lack of encouragement for requesting promotion (50 vs. 29 %, p = 0.08). Conclusions Targeting the perceived value of academic promotion among women faculty, increasing junior faculty mentorship and modifying annual review processes could address gender disparities in academic medicine ranks.

OBJECTIVE: Identify inhaler use characteristics among English (ESP) and non-English speaking patients (NSP) to develop quality improvement efforts. METHODS: Outpatients were surveyed for technique confidence, education, preferences and disease control. We compared characteristics between ESP and NSP. RESULTS: Of 197 respondents, 75% were ESP, 25% were NSP. Compared to NSP, ESP responders were more likely female (57% vs 31%, p = 0.001), used inhalers for a longer time (10 vs 6 years, p=0.008) and had higher rates of metered dose inhaler use (85% vs. 60%, p

Exposure of male mice to early life stress alters the levels of specific sperm miRNAs that promote stress-associated behaviors in their offspring. To begin to evaluate whether similar phenomena occur in men, we searched for sperm miRNA changes that occur in both mice and men exposed to early life stressors that have long-lasting effects. For men, we used the Adverse Childhood Experience (ACE) questionnaire. It reveals the degree of abusive and/or dysfunctional family experiences when young, which increases risks of developing future psychological and physical disorders. For male mice, we used adolescent chronic social instability (CSI) stress, which not only enhances sociability defects for >1 year, but also anxiety and defective sociability in female offspring for multiple generations through the male lineage. Here we found a statistically significant inverse correlation between levels of multiple miRNAs of the miR-449/34 family and ACE scores of Caucasian males. Remarkably, we found members of the same sperm miRNA family are also reduced in mice exposed to CSI stress. Thus, future studies should be designed to directly test whether reduced levels of these miRNAs could be used as unbiased indicators of current and/or early life exposure to severe stress. Moreover, after mating stressed male mice, these sperm miRNA reductions persist in both early embryos through at least the morula stage and in sperm of males derived from them, suggesting these miRNA changes contribute to transmission of stress phenotypes across generations. Since offspring of men exposed to early life trauma have elevated risks for psychological disorders, these findings raise the possibility that a portion of this risk may be derived from epigenetic regulation of these sperm miRNAs.

In this chapter the basic principles of sample size calculation are discussed. The chapter also reviews the impact of sample size calculation on the study results, the parameters needed, and ways this calculation can be performed by researchers. Over- and underestimation of sample size for any study can have significant effects for the study participants, thus ensuring its adequacy is of critical importance. Setting values for alpha (level of significance) and beta (power) should be informed by the specific research goals and study hypothesis. A priori effect size estimation is challenging and can be done in various ways, which are addressed in this chapter. The chapter concludes with examples and references of sources that can be used for sample size calculation.

Introduction: Clinical prediction models (CPMs) estimate the probability of clinical outcomes and hold the potential to improve decision-making and individualize care. We aim to conduct a systematic study of published CPMs predicting mortality, functional outcome or stroke recurrence for patients with stroke. Methods: The Tufts PACE CPM Registry is based on a systematic review of cerebrovascular and cardiovascular CPMs published in English-language articles from 1/1990-3/2015, and includes 1084 unique CPMs extracted from 747 articles. CPMs predicting outcomes for patients with stroke were characterized based on index condition (hemorrhagic, ischemic or all stroke) and outcome (mortality, functional outcome or stroke recurrence). We identified the most commonly occurring covariates in models grouped by index condition-outcome pair (I-O pair). Results: Among 1084 total models in the registry, 116 (11%) predicted mortality, functional outcomes or stroke recurrence among patients with stroke. The top three most frequent models predicted functional outcomes among ischemic stroke patients (n=23), mortality among all stroke patients (n=19), and mortality among patients with hemorrhagic stroke (n=18). The median reported C statistic was 0.84 (among n=78 models reporting this measure). About half (45%) of models reported internal validations, with only 25% reporting external validations. The most commonly occurring covariates in the models were age (77%), stroke severity (51%), and functional status (26%) (see Figure). Neuroimaging findings were included relatively infrequently (21%), but were included in all 9 models predicting functional outcome among hemorrhagic stroke patients. Conclusions: There is an abundance of CPMs to predict clinically important outcomes in stroke populations. More work is needed to understand how this prognostic information might be used to improve decision making and outcomes for stroke patients.

Communication errors are considered one of the major causes of sentinel events. Our aim was to assess the process of patient handoff among junior surgical residents and to determine ways in which to improve the handoff process.We conducted nationwide surveys that included all accredited general surgery residency programs in the United States and Canada.Of the 244 American and 17 Canadian accredited surgical residency programs contacted, 65 (27%) and 12 (71%), respectively, participated in the survey. Of the American and Canadian respondents, 66% and 69%, respectively, were from postgraduate year (PGY) 1, and 32% and 29%, respectively, were from PGY 2; 85 (77%) and 50 (96%), respectively, had not received any training about patient handoff before their surgical residency, and 27% and 64%, respectively, reported that the existing handoff system at their institutions did not adequately protect patient safety. Moreover, 29% of American respondents and 37% of Canadian respondents thought that the existing handoffs did not support continuity of patient care. Of the American residents, 67% and 6% reported receiving an incomplete handoff that resulted in minor and major patient harm, respectively. These results mirrored those from Canadian residents (63% minor and 7% major harm). The most frequent factor reported to improve the patient handoff process was standardization of the verbal handoff.Our survey results indicate that the current patient handoff system contributes to patient harm. More efforts are needed to establish standardized forms of verbal and written handoff to ensure patient safety and continuity of care.Les erreurs de communication sont considérées comme l’une des causes majeures des événements sentinelles. Notre but était d’évaluer le processus de transfert des patients chez les résidents junior en chirurgie et de trouver des façons de l’améliorer.Nous avons procédé à des sondages nationaux qui ont inclus tous les programmes agréés de résidence en chirurgie générale aux États Unis et au Canada.Sur les 244 programmes agréés de résidence en chirurgie américains et les 17 canadiens, 65 (27 %) et 12 (71 %), respectivement, ont participé au sondage. Parmi les participants américains et canadiens, 66 % et 69 %, respectivement, étaient en première année de résidence (PGY 1) et 32 % et 29 %, respectivement, étaient en deuxième année de résidence (PGY 2); 85 (77 %) et 50 (96 %), respectivement, n’avaient reçu aucune formation sur le transfert des patients avant leur résidence en chirurgie et 27 % et 64 %, respectivement, ont déclaré que le système actuel de transfert de leur établissement n’assurait pas adéquatement la sécurité des patients. De plus, 29 % des participants américains et 37 % des participants canadiens ont dit estimer que le mode actuel de transfert ne favorisait pas la continuité des soins. Chez les résidents américains, 67 % et 6 % ont déclaré recevoir un rapport de transfert incomplet susceptible d’entraîner un préjudice mineur et majeur, respectivement, pour le patient. Ces réponses correspondaient à celles des résidents canadiens (63 % et 7 %, respectivement, en ce qui concerne les préjudices mineurs et majeurs). Le facteur mentionné comme le plus propice à une amélioration du processus de transfert des patients était la standardisation du rapport verbal.Les résultats de nos sondages indiquent que le système actuel de transfert des patients serait préjudiciable à ces derniers. Il faudra travailler à standardiser les processus de transfert et de rapports verbaux et écrits pour assurer la sécurité des patients et la continuité des soins.

The effect of prior malignancy on the risk of developing, and prognosis of, acute lymphoblastic leukemia (ALL) is unknown. This observational study utilized the California Cancer Registry to estimate the risk of developing ALL after a prior malignancy using standardized incidence ratios (SIRs, 95% confidence intervals). ALL occurring after a malignancy with an SIR>1 (increased-risk (IR) malignancies) was considered secondary ALL (s-ALL). Adjusted hazard ratios (aHRs, 95% confidence intervals) compared the effect of s-ALL with de novo ALL on overall survival. A total of 14 481 patients with ALL were identified (1988–2012) and 382 (3%) had a known prior malignancy. Any prior malignancy predisposed patients to developing ALL: SIR 1.62 (1.45–1.79). Hematologic malignancies (SIR 5.57, 4.38–6.98) and IR-solid tumors (SIR 2.11, 1.73–2.54) increased the risk of developing ALL. s-ALL increased the risk of death compared with de novo ALL (aHR 1.38 (1.16–1.63)) and this effect was more pronounced among younger patients (agePde novo ALL, particularly among patients