Restricted Mean Survival Time Research Articles

All-cause mortality and suicide after pediatric traumatic brain injury: a 20-year nationwide study in Finland

ObjectivesTo assess all-cause mortality and suicides after pediatric traumatic brain injury (pTBI). Study designWe conducted population-based historical cohort study using three nationwide registers from 1998 to 2018 in Finland. All patients that were the age of 0–17 at the time of the pTBI were included. The reference group consisted of children with ankle or wrist fractures. We used Kaplan–Meier and restricted mean survival time (RMST) analysis with 95% confidence intervals (CI) to compare all-cause mortality and suicides between groups. ResultsAfter 20 years of follow-up, there were 479 deaths in the pTBI group (0.67% of 71,963) and 306 deaths in the reference group (0.47% of 64,848). In the pTBI group, 28.6% of the deaths occurred after the first follow-up year, compared to 2.6% in the reference group. In all-cause mortality, survival time was slightly less in the pTBI group with age and gender adjustment throughout the follow-up period [20-year RMST ratio: 0.995; CI (0.994–0.996)]. The leading manners of death were suicides (pTBI group = 28.4%; reference group = 45.5%) and traffic collisions (pTBI group = 37.4%; reference group = 20.8%). Age and gender-adjusted survival time was slightly less for those with suicide as a manner of death in the pTBI group [10-year RMST ratio: 0.999; CI (0.999–0.999); 20-year RMST ratio: 0.999; CI (0.998–0.999)]. ConclusionsChildren and adolescents who sustained a TBI have slightly lower long-term survival time for all-cause mortality, most of which occurs during the first year following injury. There is no clinically meaningful difference in deaths by suicide between the two injury groups.

Remote monitoring of automated peritoneal dialysis reduces mortality, adverse events, and hospitalizations: a cluster randomized controlled trial.

Remote monitoring (RM) of patients on automated peritoneal dialysis (APD) prevent complications and improve treatment quality. We analyzed the effect of RM-APD on mortality and complications related to cardiovascular disease (VD), fluid overload and insufficient dialysis efficiency. In a cluster-randomized, open-label, controlled trial, 21 hospitals with APD programs were assigned to use either RM-APD (10 hospitals; 403 patients) or conventional APD (11 hospitals; 398 patients) for the treatment of adult patients starting PD. Primary outcomes were time to first event of: 1) Composite Index-1 comprising all-cause mortality, first adverse events and hospitalizations of any cause, and 2) Composite Index-2 comprising cardiovascular mortality, first adverse event and hospitalizations related to CVD, fluid overload and insufficient dialysis efficiency. Secondary outcomes were time to first event of individual components of the two composite indices, and rates of adverse events, hospitalizations, unplanned visits, and transfer to hemodialysis. Patients were followed for a median of 9.5 months. Primary outcomes were evaluated by competing-risk analysis and restricted mean survival time (RMST) analysis. While time to reach Composite Index-1 did not differ between the groups, Composite Index-2 was reached earlier (ΔRMST: -0.85 months; p=0.02), and all-cause mortality (55 vs. 33 deaths, p=0.01; sHR 1.69 (95%CI 1.39-2.05), p<0.001) and hospitalizations of any cause were higher in APD group than in RM-APD as were cardiovascular deaths (24 vs. 13 deaths, p=0.05; sHR 2.44 (95%CI 1.72 - 3.45), p<0.001) and rates of adverse events and hospitalizations related to CVD, fluid overload or insufficient dialysis efficiency. Dropouts were more common in the APD group (131 vs. 110, p=0.048). This randomized controlled trial shows that remote monitoring may add significant advantages to APD, including improved survival and reduced rate of adverse events and hospitalizations, which can favorably impact the acceptance and adoption of the therapy.

Utilizing machine learning to tailor radiotherapy and chemoradiotherapy for low-grade glioma patients.

There is ongoing uncertainty about the effectiveness of various adjuvant treatments for low-grade gliomas (LGGs). Machine learning (ML) models that predict individual treatment effects (ITE) and provide treatment recommendations could help tailor treatments to each patient's needs. We sought to discern the individual suitability of radiotherapy (RT) or chemoradiotherapy (CRT) in LGG patients using ML models. Ten ML models, trained to infer ITE in 4,042 LGG patients, were assessed. We compared patients who followed treatment recommendations provided by the models with those who did not. To mitigate the risk of treatment selection bias, we employed inverse probability treatment weighting (IPTW). The Balanced Survival Lasso-Network (BSL) model showed the most significant protective effect among all the models we tested (hazard ratio (HR): 0.52, 95% CI, 0.41-0.64; IPTW-adjusted HR: 0.58, 95% CI, 0.45-0.74; the difference in restricted mean survival time (DRMST): 9.11, 95% CI, 6.19-12.03; IPTW-adjusted DRMST: 9.17, 95% CI, 6.30-11.83). CRT presented a protective effect in the 'recommend for CRT' group (IPTW-adjusted HR: 0.60, 95% CI, 0.39-0.93) yet presented an adverse effect in the 'recommend for RT' group (IPTW-adjusted HR: 1.64, 95% CI, 1.19-2.25). Moreover, the models predict that younger patients and patients with overlapping lesions or tumors crossing the midline are better suited for CRT (HR: 0.62, 95% CI, 0.42-0.91; IPTW-adjusted HR: 0.59, 95% CI, 0.36-0.97). Our findings underscore the potential of the BSL model in guiding the choice of adjuvant treatment for LGGs patients, potentially improving survival time. This study emphasizes the importance of ML in customizing patient care, understanding the nuances of treatment selection, and advancing personalized medicine.

Semiparametric Additive Modeling of the Restricted Mean Survival Time.

Analysis of the restricted mean survival time (RMST) has become increasingly common in biomedical studies during the last decade as a means of estimating treatment or covariate effects on survival. Advantages of RMST over the hazard ratio (HR) include increased interpretability and lack of reliance on the often tenuous proportional hazards assumption. Some authors have argued that RMST regression should generally be the frontline analysis as opposed to methods based on counting process increments. However, in order for the use of the RMST to be more mainstream, it is necessary to broaden the range of data structures to which pertinent methods can be applied. In this report, we address this issue from two angles. First, most of existing methodological development for directly modeling RMST has focused on multiplicative models. An additive model may be preferred due to goodness of fit and/or parameter interpretation. Second, many settings encountered nowadays feature high-dimensional categorical (nuisance) covariates, for which parameter estimation is best avoided. Motivated by these considerations, we propose stratified additive models for direct RMST analysis. The proposed methods feature additive covariate effects. Moreover, nuisance factors can be factored out of the estimation, akin to stratification in Cox regression, such that focus can be appropriately awarded to the parameters of chief interest. Large-sample properties of the proposed estimators are derived, and a simulation study is performed to assess finite-sample performance. In addition, we provide techniques for evaluating a fitted model with respect to risk discrimination and predictive accuracy. The proposed methods are then applied to liver transplant data to estimate the effects of donor characteristics on posttransplant survivaltime.

Comparison of clinical and MRI features of hepatic angiosarcoma and epithelioid hemangioendothelioma.

Differentiating hepatic epithelioid hemangioendothelioma (EHE) and angiosarcoma (AS), the two most common vascular tumors in the liver, is important due to disparities in their prognosis and treatment. We aimed to compare clinical and MRI features of the two tumors. This retrospective study included patients with pathologically-confirmed AS or EHE who underwent MRI using gadoxetate disodium between 2008 and 2023. Two radiologists independently reviewed MR images. Wilcoxon rank sum and Fisher's exact tests were used to compare clinical and imaging features. Overall survival was compared using restricted mean survival time at 3years. 32 patients with AS (18 women [56.3%]; median age, 68years) and 38 with EHE (24 women [63.2%]; 51years) were included. Patients with AS were generally older (81.3% ≥ 60years; P < 0.001), had more frequent laboratory abnormalities (P ≤ 0.018), and poorer overall survival (11.2 vs. 31.8months; P < 0.001) than those with EHE. On MRI, a large dominant mass accompanied by smaller nodules (14/32, 43.8%), often with ill-defined margins (15/32, 46.9%) was prevalent in AS; compared with nodules of similar sizes (24/38, 63.2%; P = 0.015) with well-defined margin (30/38, 78.9%; P = 0.002) in EHE. Cirrhotic appearance of the liver was more frequent in AS (62.5%, P < 0.001), along with decreased parenchymal enhancement on hepatobiliary phase (31.3%, P < 0.001) and ascites (37.5%, P = 0.010). AS frequently presented with avid enhancement of bizarrely-shaped foci, with a centrifugal enhancement pattern. In comparison, targetoid appearance was characteristic of EHE (78.9% on T2-weighted, 54.1% on diffusion-weighted, 65.8% on multiphase images) (P ≤ 0.002), with enhancement degree typically lower than that of the aorta. On hepatobiliary phase, all the AS exhibited hypointensity, while 39.5% of EHE showed targetoid appearance (P < 0.001). Patients aged ≥ 60years presenting with laboratory abnormalities, typically with a large dominant mass accompanied by smaller nodules, exhibiting avid, bizarre, and centrifugal enhancement-particularly in the cirrhotic-appearing liver-suggests the likelihood of AS over EHE.

Proportional Hazards Violations in Phase III Cancer Clinical Trials: A Potential Source of Trial Misinterpretation.

Survival analyses of novel agents with long-term responders often exhibit differential hazard rates over time. Such proportional hazards violations (PHV) may reduce the power of the log-rank test and lead to misinterpretation of trial results. We aimed to characterize the incidence and study attributes associated with PHVs in phase III oncology trials and assess the utility of restricted mean survival time and maximum combination test as additional analyses. Clinicaltrials.gov and PubMed were searched to identify two-arm, randomized, phase III superiority-design cancer trials with time-to-event primary endpoints and published results through 2020. Patient-level data were reconstructed from published Kaplan-Meier curves. PHVs were assessed using Schoenfeld residuals. Three hundred fifty-seven Kaplan-Meier comparisons across 341 trials were analyzed, encompassing 292,831 enrolled patients. PHVs were identified in 85/357 [23.8%; 95% confidence interval (CI), 19.7%, 28.5%] comparisons. In multivariable analysis, non-overall survival endpoints [OR, 2.16 (95% CI, 1.21, 3.87); P = 0.009] were associated with higher odds of PHVs, and immunotherapy comparisons [OR 1.94 (95% CI, 0.98, 3.86); P = 0.058] were weakly suggestive of higher odds of PHVs. Few trials with PHVs (25/85, 29.4%) prespecified a statistical plan to account for PHVs. Fourteen trials with PHVs exhibited discordant statistical signals with restricted mean survival time or maximum combination test, of which 10 (71%) reported negative results. PHVs are common across therapy types, and attempts to account for PHVs in statistical design are lacking despite the potential for results exhibiting nonproportional hazards to be misinterpreted.

Revisiting diabetes risk of olanzapine versus aripiprazole in serious mental illness care.

Exposure to second-generation antipsychotics (SGAs) carries a risk of type 2 diabetes, but questions remain about the diabetogenic effects of SGAs. To assess the diabetes risk associated with two frequently used SGAs. This was a retrospective cohort study of adults with schizophrenia, bipolar I disorder or severe major depressive disorder (MDD) exposed during 2008-2013 to continuous monotherapy with aripiprazole or olanzapine for up to 24 months, with no pre-period exposure to other antipsychotics. Newly diagnosed type 2 diabetes was quantified with targeted minimum loss-based estimation; risk was summarised as the restricted mean survival time (RMST), the average number of diabetes-free months. Sensitivity analyses were used to evaluate potential confounding by indication. Aripiprazole-treated patients had fewer diabetes-free months compared with olanzapine-treated patients. RMSTs were longer in olanzapine-treated patients, by 0.25 months [95% CI: 0.14, 0.36], 0.16 months [0.02, 0.31] and 0.22 months [0.01, 0.44] among patients with schizophrenia, bipolar I disorder and severe MDD, respectively. Although some sensitivity analyses suggest a risk of unobserved confounding, E-values indicate that this risk is not severe. Using robust methods and accounting for exposure duration effects, we found a slightly higher risk of type 2 diabetes associated with aripiprazole compared with olanzapine monotherapy regardless of diagnosis. If this result was subject to unmeasured selection despite our methods, it would suggest clinician success in identifying olanzapine candidates with low diabetes risk. Confirmatory research is needed, but this insight suggests a potentially larger role for olanzapine in the treatment of well-selected patients, particularly for those with schizophrenia, given the drug's effectiveness advantage among them.

Inference for restricted mean survival time as a function of restriction time under length-biased sampling.

The restricted mean survival time (RMST) is often of direct interest in clinical studies involving censored survival outcomes. It describes the area under the survival curve from time zero to a specified time point. When data are subject to length-biased sampling, as is frequently encountered in observational cohort studies, existing methods cannot estimate the RMST for various restriction times through a single model. In this article, we model the RMST as a continuous function of the restriction time under the setting of length-biased sampling. Two approaches based on estimating equations are proposed to estimate the time-varying effects of covariates. Finally, we establish the asymptotic properties for the proposed estimators. Simulation studies are performed to demonstrate the finite sample performance. Two real-data examples are analyzed by our procedures.

Sample size calculation for mixture cure model with restricted mean survival time as a primary endpoint.

It is not uncommon for a substantial proportion of patients to be cured (or survive long-term) in clinical trials with time-to-event endpoints, such as the endometrial cancer trial. When designing a clinical trial, a mixture cure model should be used to fully consider the cure fraction. Previously, mixture cure model sample size calculations were based on the proportional hazards assumption of latency distribution between groups, and the log-rank test was used for deriving sample size formulas. In real studies, the latency distributions of the two groups often do not satisfy the proportional hazards assumptions. This article has derived a sample size calculation formula for a mixture cure model with restricted mean survival time as the primary endpoint, and did simulation and example studies. The restricted mean survival time test is not subject to proportional hazards assumptions, and the difference in treatment effect obtained can be quantified as the number of years (or months) increased or decreased in survival time, making it very convenient for clinical patient-physician communication. The simulation results showed that the sample sizes estimated by the restricted mean survival time test for the mixture cure model were accurate regardless of whether the proportional hazards assumptions were satisfied and were smaller than the sample sizes estimated by the log-rank test in most cases for the scenarios in which the proportional hazards assumptions were violated.

Blood Hemoglobin Concentrations and the Incidence of Lower Extremity Peripheral Arterial Disease in Patients Undergoing Hemodialysis: 10-Year Outcomes of the Q-Cohort Study.

Lower extremity peripheral arterial disease is a potentially lethal cardiovascular complication in patients undergoing hemodialysis. Anemia is a risk factor for cardiovascular disease among the hemodialysis population. However, whether blood hemoglobin concentration is associated with the risk of peripheral arterial disease progression in this population remains undetermined. This is an extension of a 4-year multicenter, prospective, observational cohort study to 10 years. A total of 3504 Japanese patients undergoing maintenance hemodialysis were recruited between 2006 and 2007. The primary exposure was blood hemoglobin concentration at baseline. The main outcome was the first-ever incidence of major adverse limb events (MALE), composed of endovascular treatment, bypass surgery, and amputation. Multivariable-adjusted Cox proportional hazards model, Fine-Gray subdistribution hazards model, restricted cubic spline analysis, and restricted mean survival time analysis were used to determine the association of blood hemoglobin concentration with the incidence of MALE. During a median follow-up of 8.0 years, 257 patients experienced MALE. A Cox proportional hazards model showed that the risk of MALE in patients with blood hemoglobin concentrations <10.0 g/dL was significantly higher than in patients with concentrations of 11.0 to 11.9 g/dL, even after adjusting for confounding factors. In contrast, elevated hemoglobin concentration (≥12.0 g/dL) was not significantly associated with increased risk of MALE. Similar associations were observed when the Fine-Gray subdistribution regression model was used by setting all-cause mortality as the competing risk. A low blood hemoglobin concentration is an independent risk factor for peripheral arterial disease progression in patients undergoing maintenance hemodialysis.

Anti-cancer effects of hyperbaric oxygen therapy in mice: a meta-analysis

Abstract Objectives Hypoxia is a ubiquitous condition in solid tumors and is associated with increased glycolysis, therapy resistance and disease progression. Hyperbaric oxygen therapy (HBOT) systemically elevates O2 tension in tissues and thus counteracts hypoxia. Here, we conducted a meta-analysis to quantify the effects of HBOT on survival in mice with cancer. Methods Studies retrieved from PubMed and Google Scholar were included if they allowed extracting restricted mean survival times in an HBOT-treated and control group. Meta-analyses were conducted using standardized mean differences (SMDs) and the log-transformed response ratio (lnRR) between the RMST of the treatment and control group with multilevel random effects models in order to account for non-independence of effect sizes. Publication bias was tested using a multilevel version of Egger’s regression. Results All studies applied HBOT with pressures between 2 and 3 atmospheres absolute (ATA). When administered without additional treatments, HBOT was associated with longer mouse survival times (pooled SMD=1.359 ± 0.624, p=0.0446; lnRR=0.065 ± 0.029, p=0.0399). Higher pressure was significantly associated with higher efficacy of hyperbaric oxygen monotherapy. When combined with chemotherapy, radiotherapy, targeted therapy or a ketogenic diet, HBOT was associated with significantly prolonged survival times compared to mice receiving these treatments without HBOT (SMD=2.696 ± 0.545, p&lt;0.0001; lnRR=0.228 ± 0.042, p&lt;0.0001). The combination of HBOT with chemotherapy was associated with lower efficacy than the combination with other treatment modalities. Conclusions We found weak evidence that HBOT prolongs survival times in cancer-bearing mice and strong evidence for synergistic effects with other therapies. The translational potential of these findings and extrapolation to lower-pressure HBOT remain to be determined.

Abiraterone or Enzalutamide for Patients With Metastatic Castration-Resistant Prostate Cancer

Abiraterone acetate and enzalutamide are recommended as preferred treatments for metastatic castration-resistant prostate cancer (mCRPC), but differences in their relative efficacy are unclear due to a lack of head-to-head clinical trials. Clear guidance is needed for making informed mCRPC therapeutic choices. To compare clinical outcomes in patients with mCRPC treated with abiraterone acetate or enzalutamide. This retrospective, multicenter cohort study included patients with mCRPC in the US Department of Veterans Affairs health care system who initiated treatment with abiraterone acetate or enzalutamide between January 1, 2014, and October 30, 2022. Abiraterone acetate or enzalutamide. The study used inverse probability of treatment weighting to balance baseline characteristics between patients initiating abiraterone acetate or enzalutamide and evaluated restricted mean survival time (RMST) differences in overall survival (OS), prostate cancer-specific survival (PCS), time to next treatment switching or death (TTS), and time to prostate-specific antigen (PSA) response (TTR) at different time points after treatment initiation. The study included 5779 patients (median age, 74.42 years [IQR, 68.94-82.14 years]). Median follow-up was between 38 and 60 months. Patients initiating enzalutamide on average had longer OS than those initiating abiraterone acetate, with RMSTs of 24.29 months (95% CI, 23.58-24.99 months) and 23.38 months (95% CI, 22.85-23.92 months), respectively, and a difference in RMST of 0.90 months (95% CI, 0.02-1.79 months) at 4 years. Similarly, TTS and TTR were improved in patients initiating enzalutamide, with an RMST at 4 years of 1.95 months (95% CI, 0.92-2.99 months) longer for TTS and 3.57 months (95% CI, 1.76-5.38 months) shorter for TTR. For PCS, the RMST at 2 years was 0.48 months (95% CI, 0.01-0.95 months) longer. An examination of subgroups identified that enzalutamide initiation was associated with longer RMST in OS among patients without prior docetaxel treatment (1.14 months; 95% CI, 0.19-2.10 months) and in those with PSA doubling time of 3 months or longer (2.23 months; 95% CI, 0.81-3.66 months) but not among patients with prior docetaxel (-0.25 months; 95% CI, -2.59 to 2.09 months) or with PSA doubling time of less than 3 months (0.05 months; 95% CI, -1.05 to 1.15 months). In this cohort study of patients with mCRPC, initiation of enzalutamide was associated with small but statistically significant improvements in OS, PCS, TTS, and TTR compared with initiation of abiraterone acetate. The improvements were more prominent in short-term outcomes, including TTS and TTR, and in patient subgroups without prior docetaxel or with PSA doubling time longer than 3 months.

Injurious Fall Risk Differences Among Older Adults With First-Line Depression Treatments

One-third of older adults in the US have depression, often treated with psychotherapy and antidepressants. Previous studies suggesting an increased risk of falls and related injuries (FRI) associated with antidepressant use may be affected by confounding by indication or immortal time bias. To evaluate the association between FRI risk and first-line treatments in older adults with depression. This cohort study used a target trial emulation framework with a cloning-censoring-weighting approach with Medicare claims data from 2016 to 2019. Participants included fee-for-service beneficiaries aged 65 years or older with newly diagnosed depression. Data were analyzed from October 1, 2023, to March 31, 2024. First-line depression treatments including psychotherapy, sertraline, escitalopram, citalopram, mirtazapine, duloxetine, trazodone, fluoxetine, bupropion, paroxetine, and venlafaxine. One-year FRI rate, restricted mean survival time (RMST), and adjusted hazard ratio (aHR) with 95% CI. Among 101 953 eligible beneficiaries (mean [SD] age, 76 [8] years), 63 344 (62.1%) were female, 7404 (7.3%) were Black individuals, and 81 856 (80.3%) were White individuals. Compared with the untreated group, psychotherapy use was not associated with FRI risk (aHR, 0.94 [95% CI, 0.82-1.17]), while other first-line antidepressants were associated with a decreased FRI risk (aHR ranged from 0.74 [95% CI, 0.59-0.89] for bupropion to 0.83 [95% CI, 0.67-0.98] for escitalopram). The FRI incidence ranged from 63 (95% CI, 53-75) per 1000 person-year for those treated with bupropion to 87 (95% CI, 83-90) per 1000 person-year for those who were untreated. The RMST ranged from 349 (95% CI, 346-350) days for those who were untreated to 353 (95% CI, 350-356) days for those treated with bupropion. In this cohort study of older Medicare beneficiaries with depression, first-line antidepressants were associated with a decreased FRI risk compared with untreated individuals. These findings provide valuable insights into their safety profiles, aiding clinicians in their consideration for treating depression in older adults.

Estimating individualized treatment rules by optimizing the adjusted probability of a longer survival.

Individualized treatment rules inform tailored treatment decisions based on the patient's information, where the goal is to optimize clinical benefit for the population. When the clinical outcome of interest is survival time, most of current approaches typically aim to maximize the expected time of survival. We propose a new criterion for constructing Individualized treatment rules that optimize the clinical benefit with survival outcomes, termed as the adjusted probability of a longer survival. This objective captures the likelihood of living longer with being on treatment, compared to the alternative, which provides an alternative and often straightforward interpretation to communicate with clinicians and patients. We view it as an alternative to the survival analysis standard of the hazard ratio and the increasingly used restricted mean survival time. We develop a new method to construct the optimal Individualized treatment rule by maximizing a nonparametric estimator of the adjusted probability of a longer survival for a decision rule. Simulation studies demonstrate the reliability of the proposed method across a range of different scenarios. We further perform data analysis using data collected from a randomized Phase III clinical trial (SWOG S0819).

Liver transplantation provides survival benefit at all levels of frailty: From the Multicenter Functional Assessment in Liver Transplantation Study.

Offering LT to frail patients may reduce waitlist mortality but may increase post-LT mortality. LT survival benefit is the concept of balancing these risks. We sought to quantify net survival benefit with LT by liver frailty index (LFI). We analyzed data in the multi-center Functional Assessment in LT (FrAILT) Study from 2012-2021. Pre-LT cohort included ambulatory patients with cirrhosis awaiting LT, without hepatocellular carcinoma; post-LT cohort included those who underwent LT. Primary outcomes were pre-LT and post-LT mortality. We computed 1-, 3-, and 5-year restricted mean survival times (RMST) from adjusted Cox models. Survival benefit was calculated as net gain in life-years with LT. Pre-LT cohort included 2628 patients: median MELDNa was 18 (IQR 14-22); 731 (28%) were frail; 440 (17%) died pre-LT. Post-LT cohort included 1335 patients: median MELDNa was 20 (IQR 14-24); 325 (24%) were frail; 103 (8%) died post-LT. Pre-LT RMST decreased substantially as LFI increased. Post-LT RMST also decreased as LFI increased but only modestly. There was no LFI threshold at which pre-LT and post-LT RMST intersected-patients had net survival benefit at all LFI values. Pre-LT and, to a lesser degree, post-LT mortality increased as LFI increased. Transplant offered a survival benefit at all LFI values, driven by a reduction in pre-LT mortality. No threshold of LFI was identified at which the risk of post-LT mortality exceeded pre-LT mortality. LT offers net survival benefit even in the presence of advanced frailty among those selected for LT.

Impact of Thoracic Duct Resection on Long-Term Survival After Esophagectomy: Individual Patient Data Meta-analysis.

Radical esophagectomy, including thoracic duct resection (TDR), has been proposed to improve regional lymphadenectomy and possibly reduce the risk of locoregional recurrence. However, because of its impact on immunoregulation, some authors have expressed concerns about its possible detrimental effect on long-term survival. The purpose of this review was to assess the influence of TDR on long-term survival. PubMed, MEDLINE, Scopus, and Web of Science databases were searched through 15 March 2024. Overall survival (OS), cancer specific survival (CSS), and disease-free survival (DFS) were primary outcomes. Restricted mean survival time difference (RMSTD), risk ratio (RR), standardized mean difference (SMD), and 95% confidence intervals (CI) were used as pooled effect size measures. The Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) methodology was employed to evaluate the certainty of evidence. The analysis included six studies with 5756 patients undergoing transthoracic esophagectomy. TDR was reported in 49.1%. Patients' ages ranged from 27 to 79 years and 86% were males. At 4-year follow-up, the multivariate meta-analysis showed similar results for the comparison noTDR versus TDR in term of OS [- 0.8 months, 95% confidence interval (CI) - 3.1, 1.3], CSS (0.1 months, 95% CI - 0.9, 1.2), and DFS (1.5 months, 95% CI - 2.6, 5.5). TDR was associated with a significantly higher number of harvested mediastinal lymph nodes (SMD 0.57, 95% CI 0.01-1.13) and higher risk of postoperative chylothorax (RR = 1.32; 95% CI 1.04-2.23). Anastomotic leak and pulmonary complications were comparable. TDR seems not to improve long-term OS, CSS, and DFS regardless of tumor stage. Routine TDR should not be routinely recommended during esophagectomy.

Waitlist Time, Age, and Social Vulnerability: Impact on the Survival Benefit of Deceased Donor Kidney Transplantation Versus Long-term Dialysis Among Patients With End-stage Renal Disease.

We sought to define the survival benefit of kidney transplantation versus long-term dialysis relative to waitlist time on dialysis, social vulnerability, and age among end-stage renal transplant candidates. End-stage renal disease patients who were candidates for their first deceased donor kidney transplantation between 2008 and 2020 were identified using the US Renal Data System. Survival probabilities for patient survival were compared using the restricted mean survival times (RMSTs) across different age and social vulnerability index (SVI) ranges. Among 149 923 patients, 68 795 (45.9%) patients underwent a kidney transplant and 81 128 (54.1%) remained on dialysis. After propensity-score matching (n = 58 035 in each cohort), the 5-y RMST difference between kidney transplant and dialysis demonstrated an increasing trend in mean life-years gained within 5 y of follow-up relative to advancing age (<30 y: 0.40 y, 95% confidence interval, 0.36-0.44 y versus >70 y: 0.75 y, 95% confidence interval, 0.70-0.80 y). Conversely, disparities in 5-y RMSTs remained consistent relative to social vulnerability (median 5-y RMST difference: 0.62 y comparing low versus high SVI). When considering waitlist duration, stratified analyses demonstrated increasing trends across different age groups with the largest RMST differences observed among older patients aged ≥70 y. Notably, longer waitlist durations (>3 y) yielded more pronounced RMST differences compared with shorter durations (<1 y). These data underscore the survival benefit associated with kidney transplantation over long-term dialysis across various age and SVI ranges. Transplantation demonstrated a greater advantage among older patients who had a longer waitlist duration.

Survival loss linked to guideline-based indications for degenerative mitral regurgitation surgery.

Operating on patients with severe degenerative mitral regurgitation (DMR) is based on ACC/AHA or ESC/EACTS-guidelines. Doubts persist on best surgical indications and their potential association with postoperative survival loss. We sought to investigate whether guideline-based indications lead to late postoperative survival loss in DMR-patients. : We analyzed outcome of 2833 patients from the MIDA-registry undergoing surgical correction of DMR. Patients were stratified by surgical indications: Class-I-trigger (symptoms, left ventricular end-systolic diameter≥40mm, or left ventricular ejection fraction<60%, n=1677), isolated-Class-IIa-trigger (atrial fibrillation [AF], pulmonary hypertension [PH], or left atrial diameter≥55mm, n=568), or no-trigger (n=588). Postoperative survival was compared after matching for clinical differences. Restricted-mean-survival time (RMST) was analyzed. During a median 8.5-year follow-up, 603 deaths occurred. Long-term postoperative survival was lower with Class-I-trigger than in Class-IIa-trigger and no-trigger (71.4±1.9%, 84.3±2.3%, 88.9±1.9% at 10 years, p<0.001). Having at least one Class-I-criterion led to excess mortality (p<0.001), while several Class-I-criteria conferred additional death-risk (HR:1.53, 95%CI:1.42-1.66). Isolated-Class-IIa-triggers conferred an excess mortality risk versus those without (HR:1.46, 95%CI:1.00-2.13, p=0.05). Among these patients, isolated-PH led to decreased postoperative-survival versus those without (83.7%±2.8% vs. 89.3%±1.6%, p=0.011), with the same pattern observed for AF (81.8%±5.0% vs. 88.3%±1.5%, p=0.023). According to RMST-analysis, compare to those operated on without triggers, operating on Class-I-trigger patients led to 9.4-month survival-loss (p<0.001) and operating on isolated-Class-IIa-trigger patients displayed 4.9-month survival loss (p=0.001) after 10-years. : Waiting for the onset of Class-I or isolated-Class-IIa-triggers before operating on DMR patients is associated with postoperative survival loss. These data encourage an early surgical-strategy.

A DPC Database Study on the Safety of Atezolizumab/Bevacizumab/Carboplatin/Paclitaxel in Non-small Cell Lung Cancer in Japanese Patients.

Atezolizumab, bevacizumab, carboplatin, and paclitaxel (ABCP) combination therapy is a standard of care for advanced non-squamous non-small cell lung cancer (NSQ-NSCLC); however, the lack of safety data limits its clinical application in Japan. This study compared the safety of ABCP with that of bevacizumab, carboplatin, and paclitaxel (BCP) combination for the treatment of advanced NSQ-NSCLC in Japanese patients by evaluating the clinical background and incidence of adverse events (AEs) based on data extracted from the Diagnosis Procedure Combination (DPC) database. Incidence rates and restricted mean survival times (RMSTs) for up to 1 year were analyzed for 19 clinically important AEs. Covariates were adjusted using the inverse probability weighting method. A search conducted using the International Statistical Classification of Diseases and Related Health Problems 10th Revision codes identified 350,987 patients, of whom 202 were included in the ABCP cohort and 232 in the BCP cohort. Among the 19 AEs, the incidence of skin disorder and febrile neutropenia (FN) was significantly higher in the ABCP cohort versus the BCP cohort. The adjusted incidence rate ratios were 2.65 [95%confidence interval (CI) 1.43-4.91] for skin disorder and 1.70 (95% CI 1.01-2.85) for FN. The adjusted RMST differences were-64.2 days (95% CI-93.0 to-35.4 days) and-46.0days (95% CI-73.5 to-18.5 days) for skin disorder and FN, respectively. These results were comparable to those of other pivotal clinical trials. The findings of this DPC database study highlight the safety of ABCP in Japanese clinical practice, and this methodology may facilitate more efficient research in real-world settings. UMIN Clinical Trials Registry ID UMIN000041507.

Exploring the Bidirectional Relationship Between Periodontitis and Rheumatoid Arthritis in a Large Danish Cohort.

We investigated the bidirectional relationship between rheumatoid arthritis (RA) and periodontitis and their cross-sectional association using national administrative health care data. The sample included 3,308,903 individuals aged 20 to 79 years who resided in Denmark in 2000 and had remained free of RA and periodontitis in the previous 10 years. RA and periodontitis were defined using diagnosis and treatment codes. Marginal structural survival models were employed to estimate the effects of RA on periodontitis incidence and vice versa from 2000 to 2017. Using a cross-sectional sample of 2,574,536 individuals from 2017, the association of periodontitis with RA was investigated using regression analyses and probabilistic quantitative bias analyses, simulating RA and periodontitis misclassification and unmeasured confounding of smoking. Between 2000 and 2017, 20,348 individuals developed RA and 740,799 developed periodontitis. The estimated hazard ratio (HR) for the effect of periodontitis on incident RA was 1.05 (95% confidence interval [CI] 0.88-1.25), resulting in a restricted mean survival time difference of one day. The HR for the effect of RA on incident periodontitis was 0.84 (95% CI 0.80-0.88), corresponding to a restricted mean survival time difference of 151 days. Cross-sectionally, the unadjusted prevalence ratio for the association was 1.15 (95% CI 1.11-1.19), whereas the estimate adjusted for measured and simulated confounding was practically null (0.99, 95% simulation interval 0.93-1.04). These findings challenge previously reported bidirectional relationships between periodontitis and RA, pointing to potential residual confounding as an important link and prompting reconsideration of the biologic plausibility and clinical significance of these associations.