Lost in the plot: missing visual elements in Kaplan-Meier plots of phase III oncology trials.

Missing visual elements (MVE) in Kaplan-Meier (KM) curves can misrepresent data, preclude curve reconstruction, and hamper transparency. This study evaluated KM plots of phase III oncology trials. MVE were defined as an incomplete y-axis range or missing number at risk table in a KM curve. Surrogate endpoint KM curves were additionally evaluated for complete interpretability, defined by (1) reporting the number of censored patients and (2) correspondence of the disease assessment interval with the number at risk interval. Among 641 trials enrolling 518 235 patients, 116 trials (18%) had MVE in KM curves. Industry sponsorship, larger trials, and more recently published trials were correlated with lower odds of MVE. Only 3% of trials (15 of 574) published surrogate endpoint KM plots with complete interpretability. Improvements in the quality of KM curves of phase III oncology trials, particularly for surrogate endpoints, are needed for greater interpretability, reproducibility, and transparency in oncology research.

Clinical effectiveness and safety of olaparib in BRCA-mutated, HER2-negative metastatic breast cancer in a real-world setting: final analysis of LUCY.

PURPOSE: The interim analysis of the phase IIIb LUCY trial demonstrated the clinical effectiveness of olaparib in patients with germline BRCA-mutated (gBRCAm), human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancer (mBC), with median progression-free survival (PFS) of 8.11 months, which was similar to that in the olaparib arm of the phase III OlympiAD trial (7.03 months). This prespecified analysis provides final overall survival (OS) and safety data. METHODS: The open-label, single-arm LUCY trial of olaparib (300 mg, twice daily) enrolled adults with gBRCAm or somatic BRCA-mutated (sBRCAm), HER2-negative mBC. Patients had previously received a taxane or anthracycline for neoadjuvant/adjuvant or metastatic disease and up to two lines of chemotherapy for mBC. RESULTS: Of 563 patients screened, 256 (gBRCAm, n = 253; sBRCAm, n = 3) were enrolled. In the gBRCAm cohort, median investigator-assessed PFS (primary endpoint) was 8.18 months and median OS was 24.94 months. Olaparib was clinically effective in all prespecified subgroups: hormone receptor status, previous chemotherapy for mBC, previous platinum-based chemotherapy (including by line of therapy), and previous cyclin-dependent kinase 4/6 inhibitor use. The most frequent treatment-emergent adverse events (TEAEs) were nausea (55.3%) and anemia (39.2%). Few patients (6.3%) discontinued olaparib owing to a TEAE. No deaths associated with AEs occurred during the study treatment or 30-day follow-up. CONCLUSION: The LUCY patient population reflects a real-world population in line with the licensed indication of olaparib in mBC. These findings support the clinical effectiveness and safety of olaparib in patients with gBRCAm, HER2-negative mBC. CLINICAL TRIAL REGISTRATION: Clinical trials registration number: NCT03286842.

Beyond Hormones: Investigating the Impact of Progesterone Receptor Membrane Component 1 in Lung Adenocarcinoma.

Progesterone Receptor Membrane Component 1 (PGRMC1) is a candidate oncogene with a prominent involvement in the pathogenesis of diverse cancers (ovarian, thyroid, breast, colon, head, and neck). Our study ascertains the ability of PGRMC1 to influence WNT members in the non-small cell lung cancer subtype-lung adenocarcinoma (LUAD) and participates in augmented cell proliferation and migration. Both computational and in vitro experimental analyses were performed in this study. Gene silencing, in vitro assays, gene expression & and protein expression studies were performed to ascertain the role of PGRMC1 in LUAD cells. The computational analysis, PGRMC1 gene level expression was analysed using the microarray gene expression omnibus datasets (GSE27262; GSE18842) to compare LUAD tumours and normal tissues. Concurrently, the gene expression profiling interactive analysis of PGRMC1 and Kaplan-Meier survival analysis revealed a decreasing patient survival rate with an increasing PGRMC1 gene expression in LUAD tumour samples. Interestingly, the experimental gene silencing studies were conducted in vitro (si-PGRMC1 Vs si-Control) to understand the essential role of PGRMC1 in regulating WNT-associated genes (WNT1, WNT5A, and WNT11). Comparative experimental cell migration and spheroid formation assays (si-PGRMC1 Vs si-Control) in vitro showed a strong association between PGRMC1 and LUAD. In vitro expression analysis using real-time PCR and western blot further confirmed the connecting link between PGRMC1 and WNT5A compared to other WNT member genes (WNT1 and WNT11) in LUAD. The computational and experimental analyses agreed with one another.

Studying the Outcomes in Patients with Tricuspid Regurgitation Treated with Valve Repair or Valve Replacement: Interpreting the Survival Pattern on The Long Term by Application of Artificial Intelligence Methods.

Background: The reconstruction of individual patient data from published Kaplan-Meier survival curves is a new technique (often denoted as the IPDfromKM method) for studying efficacy in cases where multiple trials are available, and the endpoint is long-term mortality. In patients with tricuspid regurgitation, both valve repair and valve replacement have been proposed to improve prognosis; 6 controlled clinical trials (CTs) have been conducted to compare the two therapeutic options mentioned above. The objective of our analysis was to study these six trials through the application of the IPDfromKM method. Methods: In the present report, we applied the IPDfromKM method to carry out a pooled analysis of these 6 CTs to investigate the effectiveness of valve repair vs valve replacement and to assess the between-study heterogeneity from this clinical material. After reconstructing individual patient data from these 6 trials, patients treated with valve repair were pooled together and their Kaplan-Meier curve was generated. Likewise, patients treated with valve replacement were pooled together and their Kaplan-Meier curve was generated. Finally, these two curves were compared by standard survival statistics. The hazard ratio (HR) was determined; death from any cause was the endpoint. Results: These 6 CTs included a total of 552 patients; in each of these CTs, the patient group treated with valve repair was compared with another group treated with valve replacement. Our statistical results showed a significantly better survival for valve repair compared with valve replacement (HR, 0.6098; 95% confidence intervals (CI), 0.445 to 0.835; p = 0.002). Heterogeneity was found to be significant in the 6 patient arms undergoing replacement, but not in those undergoing valve repair. In valve replacement, the classification of patients in class III or IV of New York Heart Association (NYHA) was the main negative prognostic factor. Conclusions: Our analysis confirmed the methodological advantages of the IPDfromKM method in the indirect comparative analysis of multiple trials. These advantages include appropriate analysis of censored patients, original assessment of heterogeneity, and graphical presentation of the results, wherein individual patients retain an important role.

Patterns and treatment outcomes of primary bone tumors in children treated at tertiary referral hospital, Ethiopia.

BACKGROUND: Bone tumors account for approximately 6% of all cancers in children. Malignant bone tumors, commonly occurring in children and adolescents, are associated with high mortality and morbidity. The overall survival of children with primary malignant bone tumors is affected by the stage of disease, time of diagnosis, and treatment response. Despite advanced treatment modalities with chemotherapy, surgery, and radiotherapy, bone tumor is the third leading cause of death in children with malignancy. Patients with metastatic disease at diagnosis have poor outcomes compared to localized disease at presentation. The 5-year Overall Survival and event-free survival in children with primary malignant bone tumors were 85.2% and 69.2%. The study aimed to assess the clinicopathological profile and treatment outcomes of children with primary malignant bone tumors in our setup. MATERIALS AND METHODS: A hospital-based cross-sectional study was conducted on 95 children who met the inclusion criteria through structured questionnaire. The collected data were analyzed using a statistical package for social sciences (SPSS) version 25. P-value < 0.05 was considered to be statistically significant. Kaplan Meier survival estimate was used for overall and event-free survival analysis. RESULTS: A total of ninety-five patients met the study inclusion criteria and the median age at diagnosis with primary malignant bone tumors was 10 years, with an interquartile range of 8-12 years. The duration of the illness from the onset of symptoms to the oncologic treatment center ranges from three weeks to 2 years with a mean duration of five months. Swelling was the commonest presenting symptom accounting for 95.8% (n = 91). Lower extremity was the commonest primary site of involvement accounting for 55.8% (n = 53) of children with primary malignant bone tumors. Osteosarcoma was the commonest malignant bone tumor constituted 66.3% (n = 63), followed by Ewing sarcoma at 33.7% (n = 32). About 41.2% (n = 39) of children had metastatic disease at presentation and the lung was the commonest site of distant metastasis. The Kaplan Meier survival estimate analysis showed the 1-year and 5-year overall survival probabilities for all pediatric primary malignant bone tumor patients were 65% (95% CI: 0.3-0.56) and 38% (95% CI:0.19-0.47) respectively. The 1-year and 5-year event-free survival probabilities were 55% (95% CI: 0.32-0.73) and 33% (95% CI: 0.10-0.59). The stage of the disease at presentation had a significant association with the outcome (p = 0.023). CONCLUSION: Our study showed the mean duration of the illness from the onset of symptoms to the oncologic treatment center was 5 months ranging from 3 weeks to 2 years. More than one-third of the presented with metastatic disease at presentation. The 1-year and 5-year overall survival (OS) probabilities of children with primary malignant bone tumors were low in our setup compared to other studies.

Assessing the influence of graft loss on 4-year patient survival after simultaneous pancreas-kidney transplantation: Kaplan-Meier versus Competing Risk Analysis model.

BACKGROUND: Graft loss increases the risk of patient death after simultaneous pancreas-kidney (SPK) transplantation. The relative risk of each graft failure is complex due to the influence of several competing events. METHODS: This retrospective, single-center study compared 4-year patient survival according to the graft status using Kaplan-Meier (KM) and Competing Risk Analysis (CRA). Patient survival was also assessed according to five eras (Era 1: 2001-2003; Era 2: 2004-2006; Era 3: 2007-2009; Era 4: 2010-2012; Era 5: 2012-2015). RESULTS: Between 2000 and 2015, 432 SPK transplants were performed. Using KM, patient survival was 86.5% for patients without graft loss (n = 333), 93.4% for patients with pancreas graft loss (n = 46), 43.7% for patients with kidney graft loss (n = 16), and 25.4% for patients with pancreas and kidney graft loss (n = 37). Patient survival was underestimated using KM versus CRA methods in patients with pancreas and kidney graft losses (25.4% vs. 36.2%), respectively. Induction with lymphocyte depleting antibodies was associated with 81% reduced risk (HR.19, 95% CI.38-.98, p = .0048), while delayed kidney function (HR 2.94, 95% CI 1.09-7.95, p = .033) and surgical complications (HR 2.94, 95% CI 1.22-7.08, p = .016) were associated with higher risk of death. Four-year patient survival increased from Era 1 to Era 5 (79% vs. 87.9%, p = .047). CONCLUSION: In this cohort of patients, kidney graft loss, with or without pancreas graft loss, was associated with higher mortality after SPK transplantation. Compared to CRA, the KM model underestimated survival only among patients with pancreas and kidney graft losses. Patient survival increased over time.

SurvdigitizeR: an algorithm for automated survival curve digitization.

BACKGROUND: Decision analytic models and meta-analyses often rely on survival probabilities that are digitized from published Kaplan-Meier (KM) curves. However, manually extracting these probabilities from KM curves is time-consuming, expensive, and error-prone. We developed an efficient and accurate algorithm that automates extraction of survival probabilities from KM curves. METHODS: The automated digitization algorithm processes images from a JPG or PNG format, converts them in their hue, saturation, and lightness scale and uses optical character recognition to detect axis location and labels. It also uses a k-medoids clustering algorithm to separate multiple overlapping curves on the same figure. To validate performance, we generated survival plots form random time-to-event data from a sample size of 25, 50, 150, and 250, 1000 individuals split into 1,2, or 3 treatment arms. We assumed an exponential distribution and applied random censoring. We compared automated digitization and manual digitization performed by well-trained researchers. We calculated the root mean squared error (RMSE) at 100-time points for both methods. The algorithm's performance was also evaluated by Bland-Altman analysis for the agreement between automated and manual digitization on a real-world set of published KM curves. RESULTS: The automated digitizer accurately identified survival probabilities over time in the simulated KM curves. The average RMSE for automated digitization was 0.012, while manual digitization had an average RMSE of 0.014. Its performance was negatively correlated with the number of curves in a figure and the presence of censoring markers. In real-world scenarios, automated digitization and manual digitization showed very close agreement. CONCLUSIONS: The algorithm streamlines the digitization process and requires minimal user input. It effectively digitized KM curves in simulated and real-world scenarios, demonstrating accuracy comparable to conventional manual digitization. The algorithm has been developed as an open-source R package and as a Shiny application and is available on GitHub: https://github.com/Pechli-Lab/SurvdigitizeR and https://pechlilab.shinyapps.io/SurvdigitizeR/ .

Augmentation Therapy for Severe Alpha-1 Antitrypsin Deficiency Improves Survival and Is Decoupled from Spirometric Decline-A Multinational Registry Analysis.

Rationale: Intravenous plasma-purified alpha-1 antitrypsin (IV-AAT) has been used as therapy for alpha-1 antitrypsin deficiency (AATD) since 1987. Previous trials (RAPID and RAPID-OLE) demonstrated efficacy in preserving computed tomography of lung density but no effect on FEV1. This observational study evaluated 615 people with severe AATD from three countries with socialized health care (Ireland, Switzerland, and Austria), where access to standard medical care was equal but access to IV-AAT was not. Objectives: To assess the real-world longitudinal effects of IV-AAT. Methods: Pulmonary function and mortality data were utilized to perform longitudinal analyses on registry participants with severe AATD. Measurements and Main Results: IV-AAT confers a survival benefit in severe AATD (P < 0.001). We uncovered two distinct AATD phenotypes based on an initial respiratory diagnosis: lung index and non-lung index. Lung indexes demonstrated a more rapid FEV1 decline between the ages of 20 and 50 and subsequently entered a plateau phase of minimal decline from 50 onward. Consequentially, IV-AAT had no effect on FEV1 decline, except in patients with a Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage 2 lung index. Conclusions: This real-world study demonstrates a survival advantage from IV-AAT. This improved survival is largely decoupled from FEV1 decline. The observation that patients with severe AATD fall into two major phenotypes has implications for clinical trial design where FEV1 is a primary endpoint. Recruits into trials are typically older lung indexes entering the plateau phase and, therefore, unlikely to show spirometric benefits. IV-AAT attenuates spirometric decline in lung indexes in GOLD stage 2, a spirometric group commonly outside current IV-AAT commencement recommendations.

Analysis of the shorter drug survival times for Janus kinase inhibitors and interleukin-17 inhibitors compared with tumor necrosis factor inhibitors in a real-world cohort of axial spondyloarthritis patients - a retrospective analysis from the RHADAR network.

In recent years Janus kinase inhibitors (JAKi) have joined tumor necrosis factor inhibitors (TNFi) and interleukin (IL)-17 inhibitors (IL-17i) as approved disease modifying anti-rheumatic drugs (DMARD) for moderate to severe forms of axial spondyloarthritis (axSpA). Drug survival in axSpA patients has not been well studied in a real-world outpatient scenario since the approval of JAKi. We aimed to analyze the three drug classes based on modes of actions (MoA) for their persistence rates among German axSpA outpatients. A retrospective analysis of the RHADAR database for axSpA patients with a new initiation of TNFi, IL-17i, or JAKi treatment between January 2015 and October 2023 was conducted. Analyses included Kaplan-Meier curves and adjusted Cox regressions for drug discontinuation. 1222 new biological DMARD (TNFi [n = 954], IL-17i [n = 190]) or JAKi (n = 78) treatments were reported. The median drug survival was 31 months for TNFi, 25 for IL-17i, and 18 for JAKi. The corresponding 2-year drug survival rate was 79.6%, 72.6%, and 62.8% for TNFi, IL-17i, and JAKi, respectively. The probability for discontinuation for JAKi was significantly higher compared with TNFi (HR 1.91 [95% CI 1.22-2.99]) as well as for IL-17i compared with TNFi (HR 1.43 [95% CI 1.02-2.01]), possibly related to more frequent use of TNFis as first-line therapy. IL-17i and JAKi discontinuation probabilities were similar. Primary non-response was the reason for drug discontinuation in most cases across all MoA. TNFi treatment might persist longer than JAKi and IL-17i in German axSpA outpatients, possibly related to more severe or refractory disease in patients with JAKi-treated or IL-17i-treated axSpA.

Correlation between Charlson comorbidity index and surgical prognosis in elderly patients with femoral neck fractures: a retrospective study.

OBJECTIVE: Femoral neck fractures (FNF) are known to have significant morbidity and mortality rates. Multiple chronic conditions (MCC) are defined as the presence of two or more chronic diseases that greatly affect the quality of life in older adults. The aim of this study is to explore the impact of MCC and Charlson comorbidity index (CCI) on surgical outcomes in patients with FNF. METHODS: Patients with FNF who underwent joint replacement surgery were selected for this study. Patients who had two or more diseases simultaneously were divided into two groups: the MCC group and the non-MCC (NMCC) group. The CCI was calculated to assess the severity of patients' comorbidities in the MCC group. Baseline data, surgical details, and prognosis-related indicators were analyzed and compared between the two patient groups. Spearman correlation analysis was performed to assess the relationship between CCI and length of hospital stay, Harris score, skeletal muscle index (SMI), and age. Univariate and multivariate logistic regression analysis was conducted to identify the risk factors for mortality in FNF patients at 1 and 5 years after surgery. RESULTS: A total of 103 patients were included in the MCC group, while the NMCC group consisted of 40 patients. However, the patients in the MCC group were found to be older, had a higher incidence of sarcopenia, and lower SMI values (p < 0.001). Patients in the MCC group had longer hospitalization times, lower Harris scores, higher intensive care unit (ICU) admission rates, and higher complication rates (p = 0.045, p = 0.035, p = 0.019, p = 0.010). Spearman correlation analysis revealed that CCI was positively correlated with hospitalization and age (p < 0.001, p < 0.001), while it was negatively correlated with Harris score and SMI value (p < 0.001, p < 0.001). Univariate and multivariate logistic regression analysis demonstrated that MCC patients had higher 1-year and 5-year mortality rates. Hospitalization time was identified as a risk factor for death in FNF patients 1 year after joint replacement (p < 0.001), whereas CCI and age were identified as risk factors for death 5 years after surgery (p < 0.001, p < 0.001). Kaplan-Meier survival analysis results showed that the difference in death time between the two groups of patients with MCC and NMCC was statistically significant (p < 0.001). Cox proportional hazard model analysis showed that CCI, age and SMI were risk factors affecting patient death. CONCLUSION: The surgical prognosis of patients with MCC, CCI and FNF is related. The higher the CCI, the worse the patient's function and the higher the long-term risk of death.

Clinical Longevity of Obturators in Patients with Jaw Defects: a Retrospective Cohort Study.

OBJECTIVES: The primary objective of the present retrospective clinical study was to determine the survival time of obturators while analyzing possible influencing factors. MATERIALS AND METHODS: This retrospective clinical cohort study analyzed the influence of various clinical factors on the survival probability of obturators and their follow-up outcomes using Kaplan‒Meier analysis. RESULTS: A total of 76 patients with 115 obturators were included in the study (47 men and 29 women, mean age 58.1 ± 18.1 years). The mean observation time was 3.0 ± 4.5 years (maximum 26.3 years). A total of 40.9% (47) of all obturators observed had to be replaced. The survival rate after 5 years was 79.5% for telescopic-crown-retained tooth-supported obturators, 86.9% for telescopic-crown-retained implant-supported obturators, 58.8% for removable full denture obturators, 22.1% for clasp-retained obturators and 0.0% for splints. The type of attachment, attendance at a regular follow-up and defect cause significantly influenced the survival of the obturators (p < .05). CONCLUSIONS: The findings obtained in this study support the recommendation of using implant-supported obturators. Telescopic-crown attachments, either tooth- or implant-supported, seem to be favorable in terms of survival time. Attendance at a strict follow-up program seems to have a major influence on the longevity of the obturators. CLINICAL RELEVANCE: The use of implant-supported obturators to cover permanent oral and maxillofacial defects is highly recommended. Additionally, the use of telescopic-crown attachments seems to be favorable in terms of survival time. Clasp-retained obturators and surgical splints should be used primarily for temporary restorations due to their shorter survival times.

Indications, Clinical Outcomes, and Re-Revisions Following Revision Total Hip Arthroplasty - Does Age Matter?

BACKGROUND: Younger age is associated with increased revision incidence following primary total hip arthroplasty, though the association between age and repeat revision following revision total hip arthroplasty (rTHA) has not been described. This study aimed to describe the incidences and indications for subsequent revision (re-revision) following rTHA based on age. METHODS: Patients undergoing aseptic rTHA from 2011 to 2021 with minimum 1-year follow-up were retrospectively reviewed. Patients were stratified into 3 groups based on age at the time of index rTHA (ie, <55 years, 55 to 74 years, and >74 years). Perioperative characteristics, complications, and re-revisions were compared between groups. RESULTS: Of 694 included rTHAs, those in the >74 age group were more likely to undergo rTHA for periprosthetic fracture (P < .001) while those in the <55 age group were more likely to undergo rTHA for metallosis/taper corrosion (P = .028). Readmissions (P = .759) and emergency department visits (P = .498) within 90 days were comparable across ages. Rates of re-revision were comparable at 90 days (P = .495), 1 year (P = .443), and 2 years (P = .204). Kaplan-Meier analysis of all-cause re-revision at latest follow-up showed a nonstatistically significant trend toward increasing re-revisions in the <55 and 55 to 74 age groups. Using logistic regressions, smoking and index rTHA for instability were independently associated with re-revision, while age at index surgery was not. CONCLUSIONS: While indications for rTHA differ across age groups, rates of 2-year re-revision are statistically comparable between groups. Further studies are warranted to understand the association between age, activity, and re-revision rates after 5 years postoperatively.

Survival Analysis Without Sharing of Individual Patient Data by Using a Gaussian Copula.

Cox regression and Kaplan-Meier estimations are often needed in clinical research and this requires access to individual patient data (IPD). However, IPD cannot always be shared because of privacy or proprietary restrictions, which complicates the making of such estimations. We propose a method that generates pseudodata replacing the IPD by only sharing non-disclosive aggregates such as IPD marginal moments and a correlation matrix. Such aggregates are collected by a central computer and input as parameters to a Gaussian copula (GC) that generates the pseudodata. Survival inferences are computed on the pseudodata as if it were the IPD. Using practical examples we demonstrate the utility of the method, via the amount of IPD inferential content recoverable by the GC. We compare GC to a summary-based meta-analysis and an IPD bootstrap distributed across several centers. Other pseudodata approaches are also considered. In the empirical results, GC approximates the utility of the IPD bootstrap although it might yield more conservative inferences and it might have limitations in subgroup analyses. Overall, GC avoids many legal problems related to IPD privacy or property while enabling approximation of common IPD survival analyses otherwise difficult to conduct. Sharing more IPD aggregates than is currently practiced could facilitate "second purpose"-research and relax concerns regarding IPD access.

Comparison of nonparametric estimators of the expected number of recurrent events.

We compare the performance of nonparametric estimators for the mean number of recurrent events and provide a systematic overview for different recurrent event settings. The mean number of recurrent events is an easily interpreted marginal feature often used for treatment comparisons in clinical trials. Incomplete observations, dependencies between successive events, terminating events acting as competing risk, or gaps between at risk periods complicate the estimation. We use survival multistate models to represent different complex recurrent event situations, profiting from recent advances in nonparametric estimation for non-Markov multistate models, and explain several estimators by using multistate intensity processes, including the common Nelson-Aalen-type estimators with and without competing mortality. In addition to building on estimation of state occupation probabilities in non-Markov models, we consider a simple extension of the Nelson-Aalen estimator by allowing for dependence on the number of prior recurrent events. We pay particular attention to the assumptions required for the censoring mechanism, one issue being that some settings require the censoring process to be entirely unrelated while others allow for state-dependent or event-driven censoring. We conducted extensive simulation studies to compare the estimators in various complex situations with recurrent events. Our practical example deals with recurrent chronic obstructive pulmonary disease exacerbations in a clinical study, which will also be used to illustrate two-sample-inference using resampling.

Testing for Sufficient Follow-Up in Censored Survival Data by Using Extremes.

In survival analysis, it often happens that some individuals, referred to as cured individuals, never experience the event of interest. When analyzing time-to-event data with a cure fraction, it is crucial to check the assumption of "sufficient follow-up," which means that the right extreme of the censoring time distribution is larger than that of the survival time distribution for the noncured individuals. However, the available methods to test this assumption are limited in the literature. In this article, we study the problem of testing whether follow-up is sufficient for light-tailed distributions and develop a simple novel test. The proposed test statistic compares an estimator of the noncure proportion under sufficient follow-up to one without the assumption of sufficient follow-up. A bootstrap procedure is employed to approximate the critical values of the test. We also carry out extensive simulations to evaluate the finite sample performance of the test and illustrate the practical use with applications to leukemia and breast cancer data sets.

Assocation between trapezium size and failure of total trapeziometacarpal prosthesis. A survival analysis.

AIMS: To assess the survival function of cementless total trapezium metacarpal prostheses (TTMPs) at 20 years, to compare survival functions by trapezium size, and to evaluate the association between the instantaneous risk of TTMP failure and small trapezium size using a multivariate Cox regression model. METHODS: This observational cohort study included 221 consecutive patients with a mean follow-up after TTMP of 137.3 months (maximum of 246 months). Kaplan-Meier and actuarial life-table methods were used to evaluate the survival function of thecohort. Kaplan-Meier survival curves were compared by trapezium size. Multivariate Cox regression analysis was used to determine the effect of potential confounders on the association between small trapezium and the instantaneous risk of TTMP failure. RESULTS: At the end of follow-up, there was a 89.01% chance of the TTMP surviving for 246 months or more. There was an association between TTMP survival time and trapezium size showing a significant trend such that the survival curves weresignificantly higher with larger trapezium size (Mantel-Cox test, p = 0.0001; WilcoxonBreslow test, p = 0.0002; Tarone-Ware test, p = 0.0001).The unadjusted Cox regression model showed a significant association between small trapezium size (smaller than 9 mm) and the instantaneous risk of TTPM failure (HR: 7.37, 95% CI: 2.46-22.07). In the multivariate Cox analysis, "age", "trapezium morphology", and "complications" were confounders in the association between small trapezium size and the hazard ratio of prosthetic failure (HR = 3.76; 95% CI 0.96 to 13.82). CONCLUSION: These results confirm the long-term functional survival of TTMP prostheses and reveal a significant increase in trend of the survival curve with larger trapezium size. Patient age, trapezium morphology, and the presence of post-surgical complications are confounders in the association between small trapezium size and the hazard ratio of TTMP failure.

On the role of Volterra integral equations in self-consistent, product-limit, inverse probability of censoring weighted, and redistribution-to-the-right estimators for the survival function.

This paper reconsiders several results of historical and current importance to nonparametric estimation of the survival distribution for failure in the presence of right-censored observation times, demonstrating in particular how Volterra integral equations help inter-connect the resulting estimators. The paper begins by considering Efron's self-consistency equation, introduced in a seminal 1967 Berkeley symposium paper. Novel insights provided in the current work include the observations that (i) the self-consistency equation leads directly to an anticipating Volterra integral equation whose solution is given by a product-limit estimator for the censoring survival function; (ii) a definition used in this argument immediately establishes the familiar product-limit estimator for the failure survival function; (iii) the usual Volterra integral equation for the product-limit estimator of the failure survival function leads to an immediate and simple proof that it can be represented as an inverse probability of censoring weighted estimator; (iv) a simple identity characterizes the relationship between natural inverse probability of censoring weighted estimators for the survival and distribution functions of failure; (v) the resulting inverse probability of censoring weighted estimators, attributed to a highly influential 1992 paper of Robins and Rotnitzky, were implicitly introduced in Efron's 1967 paper in its development of the redistribution-to-the-right algorithm. All results developed herein allow for ties between failure and/or censored observations.

RKHS-based covariate balancing for survival causal effect estimation.

Survival causal effect estimation based on right-censored data is of key interest in both survival analysis and causal inference. Propensity score weighting is one of the most popular methods in the literature. However, since it involves the inverse of propensity score estimates, its practical performance may be very unstable, especially when the covariate overlap is limited between treatment and control groups. To address this problem, a covariate balancing method is developed in this paper to estimate the counterfactual survival function. The proposed method is nonparametric and balances covariates in a reproducing kernel Hilbert space (RKHS) via weights that are counterparts of inverse propensity scores. The uniform rate of convergence for the proposed estimator is shown to be the same as that for the classical Kaplan-Meier estimator. The appealing practical performance of the proposed method is demonstrated by a simulation study as well as two real data applications to study the causal effect of smoking on survival time of stroke patients and that of endotoxin on survival time for female patients with lung cancer respectively.

Optimal survival analyses with prevalent and incident patients.

Period-prevalent cohorts are often used for their cost-saving potential in epidemiological studies of survival outcomes. Under this design, prevalent patients allow for evaluations of long-term survival outcomes without the need for long follow-up, whereas incident patients allow for evaluations of short-term survival outcomes without the issue of left-truncation. In most period-prevalent survival analyses from the existing literature, patients have been recruited to achieve an overall sample size, with little attention given to the relative frequencies of prevalent and incident patients and their statistical implications. Furthermore, there are no existing methods available to rigorously quantify the impact of these relative frequencies on estimation and inference and incorporate this information into study design strategies. To address these gaps, we develop an approach to identify the optimal mix of prevalent and incident patients that maximizes precision over the entire estimated survival curve, subject to a flexible weighting scheme. In addition, we prove that inference based on the weighted log-rank test or Cox proportional hazards model is most powerful with an entirely prevalent or incident cohort, and we derive theoretical formulas to determine the optimal choice. Simulations confirm the validity of the proposed optimization criteria and show that substantial efficiency gains can be achieved by recruiting the optimal mix of prevalent and incident patients. The proposed methods are applied to assess waitlist outcomes among kidney transplant candidates.

Survival Probability in Multidrug Resistant Pulmonary Tuberculosis Patients in a South Indian Region.

Background: Drug-resistant tuberculosis is a burgeoning threat to public health requiring novel strategies to combat the infection. Although national tuberculosis elimination programs focus on improving health services, challenges in eradicating tuberculosis still exist. Factors attributing to unfavorable outcomes are unknown in Warangal district of Telangana state. Methods: This study included 296 patients diagnosed with multidrug-resistant pulmonary tuberculosis. The study participants followed up for a maximum of 20 months to determine treatment outcomes. Statistical applications of Kaplan-Meier curve and log-rank test used to find the survival probabilities in subgroups. Results: The survival of multidrug-resistant pulmonary tuberculosis patients was ascertained, in male and female patients, aged between 31 and 50 years. Resistance to rifampicin was prominent. The study found a survival rate of 76.68% and a mortality rate of 23.31%. The log-rank test revealed a significant difference in survival in subcategories with and without comorbidities (P = .03), non-adherence to treatment (P = .0001), treatment duration (P = .02), regimens (P = .01), and grading of radiograph (P = .0001). Conclusion: This study identified factors that influenced the survival probability of multidrug-resistant pulmonary tuberculosis patients, including comorbidities, weight band, non-adherence to treatment, treatment duration, regimens, and grading of radiograph. These findings emphasize the need for enhanced management strategies to improve treatment outcomes.