Comparison of kidney and hepatic outcomes among sodium-glucose cotransporter-2 inhibitors: a retrospective study using multiple propensity scores.

BACKGROUND: Sodium-glucose cotransporter-2 inhibitors (SGLT2i) have been reported to have effects beyond lowering blood glucose levels, with certain SGLT2i expanding their indications to chronic kidney disease and chronic heart failure. We focused on the hepatoprotective and renoprotective effects of six SGLT2i and assessed whether the effects were unique to each drug or common class effects, in addition to whether the renal and hepatoprotective effects vary based on renal and hepatic status. METHODS: Patients with diabetes (ipragliflozin: 837, empagliflozin: 850, canagliflozin: 922, dapagliflozin: 590, tofogliflozin: 288, and luseogliflozin: 193) who initiated SGLT2i treatment and were monitored for one year were included. The propensity score (PS) was calculated using patient backgrounds (age, sex, height, weight, body mass index [BMI], disease duration, concomitant diabetes medications, underlying conditions, glycated hemoglobin [HbA1c], estimated glomerular filtration rate [eGFR], aspartate aminotransferase [AST], alanine aminotransferase [ALT], high-density lipoprotein [HDL], low-density lipoprotein [LDL], and triglyceride [TG] levels) as covariates. Additionally, the inverse probability of treatment weighting (IPTW) approach was used to compare liver and renal function test values. RESULTS: Pre- and 12-month post-treatment comparisons demonstrated a significant reduction in hepatic function (AST and ALT) and an increase in renal function (eCcr and eGFR) for all SGLT2i. Comparison of differences between pre- and 12-month post-treatment using the IPTW approach demonstrated no significant differences in AST, ALT, and eGFR levels between SGLT2i. At 12 months post-treatment, 67 patients were classified as having a more severe CKD than those at pre-treatment, representing only 1.8% of all patients (67/3,680). Similarly, 107 patients with AST and 147 patients with ALT were classified as having progressed to a more severe grade than at pre-treatment, representing only 2.9 and 4.0%, respectively. CONCLUSIONS: Renoprotective and hepatoprotective effects are class effects of SGLT2i, and their effects are thought to be independent of kidney or liver status.

History-restricted marginal structural model and latent class growth analysis of treatment trajectories for a time-dependent outcome.

In previous work, we introduced a framework that combines latent class growth analysis (LCGA) with marginal structural models (LCGA-MSM). LCGA-MSM first summarizes the numerous time-varying treatment patterns into a few trajectory groups and then allows for a population-level causal interpretation of the group differences. However, the LCGA-MSM framework is not suitable when the outcome is time-dependent. In this study, we propose combining a nonparametric history-restricted marginal structural model (HRMSM) with LCGA. HRMSMs can be seen as an application of standard MSMs on multiple time intervals. To the best of our knowledge, we also present the first application of HRMSMs with a time-to-event outcome. It was previously noted that HRMSMs could pose interpretation problems in survival analysis when either targeting a hazard ratio or a survival curve. We propose a causal parameter that bypasses these interpretation challenges. We consider three different estimators of the parameters: inverse probability of treatment weighting (IPTW), g-computation, and a pooled longitudinal targeted maximum likelihood estimator (pooled LTMLE). We conduct simulation studies to measure the performance of the proposed LCGA-HRMSM. For all scenarios, we obtain unbiased estimates when using either g-computation or pooled LTMLE. IPTW produced estimates with slightly larger bias in some scenarios. Overall, all approaches have good coverage of the 95 % confidence interval. We applied our approach to a population of older Quebecers composed of 57,211 statin initiators and found that a greater adherence to statins was associated with a lower combined risk of cardiovascular disease or all-cause mortality.

Survival rates in comprehensive conservative care compared to dialysis therapy in elderly end-stage kidney disease patients: a propensity score analysis.

Initiating dialysis therapy in elderly patients with end-stage kidney disease (ESKD) is a challenging decision. We aimed to examine the mortality rates among elderly patients who underwent hemodialysis, peritoneal dialysis, or comprehensive conservative care. This retrospective cohort study included elderly patients (≥70 years) with ESKD who selected their treatment options from January 2008 to December 2018. Patients were categorized into three groups: hemodialysis, peritoneal dialysis, and comprehensive conservative care. The outcome of interest was all-cause mortality analyzed using flexible parametric survival models. Propensity score analysis with inverse probability treatment weighting technique was performed, incorporating age, Charlson Comorbidity Index score, and estimated glomerular filtration rate. The study included 719 elderly ESKD patients with mean age of 78.2 ± 4.9 years, 52.3% were male, and 60.1% died during the median follow-up period of 22.1 months. In a fully adjusted model, patients receiving comprehensive conservative care (n = 50) had higher mortality rates than those receiving hemodialysis (n = 317) (adjusted hazard ratio [HR] 5.60; 95% CI 2.26-13.84, p < 0.001). However, patients who received peritoneal dialysis (n = 352) had a similar mortality rate when compared to those who received hemodialysis (adjusted HR 1.38; 95% CI 0.78-2.44, p = 0.275). The higher mortality rate in the comprehensive conservative care group remained significantly higher than in the hemodialysis group among patients aged ≥80 years (adjusted HR 4.97; 95% CI 1.32-18.80, p = 0.018). Among elderly patients (≥70 years), treatment with dialysis was associated with longer survival rates. This survival advantage persisted in patients aged ≥80 years who chose hemodialysis or peritoneal dialysis over comprehensive conservative care.

Evaluating the impact of a trial of labor after cesarean section on labor duration: a retrospective cohort study.

BACKGROUND: Cesarean section (C-section) rates are increasing globally, and repeated C-sections are associated with increased maternal morbidity. Trial of labor after C-section (TOLAC) is an approach to reduce the recurrence of C-sections. However, limited research exists on the impact of cesarean scars on labor duration in TOLAC, considering the termination of labor through C-section and selection bias. This study aimed to investigate the impact of cesarean scars on labor duration in TOLAC participants, accounting for potential confounding factors and biases. METHODS: This retrospective cohort study included 2,964 women who attempted vaginal birth at a single center in Japan from 2012 to 2021. The study categorized participants into TOLAC (n = 187) and non-TOLAC (n = 2,777) groups. Propensity scores were calculated based on 14 factors that could influence labor duration, and inverse probability of treatment weighting (IPTW) was applied. Cox proportional hazards regression analysis estimated hazard ratios (HRs) for labor duration, with and without IPTW adjustment. Sensitivity analyses used propensity score matching, bootstrapping, and interval censoring to address potential biases, including recall bias in the reported onset of labor. RESULTS: The unadjusted HR for labor duration in the TOLAC group compared to the non-TOLAC group was 0.83 (95% CI: 0.70-0.98, P = 0.027), indicating a longer labor duration in the TOLAC group. After adjusting for confounding factors using IPTW, the HR was 0.98 (95% CI: 0.74-1.30, P = 0.91), suggesting no significant difference in labor duration between the groups. Sensitivity analyses using propensity score matching, bootstrapping, and interval censoring yielded consistent results. These findings suggested that the apparent association between TOLAC and longer labor duration was because of confounding factors rather than TOLAC itself. CONCLUSIONS: After adjusting for confounding factors and addressing potential biases, cesarean scars had a limited impact on labor duration in TOLAC participants. Maternal and fetal characteristics may have a more substantial influence on labor duration.

Impact of pembrolizumab treatment duration on overall survival and prognostic factors in advanced non-small cell lung cancer: a nationwide retrospective cohort study.

Background: The efficacy of front-line pembrolizumab has been established in studies that limit treatment duration to 2 years, but decision to stop pembrolizumab after 2 years is often at physician's discretion. ATHENA is a retrospective cohort study using a comprehensive administrative database aimed firstly at exploring the optimal duration of pembrolizumab and secondly real-life prognosis factors in patients with advanced non-small cell lung cancer (NSCLC). Methods: Using the French National Health Insurance database (SNDS), we identified patients with incident lung cancer in France from 2015 to 2022. Treatments and patients' characteristics were extracted or inferred from hospital, outpatient care, pharmacy delivery reports. The duration's hazard ratio (HR) was estimated with Cox model weighted by inverse of propensity score to account for confounding. Prognostics factors in first line population were identified with Cox model selected by a LASSO procedure. Findings: 391,106 patients with lung cancer were identified, of whom 43,359 received up-front pembrolizumab for an advanced disease. There were 67% (29,040/43,359) of male and the median age at diagnosis was 65 years old. After a median follow-up time of 25.9 months (min-max, [0-97.6]), the median overall survival (OS) after pembrolizumab initiation in first line was 15.7 [CI 95, 15.3-16.0] months. In multivariable analysis, several covariables were independently associated with worse OS, including male sex with chemo-immunotherapy, age, hospital category, high deprivation index, inpatient hospitalization for first pembrolizumab, and history of diabetes, diuretic, beta blocker, painkiller prescription. At landmark time of 29 months after pembrolizumab initiation, continuation beyond 2 years was not associated with better OS than a fixed 2-year treatment, HR = 0.97 [0.75-1.26] p = 0.95. Interpretation: This study supports the notion that stopping pembrolizumab after 2 years could be safe for patients with advanced NSCLC. However, because observational studies are prone to confounding and selection bias, causality cannot be affirmed. Funding: This study did not receive any specific grant.

Influence of initial misdiagnosis on mortality in patients with bacteraemia: propensity score matching and propensity score weighting analyses.

BACKGROUND: The diagnostic process is a key element of medicine but it is complex and prone to errors. Infectious diseases are one of the three categories of diseases in which diagnostic errors can be most harmful to patients. In this study we aimed to estimate the effect of initial misdiagnosis of the source of infection in patients with bacteraemia on 14 day mortality using propensity score methods to adjust for confounding. METHODS: Data from a previously described longitudinal cohort of patients diagnosed with monobacterial bloodstream infection (BSI) at the Leiden University Medical Centre (LUMC) between 2013 and 2015 were used. Propensity score matching and inversed probability of treatment weighting (IPTW) were applied to correct for confounding. The average treatment effect on the treated (ATT), which in this study was the average effect of initial misdiagnosis on the misdiagnosed (AEMM), was estimated. Methodological issues that were encountered when applying propensity score methods were addressed by performing additional sensitivity analyses. Sensitivity analyses consisted of varying caliper in propensity score matching and using different truncated weights in inversed probability of treatment weighting. RESULTS: Data of 887 patients were included in the study. Propensity scores ranged between 0.015 and 0.999 and 80 patients (9.9%) had a propensity score > 0.95. In the matched analyses, 35 of the 171 misdiagnosed patients died within 14 days (20.5%), versus 10 of the 171 correctly diagnosed patients (5.8%), yielding a difference of 14.6% (7.6%; 21.6%). In the total group of patients, the observed percentage of patients with an incorrect initial diagnosis that died within 14 days was 19.8% while propensity score reweighting estimated that their probability of dying would have been 6.5%, if they had been correctly diagnosed (difference 13.3% (95% CI 6.9%;19.6%)). After adjustment for all variables that showed disbalance in the propensity score a difference of 13.7% (7.4%; 19.9%) was estimated. Sensitivity analyses yielded similar results. However, performing weighted analyses without truncation yielded unstable results. CONCLUSION: Thus, we observed a substantial increase of 14 day mortality in initially misdiagnosed patients. Furthermore, several patients received propensity scores extremely close to one and were almost sure to be initially misdiagnosed.

On variance estimation of the inverse probability-of-treatment weighting estimator: A tutorial for different types of propensity score weights.

Propensity score methods, such as inverse probability-of-treatment weighting (IPTW), have been increasingly used for covariate balancing in both observational studies and randomized trials, allowing the control of both systematic and chance imbalances. Approaches using IPTW are based on two steps: (i) estimation of the individual propensity scores (PS), and (ii) estimation of the treatment effect by applying PS weights. Thus, a variance estimator that accounts for both steps is crucial for correct inference. Using a variance estimator which ignores the first step leads to overestimated variance when the estimand is the average treatment effect (ATE), and to under or overestimated estimates when targeting the average treatment effect on the treated (ATT). In this article, we emphasize the importance of using an IPTW variance estimator that correctly considers the uncertainty in PS estimation. We present a comprehensive tutorial to obtain unbiased variance estimates, by proposing and applying a unifying formula for different types of PS weights (ATE, ATT, matching and overlap weights). This can be derived either via the linearization approach or M-estimation. Extensive R code is provided along with the corresponding large-sample theory. We perform simulation studies to illustrate the behavior of the estimators under different treatment and outcome prevalences and demonstrate appropriate behavior of the analytical variance estimator. We also use a reproducible analysis of observational lung cancer data as an illustrative example, estimating the effect of receiving a PET-CT scan on the receipt of surgery.

The impact of COVID-19 vaccination prior to SARS-CoV-2 infection on prevalence of long COVID among a population-based probability sample of Michiganders, 2020-2022.

PURPOSE: To estimate the association between COVID-19 vaccination status at the time of COVID-19 onset and long COVID prevalence. METHODS: We used data from the Michigan COVID-19 Recovery Surveillance Study, a population-based probability sample of adults with COVID-19 (n = 4695). We considered 30-day and 90-day long COVID (illness duration ≥30 or ≥90 days, respectively), using Poisson regression to estimate prevalence ratios (PRs) comparing vaccinated (completed an initial series ≥14 days before COVID-19 onset) to unvaccinated individuals (received 0 doses before COVID-19 onset), accounting for differences in age, sex, race and ethnicity, education, employment, health insurance, and rurality/urbanicity. The full unvaccinated comparison group was further divided into historic and concurrent comparison groups based on timing of COVID-19 onset relative to vaccine availability. We used inverse probability of treatment weights to account for sociodemographic differences between groups. RESULTS: Compared to the full unvaccinated comparison group, the adjusted prevalence of 30-day and 90-day long COVID were lower among vaccinated individuals [PR30-day= 0.57(95%CI:0.49,0.66); PR90-day= 0.42(95%CI:0.34,0.53)]. Estimates were consistent across comparison groups (full, historic, and concurrent). CONCLUSIONS: Long COVID prevalence was 40-60% lower among adults vaccinated (vs. unvaccinated) prior to their COVID-19 onset. COVID-19 vaccination may be an important tool to reduce the burden of long COVID.

Clinicopathological differences and survival benefit in ER+/PR+/HER2+ vs ER+/PR-/HER2+ breast cancer subtypes.

INTRODUCTION: Breast cancer subtypes based on estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) expression have significant implications for prognosis. HER2-positive tumors historically demonstrated poorer survival, but anti-HER2 targeted therapy improved outcomes. However, hormone receptor (HR)-positive patients may experience reduced benefit due to HER2-HR signaling crosstalk. METHODS: Data from two databases, the Shanghai Jiao Tong University Breast Cancer Data Base (SJTUBCDB) and the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) database, were analyzed. Propensity score adjustments were used to balance patient characteristics between ER+/PR+/HER2+ and ER+/PR-/HER2+ subtypes. Kaplan-Meier survival curves estimated disease-free survival (DFS), breast cancer-specific survival (BCSS), overall survival (OS) for these subtypes in the SJTUBCDB, while subgroup analyses using multivariable models were performed based on menstruation, pN stage, HER2-targeted therapy, and endocrinotherapy. RESULTS: The ER+/PR+/HER2+ group showed significantly better DFS and BCSS than the ER+/PR-/HER2+ group, particularly in postmenopausal and pN0 stage patients. Survival outcomes were similar after anti-HER2 therapy or endocrine aromatase inhibitor (AI) therapy in both groups. However, among patients receiving selective estrogen receptor modulator (SERM) treatment, those in the ER+/PR-/HER2+ group had a significantly worse prognosis compared to ER+/PR+/HER2+ patients. CONCLUSIONS: HER2-positive breast cancers with different HR statuses exhibit distinct clinicopathological features and survival outcomes. Patients in the ER+/PR+/HER2+ group generally experience better survival, particularly in postmenopausal and pN0 stage patients. Treatment strategies should consider HR status and specific modalities for better personalized management.

Evaluating hybrid controls methodology in early-phase oncology trials: A simulation study based on the MORPHEUS-UC trial.

Phase Ib/II oncology trials, despite their small sample sizes, aim to provide information for optimal internal company decision-making concerning novel drug development. Hybrid controls (a combination of the current control arm and controls from one or more sources of historical trial data [HTD]) can be used to increase statistical precision. Here we assess combining two sources of Roche HTD to construct a hybrid control in targeted therapy for decision-making via an extensive simulation study. Our simulations are based on the real data of one of the experimental arms and the control arm of the MORPHEUS-UC Phase Ib/II study and two Roche HTD for atezolizumab monotherapy. We consider potential complications such as model misspecification, unmeasured confounding, different sample sizes of current treatment groups, and heterogeneity among the three trials. We evaluate two frequentist methods (with both Cox and Weibull accelerated failure time [AFT] models) and three different commensurate priors in Bayesian dynamic borrowing (with a Weibull AFT model), and modifications within each of those, when estimating the effect of treatment on survival outcomes and measures of effect such as marginal hazard ratios. We assess the performance of these methods in different settings and the potential of generalizations to supplement decisions in early-phase oncology trials. The results show that the proposed joint frequentist methods and noninformative priors within Bayesian dynamic borrowing with no adjustment on covariates are preferred, especially when treatment effects across the three trials are heterogeneous. For generalization of hybrid control methods in such settings, we recommend more simulation studies.

Outcomes of preoperative chemotherapy for colorectal cancer with peritoneal metastasis underwent cytoreductive surgery.

BACKGROUND: This study aims to assess and compare the extent to which preoperative chemotherapy prior to CRS improves survival in patients diagnosed with CRCPM. METHODS: We included 251 patients from 2012 to 2019 in our center. Inverse probability of treatment weighting (IPTW) analysis was used to minimize the selection bias. Survival analysis was performed to compare the survival outcomes. Multivariate Cox regression analysis was conducted to identify prognostic factors. RESULT: The baseline characteristics were well balanced using IPTW (standardized mean difference < 0.1). Preoperative chemotherapy cannot significantly improve overall survival (HR, 1.03; 95% CI 0.71-1.49; P = 0.88). In subgroup analysis, we found that intestinal obstruction after preoperative chemotherapy significantly reduced survival (HR, 2.25; 95% CI 1.01-5.03; P = 0.048), while in the upfront surgery group, intestinal obstruction had no impact on prognosis. CONCLUSION: For CRCPM patients treated with CRS, preoperative chemotherapy does not seem to prolong overall survival. Furthermore, the emergence of intestinal obstruction after chemotherapy may compromise the effectiveness of treatment, resulting in a worse prognosis. This finding has important clinical implications for treatment decisions.

Adjusted win ratio using the inverse probability of treatment weighting.

The win ratio method has been increasingly applied in the design and analysis of clinical trials. However, the win ratio method is a univariate approach that does not allow for adjusting for baseline imbalances in covariates, although a stratified win ratio can be calculated when the number of strata is small. This paper proposes an adjusted win ratio to control for such imbalances by inverse probability of treatment weighting (IPTW) method. We derive the adjusted win ratio with its variance and suggest three IPTW adjustments: IPTW-average treatment effect (IPTW-ATE), stabilized IPTW-ATE (SIPTW-ATE) and IPTW-average treatment effect in the treated (IPTW-ATT). The proposed adjusted methods are applied to analyse a composite outcome in the CHARM trial. The statistical properties of the methods are assessed through simulations. Results show that adjusted win ratio methods can correct the win ratio for covariate imbalances at baseline. Simulation results show that the three proposed adjusted win ratios have similar power to detect the treatment difference and have slightly lower power than the corresponding adjusted Cox models when the assumption of proportional hazards holds true but have consistently higher power than adjusted Cox models when the proportional hazard assumption is violated.

Survival outcomes of low-risk papillary thyroid carcinoma at different risk levels: a corollary for active surveillance.

Background: This study aims to compare the outcomes of active surveillance (AS) in low-risk papillary thyroid carcinoma (PTC) patients with different tumor sizes and lymph node metastasis status, in order to establish appropriate management strategies. By analyzing these results, this study provides valuable insights for the effective management of such patients, addressing the issues and challenges associated with AS in practical clinical practice. Methods: The study utilized the SEER database supported by the National Cancer Institute of the United States, extracting data of PTC diagnosed between 2000 and 2015. Statistical analyses were conducted using inverse probability weighting (IPTW) and propensity score matching (PSM), including Kaplan-Meier survival curves and Cox regression models, to evaluate the impact of different tumor sizes and lymph node metastasis status on thyroid cancer-specific survival (TCSS). Results: A total of 57,000 PTC patients were included, with most covariates having standardized mean differences below 10% after IPTW and PSM adjustments. The TCSS of PTC with a diameter smaller than 13mm is significantly better than that of tumors with a diameter larger than 13mm, regardless of the presence of lymph node metastasis. Among PTC cases with a diameter smaller than 13mm, the TCSS of patients is similar, regardless of the presence of lymph node metastasis. However, in PTC cases with a diameter larger than 13mm, the presence of lateral neck lymph node metastasis (N1b stage) significantly impacts the TCSS, although the absolute impact on TCSS rate is minimal. Conclusion: The treatment strategy of AS is safe for patients with T1a stage papillary thyroid microcarcinoma (PTMC). However, for patients with T1b stage, if the tumor diameter exceeds 13mm or there is lymph node metastasis in the lateral neck region, the TCSS will be significantly affected. Nevertheless, the absolute impact on survival is relatively small.

The Impact of a Digital Weight Loss Intervention on Health Care Resource Utilization and Costs Compared Between Users and Nonusers With Overweight and Obesity: Retrospective Analysis Study.

BACKGROUND: The Noom Weight program is a smartphone-based weight management program that uses cognitive behavioral therapy techniques to motivate users to achieve weight loss through a comprehensive lifestyle intervention. OBJECTIVE: This retrospective database analysis aimed to evaluate the impact of Noom Weight use on health care resource utilization (HRU) and health care costs among individuals with overweight and obesity. METHODS: Electronic health record data, insurance claims data, and Noom Weight program data were used to conduct the analysis. The study included 43,047 Noom Weight users and 14,555 non-Noom Weight users aged between 18 and 80 years with a BMI of ≥25 kg/m² and residing in the United States. The index date was defined as the first day of a 3-month treatment window during which Noom Weight was used at least once per week on average. Inverse probability treatment weighting was used to balance sociodemographic covariates between the 2 cohorts. HRU and costs for inpatient visits, outpatient visits, telehealth visits, surgeries, and prescriptions were analyzed. RESULTS: Within 12 months after the index date, Noom Weight users had less inpatient costs (mean difference [MD] -US $20.10, 95% CI -US $30.08 to -US $10.12), less outpatient costs (MD -US $124.33, 95% CI -US $159.76 to -US $88.89), less overall prescription costs (MD -US $313.82, 95% CI -US $565.42 to -US $62.21), and less overall health care costs (MD -US $450.39, 95% CI -US $706.28 to -US $194.50) per user than non-Noom Weight users. In terms of HRU, Noom Weight users had fewer inpatient visits (MD -0.03, 95% CI -0.04 to -0.03), fewer outpatient visits (MD -0.78, 95% CI -0.93 to -0.62), fewer surgeries (MD -0.01, 95% CI -0.01 to 0.00), and fewer prescriptions (MD -1.39, 95% CI -1.76 to -1.03) per user than non-Noom Weight users. Among a subset of individuals with 24-month follow-up data, Noom Weight users incurred lower overall prescription costs (MD -US $1139.52, 95% CI -US $1972.21 to -US $306.83) and lower overall health care costs (MD -US $1219.06, 95% CI -US $2061.56 to -US $376.55) per user than non-Noom Weight users. The key differences were associated with reduced prescription use. CONCLUSIONS: Noom Weight use is associated with lower HRU and costs than non-Noom Weight use, with potential cost savings of up to US $1219.06 per user at 24 months after the index date. These findings suggest that Noom Weight could be a cost-effective weight management program for individuals with overweight and obesity. This study provides valuable evidence for health care providers and payers in evaluating the potential benefits of digital weight loss interventions such as Noom Weight.

The survival impact of adjuvant radiotherapy and chemotherapy in patients with non-endometrioid endometrial carcinomas: a PSM-IPTW analysis based on SEER database.

PURPOSE: To investigate outcomes of adjuvant treatments for non-endometrioid endometrial carcinomas (NEEC), as previous studies are limited by its rarity and heterogeneity. PATIENTS AND METHODS: Patients with endometrial serous carcinoma (SC), clear cell carcinoma (CCC) and carcinosarcoma were identified between 2004 and 2018 from SEER database. Propensity score matching (PSM) along with inverse probability treatment weighting (IPTW) technique were employed to balance confounding factors. Multivariate, exploratory subgroup and sensitivity analyses were conducted to evaluate the impact of adjuvant treatment on overall survival (OS) and cause-specific survival (CSS). RESULTS: The cohort comprised 5577 serous, 977 clear cell, and 959 carcinosarcomas. Combined chemotherapy and radiotherapy (CRT), chemotherapy alone, and radiotherapy alone were respectively administered in 42.21%, 47.27% and 10.58% of the whole cohort. Prior to adjusting, chemotherapy plus brachytherapy yielded the most beneficial effect among various strategies. After PSM-IPTW adjustment, CRT still demonstrated beneficial effect on OS and CSS. Subgroup analysis indicated CRT improved survival among various TNM stages, particularly with uterine carcinosarcoma. In the sensitivity analyses for serous histology, brachytherapy with or without chemotherapy appeared to benefit stage I-II patients. In stage III-IV SC patients, chemotherapy plus brachytherapy was still associated with improved survival outcomes. When nodal metastases were identified, additional external beam radiotherapy (EBRT) to CT was more utilized with survival improvement. CONCLUSION: In NEEC patients, combined CRT yielded beneficial effects than any single mode. Both chemotherapy and brachytherapy promoted survival in early stage SC patients. Late stage SC patients may benefit from chemotherapy plus either EBRT or brachytherapy.

Differences in target estimands between different propensity score-based weights.

PURPOSE: Propensity score weighting is a popular approach for estimating treatment effects using observational data. Different sets of propensity score-based weights have been proposed, including inverse probability of treatment weights whose target estimand is the average treatment effect, weights whose target estimand is the average treatment effect in the treated (ATT), and, more recently, matching weights, overlap weights, and entropy weights. These latter three sets of weights focus on estimating the effect of treatment in those subjects for whom there is clinical equipoise. We conducted a series of simulations to explore differences in the value of the target estimands for these five sets of weights when the difference in means is the measure of treatment effect. METHODS: We considered 648 scenarios defined by different values of the prevalence of treatment, the c-statistic of the propensity score model, the correlation between the linear predictors for treatment selection and the outcome, and by the magnitude of the interaction between treatment status and the linear predictor for the outcome in the absence of treatment. RESULTS: We found that, when the prevalence of treatment was low or high and the c-statistic of the propensity score model was moderate to high, that matching weights, overlap weights, and entropy weights had target estimands that differed meaningfully from the target estimand of the ATE weights. CONCLUSIONS: Researchers using matching weights, overlap weights, and entropy weights should not assume that the estimated treatment effect is comparable to the ATE.

Evaluation of outcome of chemotherapy for breast cancer patients older than 70 years: A SEER-based study.

Background: With the aging of the population, the number of elderly breast cancer cases has increased. However, there is a lack of effective randomized clinical trial data to support whether elderly patients should receive chemotherapy. Our goal was to observe the relationship between chemotherapy and breast cancer-specific survival (BCSS) in elderly breast cancer patients and to identify those who could benefit from chemotherapy. Methods: We collected the data of patients who were diagnosed with invasive ductal carcinoma and older than 70 years in the SEER database from 1995 to 2016. The independent predictors of BCSS were identified by Cox regression analysis. Propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) were performed to eliminate confounding factors. Results: A total of 142,537 patients were collected, including 21,782 patients in the chemotherapy group and 120,755 patients in the non-chemotherapy group. We identified the same potential predictors of BCSS after PSM and IPTW, such as age, race, grade, stage, therapy, subtype. A nomogram for predicting 3-year, 5-year and 10-year BCSS was constructed. The 3-year, 5-year and 10-year AUCs of the nomogram were 0.842, 0.819, and 0.788. According to the risk stratification of model predictive scores, patients in the high-risk group achieved the greatest improvement in BCSS after receiving chemotherapy. Conclusions: Our study suggests that women older than 70 years with larger tumors, higher grade, positive nodes, negative hormone receptor and inactive local therapy gain prognostic benefits from chemotherapy, but for those with low- and median-risk, conventional chemotherapy should be administered cautiously.

Posthepatectomy but not prehepatectomy chemotherapy was associated with a longer time to recurrence in patients with resectable colorectal liver metastases: Inverse probability of treatment weighting analysis.

BACKGROUND: Patients with resectable colorectal liver metastases (CLM) are treated with surgery alone, surgery and posthepatectomy chemotherapy, or prehepatectomy chemotherapy and surgery. The optimal approach in terms of survival is unclear. We compared survival in the three treatment groups using inverse probability of treatment weighting (IPTW) analysis. METHODS: Data from patients undergoing initial CLM resection in 2005-2018 were obtained from a prospectively maintained database. Our group treated resectable CLM with surgery alone but gradually adopted post- and prehepatectomy chemotherapy for patients with CLM number ≥5 after 2015. IPTW analysis was employed to adjust the characteristics of the three groups. RESULTS: Of the 439 patients meeting the inclusion criteria, 175 underwent surgery alone, 135 underwent surgery and posthepatectomy chemotherapy, and 129 underwent prehepatectomy chemotherapy and surgery. After the IPTW adjustment, the demographic and clinicopathological characteristics were well balanced. The IPTW analysis revealed that the recurrence-free survival was better in patients undergoing surgery and posthepatectomy chemotherapy than in patients undergoing surgery alone (median recurrence-free survival, 1.3 years vs 0.7 years; P = .018). Overall survival was not significantly different between the three treatment approaches. CONCLUSION: Posthepatectomy but not prehepatectomy chemotherapy prolongs the time to recurrence after curative-intent resection of CLM.

A comparison of covariate adjustment approaches under model misspecification in individually randomized trials.

Adjustment for baseline covariates in randomized trials has been shown to lead to gains in power and can protect against chance imbalances in covariates. For continuous covariates, there is a risk that the the form of the relationship between the covariate and outcome is misspecified when taking an adjusted approach. Using a simulation study focusing on individually randomized trials with small sample sizes, we explore whether a range of adjustment methods are robust to misspecification, either in the covariate-outcome relationship or through an omitted covariate-treatment interaction. Specifically, we aim to identify potential settings where G-computation, inverse probability of treatment weighting (IPTW), augmented inverse probability of treatment weighting (AIPTW) and targeted maximum likelihood estimation (TMLE) offer improvement over the commonly used analysis of covariance (ANCOVA). Our simulations show that all adjustment methods are generally robust to model misspecification if adjusting for a few covariates, sample size is 100 or larger, and there are no covariate-treatment interactions. When there is a non-linear interaction of treatment with a skewed covariate and sample size is small, all adjustment methods can suffer from bias; however, methods that allow for interactions (such as G-computation with interaction and IPTW) show improved results compared to ANCOVA. When there are a high number of covariates to adjust for, ANCOVA retains good properties while other methods suffer from under- or over-coverage. An outstanding issue for G-computation, IPTW and AIPTW in small samples is that standard errors are underestimated; they should be used with caution without the availability of small-sample corrections, development of which is needed. These findings are relevant for covariate adjustment in interim analyses of larger trials.

Factors impacting survival after transarterial radioembolization in patients with hepatocellular carcinoma: Results from the prospective CIRT study.

Background & Aims: Transarterial radioembolization (TARE) with Yttrium-90 resin microspheres is an established treatment option for patients with hepatocellular carcinoma (HCC). However, optimising treatment application and patient selection remains challenging. We report here on the effectiveness, safety and prognostic factors, including dosing methods, associated with TARE for HCC in the prospective observational CIRT study. Methods: We analysed 422 patients with HCC enrolled between Jan 2015 and Dec 2017, with follow-up visits every 3 months for up to 24 months after first TARE. Patient characteristics and treatment-related data were collected at baseline; adverse events and time-to-event data (overall survival [OS], progression-free survival [PFS] and hepatic PFS) were collected at every 3-month follow-up visit. We used the multivariable Cox proportional hazard model and propensity score matching to identify independent prognostic factors for effectiveness outcomes. Results: The median OS was 16.5 months, the median PFS was 6.1 months, and the median hepatic PFS was 6.7 months. Partition model dosimetry resulted in improved OS compared to body surface area calculations on multivariable analysis (hazard ratio 0.65; 95% CI 0.46-0.92; p = 0.0144), which was confirmed in the exact matching propensity score analysis (hazard ratio 0.56; 95% CI 0.35-0.89; p = 0.0136). Other independent prognostic factors for OS were ECOG-performance status >0 (p = 0.0018), presence of ascites (p = 0.0152), right-sided tumours (p = 0.0002), the presence of portal vein thrombosis (p = 0.0378) and main portal vein thrombosis (p = 0.0028), ALBI grade 2 (p = 0.0043) and 3 (p = 0.0014). Adverse events were recorded in 36.7% of patients, with 9.7% of patients experiencing grade 3 or higher adverse events. Conclusions: This large prospective observational dataset shows that TARE is an effective and safe treatment in patients with HCC. Using partition model dosimetry was associated with a significant improvement in survival outcomes. Impact and implications: Transarterial radioembolization (TARE) is a form of localised radiation therapy and is a potential treatment option for primary liver cancer. We observed how TARE was used in real-life clinical practice in various European countries and if any factors predict how well the treatment performs. We found that when a more complex but personalised method to calculate the applied radiation activity was used, the patient responded better than when a more generic method was used. Furthermore, we identified that general patient health, ascites and liver function can predict outcomes after TARE. Clinical trial number: NCT02305459.