Proportional Hazards Assumption Research Articles

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.

A nomogram based on circulating CD8+ T cell and platelet-to-lymphocyte ratio to predict overall survival of patients with locally advanced nasopharyngeal carcinoma

PurposeTo explore the influence of circulating lymphocyte subsets, serum markers, clinical factors, and their impact on overall survival (OS) in locally advanced nasopharyngeal carcinoma (LA-NPC). Additionally, to construct a nomogram predicting OS for LA-NPC patients using independent prognostic factors.MethodsA total of 530 patients with LA-NPC were included in this study. In the training cohort, Cox regression analysis was utilized to identify independent prognostic factors, which were then integrated into the nomogram. The concordance index (C-index) was calculated for both training and validation cohorts. Schoenfeld residual analysis, calibration curves, and decision curve analysis (DCA) were employed to evaluate the nomogram. Kaplan-Meier methods was performed based on risk stratification using the nomogram.ResultsA total of 530 LA-NPC patients were included. Multivariate Cox regression analysis revealed that the circulating CD8+T cell, platelet-to-lymphocyte ratio (PLR), lactate dehydrogenase (LDH), albumin (ALB), gender, and clinical stage were independent prognostic factors for LA-NPC (p < 0.05). Schoenfeld residual analysis indicated overall satisfaction of the proportional hazards assumption for the Cox regression model. The C-index of the nomogram was 0.724 (95% CI: 0.669–0.779) for the training cohort and 0.718 (95% CI: 0.636-0.800) for the validation cohort. Calibration curves demonstrated good correlation between the model and actual survival outcomes. DCA confirmed the clinical utility enhancement of the nomogram over the TNM staging system. Significant differences were observed in OS among different risk stratifications.ConclusionCirculating CD8+ T cell, PLR, LDH, ALB, gender and clinical stage are independent prognostic factors for LA-NPC. The nomogram and risk stratification constructed in this study effectively predict OS in LA-NPC.

Postoperative radiotherapy in women with early operable breast cancer (Scottish Breast Conservation Trial): 30-year update of a randomised, controlled, phase 3 trial

Breast-conserving surgery, adjuvant systemic therapy, and radiotherapy are the standard of care for most women with early breast cancer. There are few reports of clinical outcomes beyond the first decade of follow-up of randomised trials comparing breast-conserving surgery with or without radiotherapy. We present a 30-year update of the Scottish Breast Conservation Trial. In this randomised, controlled, phase 3 trial across 14 hospitals in Scotland, women aged younger than 70 years with early breast cancer (tumours ≤4 cm [T1 or T2 and N0 or N1]) were included. They underwent breast-conserving surgery (1 cm margin) with axillary node sampling or clearance. Oestrogen receptor (ER)-rich patients (≥20 fmol/mg protein) received 20 mg oral tamoxifen daily for 5 years. ER-poor patients (<20 fmol/mg protein) received chemotherapy (cyclophosphamide 600 mg/m2, methotrexate 50 mg/m2, and fluorouracil 600 mg/m2 every 21 days intravenously in eight courses). Stratification was by menstrual status (within or more than 12 months from last menstrual period) and ER status (oestrogen concentration ≥20 fmol/mg protein, <20 fmol/mg protein, or unknown) and patients were randomly assigned (1:1) to high-dose (50 Gy in 20-25 fractions) local or locoregional radiotherapy versus no radiotherapy. No blinding was possible due to the nature of the treatment. We report the primary endpoint of the original trial, ipsilateral breast tumour recurrence, and the co-primary endpoint, overall survival. Clinical outcomes were compared by the log-rank test. Hazard ratios (HRs) are reported, with no radiotherapy as the reference group. Failures of the proportional hazards assumption are reported if significant. All analyses are by intention to treat. Between April 1, 1985, and Oct 2, 1991, 589 patients were enrolled and randomly assigned to the two treatment groups (293 to radiotherapy and 296 to no radiotherapy). After exclusion of four ineligible patients (two in each group), there were 291 patients in the radiotherapy group and 294 patients in the no radiotherapy group. Median follow-up was 17·5 years (IQR 8·4-27·9). Ipsilateral breast tumour recurrence was significantly lower in the radiotherapy group than in the no radiotherapy group (46 [16%] of 291 vs 107 [36%] of 294; HR 0·39 [95% CI 0·28-0·55], p<0·0001). Although there were differences in the hazard rate for ipsilateral breast tumour recurrence in the first decade after treatment (HR 0·24 [95% CI 0·15-0·38], p<0·0001), subsequent risks of ipsilateral breast tumour recurrence were similar in both groups (0·98 [0·54-1·79], p=0·95). There was no difference in overall survival between the two groups (median 18·7 years [95% CI 16·5-21·5] in the no radiotherapy group vs 19·2 years [16·9-21·3] in the radiotherapy group; HR 1·08 [95% CI 0·89-1 ·30], log-rank p=0·43). Our findings suggest that patients whose biology predicts a late relapse a decade or more after breast-conserving surgery for early breast cancer might gain little from adjuvant radiotherapy. Breast Cancer Institute (part of Edinburgh and Lothian Health Foundation) and PFS Genomics (now part of Exact Sciences).

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.

Incidence and risk factors of SARS-CoV-2 breakthrough infection in the early Omicron variant era among vaccinated and boosted individuals in Chicago.

SARS-CoV-2 vaccines are safe and effective against infection and severe COVID-19 disease worldwide. Certain co-morbid conditions cause immune dysfunction and may reduce immune response to vaccination. In contrast, those with co-morbidities may practice infection prevention strategies. Thus, the real-world clinical impact of co-morbidities on SARS-CoV-2 infection in the recent post-vaccination period is not well established. This study was performed to understand the epidemiology of Omicron breakthrough infection and evaluate associations with number of comorbidities in a vaccinated and boosted population. A retrospective clinical cohort study was performed utilizing the Northwestern Medicine Enterprise Data Warehouse. Our study population was identified as fully vaccinated adults with at least one booster. The primary risk factor of interest was the number of co-morbidities. The primary outcome was the incidence and time to the first positive SARS-CoV-2 molecular test in the Omicron predominant era. Multivariable Cox modeling analyses to determine the hazard of SARS-CoV-2 infection were stratified by calendar time (Period 1: January 1 -June 30, 2022; Period 2: July 1 -December 31, 2022) due to violations in the proportional hazards assumption. In total, 133,191 patients were analyzed. During Period 1, having 3+ comorbidities was associated with increased hazard for breakthrough (HR = 1.16 CI 1.08-1.26). During Period 2 of the study, having 2 comorbidities (HR = 1.45 95% CI 1.26-1.67) and having 3+ comorbidities (HR 1.73, 95% CI 1.51-1.97) were associated with increased hazard for Omicron breakthrough. Older age was associated with decreased hazard in Period 1 of follow-up. Interaction terms for calendar time indicated significant changes in hazard for many factors between the first and second halves of the follow-up period. Omicron breakthrough is common with significantly higher risk for our most vulnerable patients with multiple co-morbidities. Age plays an important role in breakthrough infection with the highest incidence among young adults, which may be due to age-related behavioral factors. These findings reflect real-world differences in immunity and exposure risk behaviors for populations vulnerable to COVID-19.

Confirming the efficacy and safety of CDK4/6 inhibitors in the first-line treatment of HR+ advanced breast cancer: a systematic review and meta-analysis.

Objective: Cyclin-dependent kinase (CDK) 4 and 6 inhibitors (abemaciclib, palbociclib and ribociclib) have been recommended in the first-line treatment of hormone receptor-positive (HR+) breast cancer in China. Our study aims to evaluate the efficacy and safety of CDK4/6 inhibitors by processing survival data using fractional polynomial modeling methods. Methods: Phase II or III randomized controlled trials in treatment-naive HR + patients with advanced breast cancer were systematically searched through the preset search strategy. The fractional polynomial (FP) model was used to relax the proportional hazard assumption and obtain time-varying hazard ratio (HR). Progression-free life years (PFLYs) and life years (LYs) were calculated from the area under curve (AUC) of the predicted progression-free survival (PFS) and overall survival (OS) curves to evaluate the long-term efficacy benefit. Odds ratio (OR) of grade≥3 adverse events were analyzed for safety outcomes. Results: 6 randomized controlled trials with 2,638 patients were included. The first-order FP model (p = -1) and the first-order FP model (p = 1) were used to calculate the time-varying HR of PFS and OS, respectively. Extrapolating to 240 months, abemaciclib obtained a PFS benefit of 3.059 PFLYs and 6.275 LYs by calculating the AUC of the PFS and OS curves. Palbociclib obtained 2.302 PFLYs and 6.351 LYs. Ribociclib obtained 2.636 PFLYs and 6.543 LYs. In terms of safety, the use of CDK4/6 inhibitors resulted in a higher risk of adverse events (OR = 9.84, 95% CI: 8.13-11.95), especially for palbociclib (OR = 14.04, 95% CI: 10.52-18.90). Conclusion: The use of CDK4/6 inhibitors in treatment-naive patients with HR + advanced breast cancer significantly improves survival, but also increases the risk of adverse events. Abemaciclib and ribociclib may be the best options for prolonging PFS and OS in treatment-naïve patients, respectively.

Lenvatinib plus pembrolizumab for untreated advanced renal cell carcinoma: a systematic review and cost-effectiveness analysis.

Renal cell carcinoma is the most common type of kidney cancer, comprising approximately 85% of all renal malignancies. Patients with advanced renal cell carcinoma are the focus of this National Institute for Health and Care Excellence multiple technology appraisal. A patient's risk of disease progression depends on a number of prognostic risk factors; patients are categorised as having intermediate/poor risk or favourable risk of disease progression. The objectives of this multiple technology appraisal were to appraise the clinical effectiveness and cost-effectiveness of lenvatinib plus pembrolizumab versus relevant comparators listed in the final scope issued by the National Institute for Health and Care Excellence: sunitinib, pazopanib, tivozanib, cabozantinib and nivolumab plus ipilimumab. The assessment group carried out clinical and economic systematic reviews and assessed the clinical and cost-effectiveness evidence submitted by Eisai, Hatfield, Hertfordshire, UK (the manufacturer of lenvatinib) and Merck Sharp & Dohme, Whitehouse Station, NJ, USA (the manufacturer of pembrolizumab). The assessment group carried out fixed-effects network meta-analyses using a Bayesian framework to generate evidence for clinical effectiveness. As convergence issues occurred due to sparse data, random-effects network meta-analysis results were unusable. The assessment group did not develop a de novo economic model, but instead modified the partitioned survival model provided by Merck Sharp & Dohme. The assessment group clinical systematic review identified one relevant randomised controlled trial (CLEAR trial). The CLEAR trial is a good-quality, phase III, multicentre, open-label trial that provided evidence for the efficacy and safety of lenvatinib plus pembrolizumab compared with sunitinib. The assessment group progression-free survival network meta-analysis results for all three risk groups should not be used to infer any statistically significant difference (or lack of statistically significant difference) for any of the treatment comparisons owing to within-trial proportional hazards violations or uncertainty regarding the validity of the proportional hazards assumption. The assessment group overall survival network meta-analysis results for the intermediate-/poor-risk subgroup suggested that there was a numerical, but not statistically significant, improvement in the overall survival for patients treated with lenvatinib plus pembrolizumab compared with patients treated with cabozantinib or nivolumab plus ipilimumab. Because of within-trial proportional hazards violations or uncertainty regarding the validity of the proportional hazards assumption, the assessment group overall survival network meta-analysis results for the favourable-risk subgroup and the all-risk population should not be used to infer any statistically significant difference (or lack of statistically significant difference) for any of the treatment comparisons. Only one cost-effectiveness study was included in the assessment group review of cost-effectiveness evidence. The study was limited to the all-risk population, undertaken from the perspective of the US healthcare system and included comparators that are not recommended by the National Institute for Health and Care Excellence for patients with untreated advanced renal cell carcinoma. Therefore, the extent to which resource use and results are generalisable to the NHS is unclear. The assessment group cost-effectiveness results from the modified partitioned survival model focused on the intermediate-/poor-risk and favourable-risk subgroups. The assessment group cost-effectiveness results, generated using list prices for all drugs, showed that, for all comparisons in the favourable-risk subgroup, treatment with lenvatinib plus pembrolizumab costs more and generated fewer benefits than all other treatments available to NHS patients. For the intermediate-/poor-risk subgroup, treatment with lenvatinib plus pembrolizumab costs more and generated more benefits than treatment with cabozantinib and nivolumab plus ipilimumab. Good-quality clinical effectiveness evidence for the comparison of lenvatinib plus pembrolizumab with sunitinib is available from the CLEAR trial. For most of the assessment group Bayesian hazard ratio network meta-analysis comparisons, it is difficult to reach conclusions due to within-trial proportional hazards violations or uncertainty regarding the validity of the proportional hazards assumption. However, the data (clinical effectiveness and cost-effectiveness) used to populate the economic model are relevant to NHS clinical practice and can be used to inform National Institute for Health and Care Excellence decision-making. The assessment group cost-effectiveness results, generated using list prices for all drugs, show that lenvatinib plus pembrolizumab is less cost-effective than all other treatment options. This study is registered as PROSPERO CRD4202128587. This award was funded by the National Institute for Health and Care Research (NIHR) Evidence Synthesis Programme (NIHR award ref: NIHR134985) and is published in full in Health Technology Assessment; Vol. 28, No. 49. See the NIHR Funding and Awards website for further award information.

Construction of a nomogram with IrAE and clinic character to predict the survival of advanced G/GEJ adenocarcinoma patients undergoing anti-PD-1 treatment.

This study aimed to develop and validate a survival prediction model and nomogram to predict survival in patients with advanced gastric or gastroesophageal junction (G/GEJ) adenocarcinoma undergoing treatment with anti-programmed cell death 1 receptor (PD-1). This model incorporates immune-related adverse events (irAEs) alongside common clinical characteristics as predictive factors. A dataset comprising 255 adult patients diagnosed with advanced G/GEJ adenocarcinoma was assembled. The irAEs affecting overall survival (OS) to a significant degree were identified and integrated as a candidate variable, together with 12 other candidate variables. These included gender, age, Eastern cooperative oncology group performance status (ECOG PS) score, tumor stage, human epidermal growth factor receptor 2 (HER2) expression status, presence of peritoneal and liver metastases, year and line of anti-PD-1 treatment, neutrophil-to-lymphocyte ratio (NLR), controlling nutritional status (CONUT) score, and Charlson comorbidity index (CCI). To mitigate timing bias related to irAEs, landmark analysis was employed. Variable selection was performed using the least absolute shrinkage and selection operator (LASSO) regression to pinpoint significant predictors, and the variance inflation factor was applied to address multicollinearity. Subsequently, a Cox regression analysis utilizing the forward likelihood ratio method was conducted to develop a survival prediction model, excluding variables that failed to satisfy the proportional hazards (PH) assumption. The model was developed using the entire dataset, then internally validated through bootstrap resampling and externally validated with a cohort from another Hospital. Furthermore, a nomogram was created to delineate the predictive model. After consolidating irAEs from the skin and endocrine systems into a single protective irAE category and applying landmark analysis, variable selection was conducted for the prognostic prediction model along with other candidate variables. The finalized model comprised seven variables: ECOG PS score, tumor stage, HER2 expression status in tumor tissue, first-line anti-PD-1 treatment, peritoneal metastasis, CONUT score, and protective irAE. The overall concordance index for the model was 0.66. Calibration analysis verified the model's accuracy in aligning predicted outcomes with actual results. Clinical decision curve analysis indicated that utilizing this model for treatment decisions could enhance the net benefit regarding 1- and 2-year survival rates for patients. This study developed a prognostic prediction model by integrating common clinical characteristics of irAEs and G/GEJ adenocarcinoma. This model exhibits good clinical practicality and possesses accurate predictive ability for overall survival OS in patients with advanced G/GEJ adenocarcinoma.

Diabetic retinopathy incidence, predictors and its association with longitudinal fasting blood sugar level changes among diabetes mellitus patients in Ethiopia: joint model.

Diabetes mellitus (DM) is a global public health problem characterized by an elevated blood glucose level. Monitoring blood sugar levels is vital for effective diabetes management and preventing complications. However, the association between longitudinal biomarkers and the incidence of diabetic complications is often overlooked. Therefore, this study aimed to assess the incidence of diabetic retinopathy, predictors, and association with longitudinal fasting blood sugar level changes among diabetes mellitus patients in Ethiopia. A multicenter retrospective follow-up study was carried out in referral hospitals in Amhara region, Ethiopia. A random sample of 462 newly diagnosed DM patients was selected. The proportional hazard assumption was checked for the survival sub-model, and for the longitudinal sub-model, the normality assumption was checked. Then the joint modeling with time-dependent lagged parameterizations was fitted. Model assumptions and comparisons were checked. Finally, the hazard ratio with a 95% confidence interval (CI) with a corresponding P-value<0.05 was used to identify predictors. In this study, Overall, 54 patients developed DR, and the incidence rate was 2.33 per 1000 person-months over the follow-up period, with a 95% CI of [1.78, 3.05]. Rural residence (AHR = 2.21, 95% CI: [1.21, 4.05]), hypertension co-morbidity (AHR = 3.01, 95% CI: [1.85, 6.53]), and longer duration of DM (>5 years) (AHR = 2.28, 95% CI: [1.91, 5.15]) were important predictors for the incidence of DR. In addition, the incidence of DR was substantially correlated with the time-dependent lagged value of FBS change (AHR = 4.20, 95% CI [1.62, 10.85]). In this study, the incidence of diabetic retinopathy was somewhat high when compared to prior similar studies in Ethiopia. A joint model of longitudinal fasting blood sugar level changes was significantly associated with an increased risk of DR. Besides, being rural residence, hypertension co-morbidity, and a longer duration of DM were significant predictors for the incidence of DR. Therefore, public awareness, an integrated care approach, and prioritizing glycemic control are highly recommended.

Effective comparison of two potentially crossing hazard rate curves

In survival data analysis, comparison of two hazard rate curves is critically important for evaluating a treatment effect. In many applications, the two hazard curves could potentially cross each other, violating the proportional hazards assumption in the Cox's model. In such cases, the traditional tests like the log-rank test and the Peto-Peto test that were developed based on that assumption would be ineffective. There have been some discussions in the literature on comparison of two potentially crossing hazard curves, based on either parametric modeling or nonparametric testing approaches. However, the assumed models of the existing parametric methods are often difficult to justify in practice. On the other hand, the existing nonparametric tests are usually based on the maximization with respect to an unknown crossing point, leading to complex null distributions for the corresponding test statistics. We suggest a novel method in this paper for comparing two hazard curves based on a nonparametric testing procedure. Its test statistic avoids the maximization mentioned above and consequently has the desirable asymptotic normality property under some regularity conditions. We show that the new method is effective for comparing two potentially crossing hazard curves.

Group sequential methods based on supremum logrank statistics underproportional and nonproportionalhazards.

Despite the widespread use of Cox regression for modeling treatment effects in clinical trials, in immunotherapy oncology trials and other settings therapeutic benefits are not immediately realized thereby violating the proportional hazards assumption. Weighted logrank tests and the so-called Maxcombo test involving the combination of multiple logrank test statistics have been advocated to increase power for detecting effects in these and other settings where hazards are nonproportional. We describe a testing framework based on supremum logrank statistics created by successively analyzing and excluding early events, or obtained using a moving time window. We then describe how such tests can be conducted in a group sequential trial with interim analyses conducted for potential early stopping of benefit. The crossing boundaries for the interim test statistics are determined using an easy-to-implement Monte Carlo algorithm. Numerical studies illustrate the good frequency properties of the proposed group sequential methods.

Evaluation of the proportional hazards assumption and covariate adjustment methods in comparative surgical observational studies with time-to-event endpoints

IntroductionComparative studies on surgical treatments with time-to-event endpoints have provided substantial evidence for clinical practice, but the accurate use of survival data analysis and the control of confounding bias remain big challenges. MethodsThis was a survey of surgical studies with survival outcomes published in four general medical journals and five general surgical journals in 2021. The two most concerned statistical issues were evaluated, including confounding control by propensity score analysis (PSA) or multivariable analysis and testing of proportional hazards (PH) assumption in Cox model. ResultsA total of 74 studies were included, comprising 63 observational studies and 11 randomized controlled trials. Among the observational studies, the proportion of studies utilizing PSA in surgical oncology and non-oncology studies was similar (40.9 % versus 36.8 %, P = 0.762). However, the former reported a significantly lower proportion of PH assumption assessments compared to the latter (13.6 % versus 42.1 %, P = 0.020). Twenty-five observational studies (25/63) used PSA methods, but two-thirds of them (17/25) showed unclear balance of baseline data after PSA. And the proportion of PH assumption testing after PSA was slightly lower than that before PSA, but the difference was not statistically significant (24.0 % versus 28.0 %, P = 0.317). Comprehensive suggestions were given on confounding control in survival analysis and alternative resolutions for non-compliance with PH assumption. ConclusionThis study highlights suboptimal reporting of PH assumption evaluation in observational surgical studies both before and after PSA. Efforts and consensus are needed with respect to the underlying assumptions of statistical methods.

Hazard of Failed Nonoperative Management for Symptomatic Accessory Navicular in Children and Adolescents: A Population-Based Case-Cohort Study.

The accessory navicular (AN) is an idiopathic condition of the foot present in 4% to 21% of the population. Most ANs remain asymptomatic, but children and adolescents who develop symptoms can have remarkably reduced quality of life. Although many respond to conservative measures, surgery is occasionally needed. Our purpose was to determine factors associated with the failure of nonoperative management. This single-institution retrospective case-cohort study included patients up to age 19 years presenting between 2000 and 2021 with symptomatic AN and treated with standard-of-care. All 298 surgical cases, indicating failed nonoperative treatment, were included. For the subcohort, 299 patients were randomly sampled from all eligible patients, regardless of treatment. Baseline characteristics were summarized for the surgical cases and subcohort. Proportional hazards assumptions were checked and stratification implemented when necessary. Marginal structural proportional hazard modeling was used to estimate hazard ratios with 95% confidence intervals via inverse probability and LinYing weighting methods. The 298 surgical cases failed nonoperative management at a median of 5.2 months (IQR, 2.0-11.6 mo). In the subcohort, 86 failures of nonoperative management and 213 nonfailures constituted a 28.8% surgery rate. In both cohorts, nearly all patients played sports. Univariate proportional hazard modeling found older age ( P =0.02) and activity limitation ( P <0.001) at presentation, female sex ( P =0.002), higher BMI ( P =0.01), AN on the right ( P <0.001), and bone marrow edema of the AN ( P <0.001) and navicular body ( P <0.001) on MRI were associated with increased hazard of nonoperative failure. Nearly all of the surgical cohort reported improvement in pain (278/296, 94%) and returned to their primary sport (236/253, 93%) after surgery. Most also experienced full resolution of symptoms (187/281, 67%). Symptomatic AN predominantly affects female athletes, leading to surgery in 28.8% of our subcohort. Conservative treatment may be less successful-and therefore surgery could be more strongly considered-in older age, activity limitation at presentation, female sex, higher BMI, right-sided AN, and bone marrow edema on MRI. Surgery is effective for symptomatic and functional improvement. Case-cohort-Level III.

Real-World Assessment of Recommended COVID-19 Vaccination Waiting Period after Chemotherapy.

There is a knowledge gap concerning the proper timing for COVID-19 vaccination in cancer patients undergoing chemotherapy. We aimed to evaluate the suitability of the guidelines that recommend waiting at least three months after undergoing chemotherapy before receiving a COVID-19 vaccine. This retrospective cohort study used aggregated data from the TriNetX US Collaboratory network. Participants were grouped into two groups based on the interval between chemotherapy and vaccination. The primary outcome assessed was infection risks, including COVID-19; skin, intra-abdominal, and urinary tract infections; pneumonia; and sepsis. Secondary measures included healthcare utilization and all causes of mortality. Kaplan-Meier analysis and the Cox proportional hazard model were used to calculate the cumulative incidence and hazard ratio (HR) and 95% confidence intervals for the outcomes. The proportional hazard assumption was tested with the generalized Schoenfeld approach. Four subgroup analyses (cancer type, vaccine brand, sex, age) were conducted. Sensitivity analyses were performed to account for competing risks and explore three distinct time intervals. Patients receiving a vaccine within three months after chemotherapy had a higher risk of COVID-19 infection (HR: 1.428, 95% CI: 1.035-1.970), urinary tract infection (HR: 1.477, 95% CI: 1.083-2.014), and sepsis (HR: 1.854, 95% CI: 1.091-3.152) compared to those who adhered to the recommendations. Hospital inpatient service utilization risk was also significantly elevated for the within three months group (HR: 1.692, 95% CI: 1.354-2.115). Adhering to a three-month post-chemotherapy waiting period reduces infection and healthcare utilization risks for cancer patients receiving a COVID-19 vaccine.

A Bayesian adaptive phase III design for multi-arm trials with time-to-event endpoint for nonproportional hazards utilizing the generalized gamma distribution

In case of trials with time-to-event endpoints, sample size calculations are well-studied under the assumption of proportional hazards or when the endpoint of interest follows an exponential distribution. When prior evidence suggests otherwise, using traditional approaches may lead to inefficiently designed and underpowered studies. In such situations, a recently introduced frequentist approach proposes a sample size calculation for a fixed two-arm trial based on the accelerated failure time model thereby allowing nonproportional hazards and can be utilized for any distribution from the generalized gamma family. Advances in the field of clinical trials research have focused on the need for adaptive phase III designs with complex features, however, existing methods in literature have ignored the nonproportional hazards scenario. In this article, we propose a Bayesian adaptive design for a multi-arm phase III trial with nonproportional hazards allowing many complex features such as incorporation of prior knowledge of early phase studies, arms dropping, and response adaptive randomization. We extend the frequentist approach utilizing a generalized gamma distribution to a Bayesian setting while simultaneously addressing one of the key limitations of the frequentist approach. Extensive simulations are performed to study the operation characteristics of the proposed design using two examples representing real-life applications.

Time, cause of early neonatal death, and its predictors among neonates admitted to neonatal intensive care units at Bahir Dar City public hospitals, northwest Ethiopia: a prospective follow-up study.

Globally, 75% of neonatal deaths occur during the first weeks of life and more than 43% of deaths are covered by sub-Saharan Africa. Health-related policymakers and decision-makers need to use evidence-based treatments to reduce the time to early neonatal death and associated predictors. However, there are limited studies on median survival time, cause, incidence, and predictors in the study area as well as the country. Therefore, the aim of the present study was to assess time, the cause of early neonatal death, and its predictors among neonates admitted to neonatal intensive care units at Bahir Dar City public hospitals in northwest Ethiopia. An institution-based prospective follow-up study design was conducted among 387 early neonates selected by systematic sampling between 22 February and 22 April 2023. Statistical software, Epi Data version 4.6 and Stata version 14, was used for entry and analysis, respectively. Proportional hazard assumption and model fitness were checked by the Schoenfeld residual test and the Cox-Snell residual test, respectively. Descriptive statistics, the Kaplan-Meier curve, and the life table were used to describe variables. The Cox regression analysis model was fitted to identify the predictors of early neonatal death. During the follow-up time, 59 (15.25%) early neonates died, with an incidence of 31.79 per 1,000 early neonate days [95% confidence interval (CI): 0.024-0.041]. The leading causes of early neonatal death were prematurity complications, asphyxia, sepsis, meconium aspiration syndrome, and necrotizing enterocolitis. The mean survival time was 2.72 days. Being born from a multigravida mother [adjusted hazard ratio (AHR) 4.34; 95% CI: 1.63-11.55], a grand multigravida mother (AHR 3.50; 95% CI: 1.12-10.95), respiratory distress syndrome (AHR 2.60; 95% CI: 1.03-6.58), birth asphyxia (AHR 7.51; 95% CI: 2.30-24.51), a small gestational age (AHR 2.05; 95% CI: 1.08-4.92), and being unable to exclusively breastfeed (AHR 3.46; 95% CI: 1.52-7.88) were significantly associated predictors for time to early neonatal death. The incidence of early neonatal death was high, and the mean survival time was 2.72 days. Gravidity, respiratory distress syndrome, birth asphyxia, and being unable to exclusively breastfeed were identified as predictors of early neonatal death. Therefore, future research will consist of long-term prospective follow-up studies at a multicenter, nationwide level.

Ramucirumab plus paclitaxel as switch maintenance versus continuation of oxaliplatin-based chemotherapy in patients (pts) with advanced HER2-negative gastric or gastroesophageal junction (GEJ) cancer: The ARMANI phase III trial.

LBA4002 Background: In pts with HER2-negative advanced gastric/GEJ cancer and PD-L1 low/absent expression, platinum/fluoropyrimidine doublets are a standard first-line therapy. In this patient population, the outcomes are unsatisfactory and second-line therapy is given in only 40% of clinical trial patients. Switch consolidation maintenance may prolong the benefit of the initial strategy and delay clinical deterioration. Despite ramucirumab failing to prolong both progression-free survival (PFS) and overall survival (OS) in the first-line setting, paclitaxel plus ramucirumab is a standard second-line therapy and warrants investigation as a post-induction strategy. Methods: Pts with HER2-negative advanced gastric/GEJ cancer without disease progression after 3 months of initial oxaliplatin-based chemotherapy, stratified by site of origin (GEJ vs gastric), prior gastrectomy and peritoneal disease, were randomized 1:1 to ramucirumab 8 mg/Kg on days 1,15 plus paclitaxel 80 mg/sqm on days 1,8,15 every 28 days (arm A) vs CAPOX/FOLFOX at the same doses used in the last induction cycle, for additional 3 mos followed by fluoropyrimidine monotherapy maintenance (arm B). The primary endpoint was PFS, OS was a key secondary endpoint; quality of life, safety, and biomarkers were evaluated. A sample size of 280 pts achieved a 90% power to detect as significant at a 5% level (2-sided log-rank test) a median PFS increase from 4 to 6 mos (target HR=0.67). HRs were estimated by Cox models adjusting for stratification factors. Restricted Mean Survival Time (RMST) analysis was conducted in case of violation of proportional hazards assumption. Results: From Jan 2017 to Oct 2023, 280 patients were randomly assigned (144 arm A/136 arm B). Baseline characteristics were: male sex 67/61%, median age 64/66 years, PS 0 74/65%, GEJ 26/26%, prior gastrectomy 28/23%, peritoneal metastases 53/42%. At a median follow-up of 43.7 months (IQR 22.0-57.9), median PFS was 6.6 vs. 3.5 mos in Arm A vs. B (HR=0.63, 95%CI 0.49-0.81; P&lt;0.001). 24-mos RMST analysis showed a statistically significant 2.4-mos average increment (p=0.002). Median OS was 12.6 vs. 10.4 mos in Arm A vs. B (HR=0.75, 95%CI 0.58-0.97; P=0.030). The frequency of grade ≥3 adverse events was 40.4% vs. 20.7% in arms A vs. B, respectively, mainly neutropenia 25.5/9.6%; febrile neutropenia 2.1/0%; hypertension 6.4/0%; venous thromboembolism 2.1/0%; peripheral neuropathy 5.7/6.7%. No treatment-related deaths were reported. Conclusions: Switch maintenance with paclitaxel plus ramucirumab after 3 months of oxaliplatin-based doublets may be a new strategy in patients with HER2-negative metastatic gastric/GEJ cancer who are non-eligible for initial immune checkpoint inhibitor-based regimens according to specific guidelines and regulatory approvals. Clinical trial information: NCT02934464 .

Two-stage randomized clinical trials with a right-censored endpoint: Comparison of frequentist and Bayesian adaptive designs.

Adaptive randomized clinical trials are of major interest when dealing with a time-to-event outcome in a prolonged observation window. No consensus exists either to define stopping boundaries or to combine values or test statistics in the terminal analysis in the case of a frequentist design and sample size adaptation. In a one-sided setting, we compared three frequentist approaches using stopping boundaries relying on -spending functions and a Bayesian monitoring setting with boundaries based on the posterior distribution of the log-hazard ratio. All designs comprised a single interim analysis with an efficacy stopping rule and the possibility of sample size adaptation at this interim step. Three frequentist approaches were defined based on the terminal analysis: combination of stagewise statistics (Wassmer) or of values (Desseaux), or on patientwise splitting (Jörgens), and we compared the results with those of the Bayesian monitoring approach (Freedman). These different approaches were evaluated in a simulation study and then illustrated on a real dataset from a randomized clinical trial conducted in elderly patients with chronic lymphocytic leukemia. All approaches controlled for the type I error rate, except for the Bayesian monitoring approach, and yielded satisfactory power. It appears that the frequentist approaches are the best in underpowered trials. The power of all the approaches was affected by the violation of the proportional hazards (PH) assumption. For adaptive designs with a survival endpoint and a one-sided alternative hypothesis, the Wassmer and Jörgens approaches after sample size adaptation should be preferred, unless violation of PH is suspected.

Phase III Randomized, Placebo-Controlled Trial of Endocrine Therapy ± 1 Year of Everolimus in Patients With High-Risk, Hormone Receptor-Positive, Early-Stage Breast Cancer.

Phosphatidylinositol 3-kinase/AKT-serine threonine kinase/mammalian target of rapamycin (mTOR) pathway abnormalities contribute to endocrine resistance. Everolimus, an mTOR inhibitor, improved progression-free survival in hormone receptor-positive metastatic breast cancer (BC) when combined with endocrine therapy (ET). In this phase III randomized, placebo-controlled trial, we assessed the efficacy of everolimus + ET as adjuvant therapy in high-risk, hormone receptor-positive, human epidermal growth factor receptor 2-negative BC after adjuvant/neoadjuvant chemotherapy. Patients were randomly assigned 1:1 to physician's choice ET and 1 year of everolimus (10 mg orally once daily) or placebo stratified by risk group. The primary end point was invasive disease-free survival (IDFS) evaluated by a stratified log-rank test with the hazard ratio (HR) estimated by Cox regression. Subset analyses included preplanned evaluation by risk group and exploratory analyses by menopausal status and age. Secondary end points included overall survival (OS) and safety. Everolimus did not improve IDFS/OS when added to ET in patients with early-stage high-risk, hormone receptor-positive BC. One thousand and nine hundred thirty-nine patients were randomly assigned with 1,792 eligible for analysis. Overall, no benefit of everolimus was seen for IDFS (HR, 0.94 [95% CI, 0.77 to 1.14]) or OS (HR, 0.97 [95% CI, 0.75 to 1.26]). The assumption of proportional hazards was not met suggesting significant variability in the HR over time since the start of treatment. In an unplanned subgroup analysis among postmenopausal patients (N = 1,221), no difference in IDFS (HR, 1.08 [95% CI, 0.86 to 1.36]) or OS (HR, 1.19 [95% CI, 0.89 to 1.60]) was seen. In premenopausal patients (N = 571), everolimus improved both IDFS (HR, 0.64 [95% CI, 0.44 to 0.94]) and OS (HR, 0.49 [95% CI, 0.28 to 0.86]). Treatment completion rates were lower in the everolimus arm compared with placebo (48% v 73%) with higher grade 3 and 4 adverse events (35% v 7%). One year of adjuvant everolimus + ET did not improve overall outcomes. Subset analysis suggests mTOR inhibition as a possible target for patients who remain premenopausal after chemotherapy.

Neoadjuvant and perioperative immunotherapy in resectable non-small cell lung cancer (NSCLC): A systematic review and extracted individual patient data meta-analysis.

8045 Background: Neoadjuvant and perioperative immunotherapy are emerging approaches for resectable NSCLC. However, survival outcomes are still immature and subgroup analyses are underpowered. We report extracted individual patient (pt) data (eIPD) and trial-level (TL) meta-analyses of phase II and III randomized controlled trials (RCTs) in this setting. Methods: The systematic review included Cochrane, Embase, and major oncology conferences (ASCO annual meetings, ESMO meetings, WCLC meetings). Primary objectives were eIPD event-free survival (EFS) and overall survival (OS). Secondary objectives included eIPD and TL meta-analysis of subgroups. Kaplan-Meier plots of time-to-event outcomes were reconstructed with WebPlotDigitizer (v4.6, 2022), and eIPD was estimated with IPDfromKM (v0.1.10, 2020) stratified by study. Comparisons between arms were made in a 1-stage model with a Cox Proportional Hazards model stratified by study. The difference of restricted mean survival time (D-RMST), a quantification of the postponement of an event during a specified interval, was used to compare survival when the proportional hazard assumption (PHA) was violated, tau being the shortest follow-up time of the available trials. TL meta-analysis was performed with a random effects model. This meta-analysis was registered in the PROSPERO database under CRD42024502150. Results: Seven RCTs (AEGEAN, CM816, CM77T, KN671, NADIM II, NeoTorch, and Lei et al. [ESMO IOTECH 2022, #56O]) were identified, comprising 2995 pts. EFS analysis included all pts, with HR of 0.58 (0.52-0.65; p&lt;0.01). OS analysis (1645 evaluable pts from 4 trials) showed a D-RMST of 5.17 mo. (p&lt;0.01) due to PHA violation. Full eIPD analysis in the table. TL meta-analysis showed benefit in all subgroups, including PD-L1 expression, histology, stage, smoking status, sex, and age. TL EFS and OS results were comparable to results obtained from eIPD analysis, with low heterogeneity measures. Conclusions: This meta-analysis provides robust and nuanced insights into the positive impact of immunotherapy in resectable NSCLC. While evidence supports its efficacy, uncertainty surrounding the benefit in stage &lt; III disease highlights the need for additional research and more mature results to guide clinical decision-making effectively. [Table: see text]