Hazard Rate Research Articles

Some New Results on Stochastic Comparisons of Spacings of Generalized Order Statistics from One and Two Samples

Generalized order statistics (GOSs) are often adopted as a tool for providing a unified approach to several stochastic models dealing with ordered random variables. In this contribution, we first recall various useful results based on the notion of total positivity. Then, some stochastic comparisons between spacings of GOSs from one sample, as well as two samples, are developed under the more general assumptions on the parameters of the model. Specifically, the given results deal with the likelihood ratio order, the hazard rate order and the mean residual life order. Finally, an application is demonstrated for sequential systems.

Preoperative use of angiotensin-converting enzyme inhibitors, angiotensin II receptor blockers and diuretics increases the risk of dehydration after ileostomy formation: population-based cohort study.

Readmission rates following ileostomy formation are high. Dehydration and consecutive renal failure are common causes of readmission, potentially pronounced by drugs affecting the homeostasis. The aim of the study was to assess the risk of dehydration after ileostomy formation in patients treated with angiotensin-converting enzyme inhibitors (ACEI), angiotensin II receptor blockers (ARB) or diuretics. This nationwide population-based cohort study used data derived from the Colorectal Cancer Data Base of several Swedish healthcare registers. The study included all patients operated on with elective anterior resection and temporary ileostomy for rectal cancer clinically staged I-III in Sweden in 2007-2016. Exposure was at least two dispensations of ACEI, ARB or diuretics within 1 year prior to surgery. Outcome was 90-day readmission due to dehydration including acute renal failure. In total, 3252 patients were included with 1173 (36.1%) exposed to ACEI, ARB or diuretics. The cumulative incidence for 90-day readmission due to dehydration was 29.0% (151 of 520) for exposed versus 13.8% (98 of 712) for unexposed. The proportion of readmissions due to any reason was 44.3% (520 of 1173) for exposed compared to 34.2% (712 of 2079) for unexposed. The incidence rate ratio for readmission due to dehydration was 2.83 (95% c.i. 2.21 to 3.63, P < 0.001). The hazard rate ratio was 2.45 (95% c.i. 1.83 to 3.27, P < 0.001) after adjusting for age, gender and comorbidity. Medication with ACEI, ARB or diuretics defines a vulnerable patient group with increased risk of readmission due to dehydration after ileostomy formation.

Clinical biomarkers for thyroid immune-related adverse events in patients with stage III and IV gastrointestinal tumors.

Thyroid immune-related adverse events (irAEs) associated with immune checkpoint inhibitor (ICI) treatment appear to correlate with a better prognosis. We aimed to investigate clinical biomarkers associated with thyroid irAEs. We retrospectively analyzed data from 129 patients receiving programmed cell death protein 1 (PD-1) inhibitors for stage III and IV gastrointestinal tumors. Patients were divided into two groups: "thyroid irAEs" group and "no thyroid irAEs" group. We compared continuous variables using Mann-Whitney U and Kruskal-Wallis tests and categorical variables using Pearson's chi-square test. Survival curves were generated using the Kaplan-Meier method, and associations between clinical features and thyroid irAEs were assessed using univariate and multivariate logistic regression models. Associations for thyroid irAEs and outcomes [progression-free survival (PFS), overall survival (OS)] of the patients were performed with a Cox proportional hazard model. A total of 129 patients, including 66 gastric cancer, 30 esophageal squamous cell carcinoma, and 33 hepatocellular carcinoma (HCC), were involved in this analysis with 47 cases of thyroid irAEs occurrence. The Cox proportional hazard model analysis confirmed the extended PFS [hazard rate (HR) = 0.447, 95% confidence interval (CI): 0.215 to 0.931, p = 0.031] and OS (HR = 0.424, 95% CI: 0.201 to 0.893, p = 0.024) for thyroid irAEs group when compared with those of the no thyroid irAEs group. Association between thyroid irAEs and clinical characteristics at baseline was analyzed subsequently by univariate analysis. Higher body mass index (p = 0.005), increased eosinophil count (p = 0.014), increased lactate dehydrogenase (p = 0.008), higher baseline thyroid stimulating hormone (TSH) (p = 0.001), HCC (p = 0.001) and increased adenosine deaminase (ADA) (p = 0.001) were linked with thyroid irAEs occurrence. The multivariable logistic regression model indicated that ADA [odds rate (OR) = 4.756, 95% CI: 1.147 to 19.729, p = 0.032] was independently associated with thyroid irAEs occurrence. Increased baseline level of ADA was associated with thyroid irAEs occurrence in patients with advanced gastrointestinal tumors who received ICI treatment. In the case of abnormal ADA, attention should be paid to the risk of thyroid irAEs.

Orderings of extremes among dependent extended Weibull random variables

Abstract In this work, we consider two sets of dependent variables $\{X_{1},\ldots,X_{n}\}$ and $\{Y_{1},\ldots,Y_{n}\}$ , where $X_{i}\sim EW(\alpha_{i},\lambda_{i},k_{i})$ and $Y_{i}\sim EW(\beta_{i},\mu_{i},l_{i})$ , for $i=1,\ldots, n$ , which are coupled by Archimedean copulas having different generators. We then establish different inequalities between two extremes, namely, $X_{1:n}$ and $Y_{1:n}$ and $X_{n:n}$ and $Y_{n:n}$ , in terms of the usual stochastic, star, Lorenz, hazard rate, reversed hazard rate and dispersive orders. Several examples and counterexamples are presented for illustrating all the results established here. Some of the results here extend the existing results of [5] (Barmalzan, G., Ayat, S.M., Balakrishnan, N., &amp; Roozegar, R. (2020). Stochastic comparisons of series and parallel systems with dependent heterogeneous extended exponential components under Archimedean copula. Journal of Computational and Applied Mathematics380: Article No. 112965).

Competing risks and multivariate outcomes in epidemiological and clinical trial research.

Data analysis methods for the study of treatments or exposures in relation to a clinical outcome in the presence of competing risks have a long history, often with inference targets that are hypothetical, thereby requiring strong assumptions for identifiability with available data. Here data analysis methods are considered that are based on single and higher dimensional marginal hazard rates, quantities that are identifiable under standard independent censoring assumptions. These lead naturally to joint survival function estimators for outcomes of interest, including competing risk outcomes, and provide the basis for addressing a variety of data analysis questions. These methods will be illustrated using simulations and Women's Health Initiative cohort and clinical trial data sets, and additional research needs will be described.

Quality of early stroke care and long-term mortality in patients with acute stroke: A nationwide follow-up study.

High quality of early stroke care is essential for optimizing the chance of a good patient outcome. The quality of care may be monitored by process performance measures (PPMs) and previous studies have found an association between fulfilment of PPMs and short-term mortality. However, the association with long-term mortality remains to be determined. We aimed to evaluate the association between fulfilment of PPMs and long-term mortality for patients with acute stroke in Denmark. We used data from Danish health care registers between 2008 and 2020 to identify all patients admitted with incident stroke (haemorrhagic (ICH) or ischaemic stroke). The quality of early stroke care was assessed using 10 PPMs. Mortality was compared using Cox proportional hazard ratios, risk ratios computed using Poisson regression, and standardized relative survival. We included 102,742 patients; 9804 cases of ICH, 88,591 cases of ischaemic stroke, and 4347 cases of unspecified strokes. The cumulative 10-year mortality risk was 56.8%. Fulfilment of the individual PPMs was associated with adjusted hazard rate ratios of death between 0.76 and 0.96. Patients with 100% fulfilment of all PPMs had a lower 10-year post-stroke mortality (adjusted risk ratio 0.90) compared to the patients with 0%-49% fulfilment and a standardized relative survival of 81.3%, compared to the general population. High quality of early stroke care was associated with lower long-term mortality following both ICH and ischaemic stroke, which emphasizes the importance of continued attention on the ability of stroke care providers to deliver high quality of early care.

A transformer model for cause-specific hazard prediction

BackgroudModelling discrete-time cause-specific hazards in the presence of competing events and non-proportional hazards is a challenging task in many domains. Survival analysis in longitudinal cohorts often requires such models; notably when the data is gathered at discrete points in time and the predicted events display complex dynamics. Current models often rely on strong assumptions of proportional hazards, that is rarely verified in practice; or do not handle sequential data in a meaningful way. This study proposes a Transformer architecture for the prediction of cause-specific hazards in discrete-time competing risks. Contrary to Multilayer perceptrons that were already used for this task (DeepHit), the Transformer architecture is especially suited for handling complex relationships in sequential data, having displayed state-of-the-art performance in numerous tasks with few underlying assumptions on the task at hand.ResultsUsing synthetic datasets of 2000–50,000 patients, we showed that our Transformer model surpassed the CoxPH, PyDTS, and DeepHit models for the prediction of cause-specific hazard, especially when the proportional assumption did not hold. The error along simulated time outlined the ability of our model to anticipate the evolution of cause-specific hazards at later time steps where few events are observed. It was also superior to current models for prediction of dementia and other psychiatric conditions in the English longitudinal study of ageing cohort using the integrated brier score and the time-dependent concordance index. We also displayed the explainability of our model’s prediction using the integrated gradients method.ConclusionsOur model provided state-of-the-art prediction of cause-specific hazards, without adopting prior parametric assumptions on the hazard rates. It outperformed other models in non-proportional hazards settings for both the synthetic dataset and the longitudinal cohort study. We also observed that basic models such as CoxPH were more suited to extremely simple settings than deep learning models. Our model is therefore especially suited for survival analysis on longitudinal cohorts with complex dynamics of the covariate-to-outcome relationship, which are common in clinical practice. The integrated gradients provided the importance scores of input variables, which indicated variables guiding the model in its prediction. This model is ready to be utilized for time-to-event prediction in longitudinal cohorts.

Stochastic comparison results between two finite mixture models with generalized Weibull distributed components

In this paper, we establish sufficient conditions for stochastic comparisons of two finite mixture models (FMMs) with respect to the usual stochastic order, hazard rate order, and likelihood ratio order when the mixing components have generalized Weibull family of distributions. The established (sufficient) conditions are mainly based on the majorization order, weak supermajorization order, and weak submajorization order. The stochastic comparisons are studied when there is heterogeneity in one (model) parameter, and then in two parameters (model parameter and mixing proportion). Further, the concept of unordered majorization order is employed to establish the usual stochastic order between two FMMs. To illustrate the theoretical results established here, several numerical examples and counterexamples are presented. Finally, we have generalized some of the results to the case of τ-mixture models.

Abstract PO5-19-10: First oncological outcomes of HypoG-01: a UNICANCER phase III trial comparing loco-regional hypo vs normo fractionated radiation therapy in early breast cancer patients

Abstract Objective Normofractionated (NF) radiation therapy (RT) is still standard for loco-regional early breast cancer (EBC) in many countries. HypoG-01, a UNICANCER, non-inferiority, open-label, multicenter, randomized phase III trial (NCT03127995), conducted in parallel with the DBCG Skagen trial 1 (NCT02384733), evaluated hypofractionated (HF) RT with 40 Gy/15 fr (2.67 Gy/fr) versus NF RT 50 Gy/25 fr (2.0 Gy/fr). This is the first report of oncological outcomes, secondary endpoints of the trial. Methods Patients (pts) ≥18 years old were operated for T1-3, N0-3, M0 breast cancer. All pts received nodal and thoracic wall or breast RT. Tumor-bed boost (sequential or simultaneous) and nodal levels treated were decided according to local guidelines. Target volumes were delineated according to the ESTRO consensus. RT technique was left at the investigator’s discretion. Stratification factors included treating center, type of surgery, number of positive nodes and body mass index. The primary endpoint, reported previously, was time to occurrence of arm lymphedema. Oncological outcomes included locoregional relapse free survival (LRFS), invasive disease-free survival (IDFS), distant disease-free survival (DDFS), breast cancer specific survival (BCSS) and overall survival (OS) as defined per DATECAN guidelines. All time to cancer related endpoints were defined as starting from the date of randomization until the event. The primary statistic test was stratified one-sided logrank test: 5% significance level in per-protocol population (PPP) with a pre-specified non-inferiority margin of 1.545. Stratified Cox model was used for calculating hazard ratios of oncological outcomes. Results In total, 1265 pts were randomized to HF versus NF RT from Sep 2016 to Mar 2020 with 1221 in the PPP (HF group 614 pts (50.3%); NF group 607 (49.7%)), 5 consent withdrawn and 39 major deviations. Median age was 58 years (range 23-91), surgery included mastectomy (501 pts; 45%) and axillary clearance (921 pts; 82.8%). Sequential (67.8%) or simultaneous integrated (32.2%) tumor-bed boost was used in 596 pts (48.8%). With a median follow-up for OS in PP analysis of 3.8 years (95% CI 3.3 to 3.9), HF was non-inferior to NF RT in terms of lymphedema (HR=1.07; 90% CI 0.86-1.34, non-inferiority p=0.003). Table 1 reports the hazard ratio and 3-year survival rates for the oncological endpoints LRFS, IDFS, DDFS, BCCS and OS. There was no sign of disadvantage for any of these endpoints comparing HF to NF. Additional analyses will be presented at the meeting. Conclusion Moderately HF loco-regional RT is non-inferior to NF RT in terms of lymphedema risk in EBC and does not show a disadvantage in terms of LRFS, IDFS, DDFS, BCCS and OS with a median follow-up of 3.8 years. Together with the Skagen 1 trial, this study provides level 1A evidence supporting the use of 40 Gy/15 fr for loco-regional radiation therapy in EBC with respect to arm lymphedema risk; Table 1: Oncological outcomes according to treatment arm in the per protocol analysis HF: Moderately hypofractionated radiation therapy; NF: Normofractionated radiation therapy; n:number of patients; N: number of events Citation Format: Sofia Rivera, Eleni Karamouza, Youlia Kirova, Séverine Racadot, Mohamed Benchalal, Jean-Baptiste Clavier, Claire Charra-Brunaud, Marie-Eve Chand-Fouche, Delphine Argo-Leignel, Karine Peignaux, Ahmed Benyoucef, David Pasquier, Philippe Guilbert, Julien Blanchecotte, Agnès Tallet, Adeline Petit, Guillemette Bernadou, Xavier Zasadny, Claire Lemanski, Jacques Fourquet, Emmanuelle Malaurie, Honorine Kouto, Carole Massabeau, Alexandre Henni, Pauline Regnault, Aurélie Belliere, Yazid Belkacemi, Magali Le Blanc-Onfroy, Julien Geffrelot, Jean-Briac Prevost, Marie Bergeaud, Assia Lamrani-Ghaouti, Amandine Ruffier, Naima Bonnet, Stephanie Wong, Christine Rossier, Thomas Brion, Pierre Maroun, Claire Petit, Guillaume Auzac, Stefan Michiels. First oncological outcomes of HypoG-01: a UNICANCER phase III trial comparing loco-regional hypo vs normo fractionated radiation therapy in early breast cancer patients [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-19-10.

Abstract PO2-25-09: The hidden costs of beauty: An evaluation of breast cancer risk for Black women

Abstract The Black identity, hair product use, and breast cancer scale (BHBS) was developed and previously validated to evaluate the relationship between identity, hair product use, and breast cancer risk for Black women. Black women are disproportionately affected by breast cancer compared to other racial/ethnic groups, with a mortality rate of 40% higher than all other groups. Endocrine Disrupting Chemicals (EDCs) are present in many hair care products and have been linked to several health issues including breast cancer. Due to these health inequities and the complexity of how cultural norms shape Black women’s hair product usage, the purpose of this study was to assess the reliability of the BHBS for intervention planning and evaluate the hazard scores of hair products used by Black women. Methods: Participants were recruited using purposive convenience sampling techniques. The 11-item BHBS includes two subscales: five items measuring sociocultural perspectives about hair and identity (S1) and six items assessing perceived breast cancer risk related to hair product use (S2). To determine reliability, the BHBS was administered twice over a three-week period with sociodemographic factors obtained in the initial data collection phase. All statistical analyses, including descriptive statistics and test-retest reliability (Pearson correlations) were conducted using SPSS version 26. The Environmental Working Group's (EWG's) Skin Deep® database was used to determine hazard scores of hair products used by participants. Products are rated on a 10-point scale with low (0-2), moderate (3-6), and high hazard (7-10) scores. Results: Twenty-three (86.9% African, African American &amp; Caribbean; 13% multiracial) female participants completed the study. Their age ranged from 18-63 years (30.78, SD= 15.40), 47.8% reported an income of less than $25,000, and 34.8% completed some college education. Both subscales demonstrated highly significant and strong reliability (S1: r=.82, p&amp;lt; .001; S2: r=.88, p&amp;lt; .001). Participants primarily used conditioners (91.3% used wash out and 60.9% used leave-in), and professional hair dyes (34.8%). There was also a high frequency of non-use (91.3%) of do-it-yourself relaxers and hair dye kits. We evaluated 40 products across three categories including wash out conditioners, leave-in conditioners and other hair products (e.g., styling gels, shampoo, and hair oils), of which most had a moderate hazard rating of 5 denoting ingredients of health concerns (e.g., parabens, fragrance, and phenoxyethanol). Additionally, of the 22 company brands analyzed, only 10 (45%) are Black owned or founded. Conclusions: The BHBS is a valid and reliable instrument to assess sociocultural perspectives about hair, identity and perceived breast cancer risk. Black women use hair products including relaxers, hair dyes, and conditioners that contain EDCs that may be harmful to their health including risk for breast cancer. The BHBS will be used to evaluate psychosocial interventions that address the unique needs of Black women including exposure to EDCs from hair product use and breast cancer risk. Citation Format: Nicole Sarkaria, Marissa Ericson, Abigail Lopez, Dede Teteh. The hidden costs of beauty: An evaluation of breast cancer risk for Black women [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-25-09.

Abstract PO2-09-08: Biological and non-biological predictors of breast cancer disease-free survival among young Black females

Abstract Introduction: Young Black females bear a disproportionate burden of breast cancer (BC) deaths compared to White females yet remain underrepresented in clinical studies. We sought to discover predictors of disease-free survival (DFS) in a cohort of young Black females with BC. Methods: Black females diagnosed with invasive BC ≤ age 50 from 2005 to 2016 were recruited through the Florida and Tennessee state cancer registries. Participants were asked to complete a questionnaire, medical records release, and tissue/tumor release. Saliva was also requested for germline DNA extraction. For the primary outcome of BC DFS, univariate analyses were conducted using the following variables: proportion of West African ancestry, RNA expression based on PAM50 analyses, body mass index (BMI), social determinants of health (i.e., employment and insurance), immunohistochemistry (IHC) subtype, treatment category (i.e., chemotherapy, radiation, and surgery), and BC family history. Multivariate analyses were conducted using backward selection among these variables to analyze in the reduced model. Results: Of 701 consented, 687 participants with early-stage disease were included in the analysis; 14 participants with stage 4 disease at diagnosis were excluded. Among the 687 participants, the median age at diagnosis was 44, 28% had triple-negative breast cancer (TNBC), 13% were deceased, and 5% had recurrent disease. Clinically, participants with TNBC and lymph node involvement had worse BC DFS (p=0.001 and p=0.0002, respectively). Socio-economically, full-time employement was associated with higher BC DFS (p=0.0003). Among those for whom global ancestry data were available (n=551), multivariate analysis showed an association between increased percent of West African ancestry and worse BC DFS with HRIQR=1.23*, which approached significance (p=0.085). Additional subgroup analyses among those with hormone receptor-positive (HR+) (estrogen and/or progesterone receptor positive) BC (n=431) showed that participants with private insurance had better BC DFS (HR=0.45; p=0.05), while those with lymph node involvement had worse BC DFS (HR=2.07; p=0.001). Among HR+ participants with available ancestry data (n=349), worse BC DFS was associated with increased West African ancestry (p=0.05) and lymph node involvement (p=0.08). When ancestry was included in the model, private insurance was no longer associated with BC DFS in this HR+ subgroup (p=0.31). Other predictors analyzed did not reach statistical significance. Conclusion: Our findings confirm prior established adverse predictors of BC DFS, such as TNBC with lymph node involvement and the protective effect of full-time employment. We also found a novel association with West African ancestry among patients with HR+ breast cancer. Although further large-scale studies are needed, results from this cohort of young Black females with BC and highlight the critical need to support research to understand biological and non-biological factors contributing to BC DFS and develop targeted strategies to improve survival outcomes. * HRIQR is the ratio of hazard rates corresponding to upper and lower quartiles of percent West African (interquartile range (IQR): 70.0%-80.8%). Citation Format: Sonya Reid, Run Fan, Lindsay Venton, Anne Weidner, Ann Tezak, Mya Roberson, Susan Vadaparampil, Xuefeng Wang, Sean Yoder, Marilin Rosa, Jibril Hirbo, Jennifer Whisenant, Jennifer Pietenpol, Sheila Rajagopal, Brian Lehmann, Fei Ye, Tuya Pal. Biological and non-biological predictors of breast cancer disease-free survival among young Black females [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-09-08.

Abstract PO5-02-11: Is There A Survival Benefit With Adjuvant Chemotherapy Use In Elderly Breast Cancer Patients? A Retrospective Study Using The National Cancer Database

Abstract Background Geriatric patients (Age &amp;gt;=65 years) with Breast Cancer (BC) face a unique challenge due to the relatively lower functional status, as well as co-existing comorbidities. Studies like the recently published meta-analysis by the Early Breast Cancer Trialists’ Collaborative Group (EBCTCG) group provide irrefutable evidence for the recurrence free survival benefit of anthracycline and taxane based adjuvant chemotherapy (ACT) regimes in early-stage BC patients. However, the age range of the trials analyzed ranged between 46-55 years, with underrepresentation of the geriatric group. The question on whether ACT results in an overall survival (OS) benefit for the elderly remains at large, which we hope to answer through our study. Methods The 2019 National Cancer Database (NCDB) was used to extract patients aged &amp;gt;= 65 years with breast cancer. We included stage 1-3 patients and stratified them into those who received ACT (ACT+) and those who did not (ACT-). Patients who received ACT were identified from the columns that specified the times of events from diagnosis or from the column for systemic therapy-surgery sequence. Patients should have had definitive surgery for their BC management to be included. Odds Ratio (OR) from logistic regression was used to analyze the utility of ACT based on various factors. Kaplan Meier (KM) survival curves and Hazard Ratio (HR) estimates from multivariate cox model was used to compare OS outcomes. Results Our cohort had 866,071 (ACT+: 642721, ACT-:223350) patients. The age distribution showed that ACT+ had 86.45% in the 65-80 years group and 13.55% in the &amp;gt;80 years group. ACT- had 68.32% aged 65-80 and 31.68% &amp;gt;80 years. The distribution of various demographic, pathologic and clinical factors by ACT use are shown in Table 1. Factors associated with ACT use based on OR estimates are shown in Table 2. ACT use is more likely in younger age group (65-80), lower comorbidity score, poorly differentiated and undifferentiated tumors, ER/PR negativity, T2 and lymph node positivity, those who underwent partial mastectomy and regional lymph node surgery, and HER2 positivity. Both 5-year (86.3 vs 74.2%) and 10-year (66 vs 50.8) OS were better with ACT+ (Table 2). The HR using propensity score (PS) weighted cox model revealed a higher hazard rate on omitting ACT [1.436, 95% Confidence Interval (CI) 1.417,1.456, p&amp;lt; .0001] (Table 2). HR estimates between ACT- vs ACT+, stratified by subgroups [Age (65-80, &amp;gt;80), T stage, grade (G), HER2] favored ACT use in all groups except G1 tumors (Table 3). Discussion Our study using a large national database, supports the use of ACT in the geriatric BC population by showing a clear OS advantage of 15.2% at 10 years. This benefit was observed even in BC patients aged more than 80 years with a HR of 1.683 when compared to ACT-, as represented in Table 3. While the existing literature provides robust evidence for ACT use in situations such as a high oncotype recurrence score, our study provides real-world evidence from a population-based dataset to supports its use in the elderly, including those above 80 years. The geriatric assessment recommended by the American Society of Clinical Oncology guideline for geriatric oncology should be followed in this setting. Utilization of geriatric assessment tools among oncologists has been poor with a survey revealing that 60% of providers did not utilize these tools in making treatment decisions. Limitations of our study include the potential for missing confounding factors and the retrospective nature of the study using a large database. Table 1 Demographic, pathological, and clinical characteristics of the study population and their distribution based on ACT use. Table 2 Odds Ratio for ACT use, KM survival curves and HR estimates of ACT use Table 3 HR estimates of mortality for ACT- vs ACT+ stratified by various subgroups Citation Format: Prashanth Ashok Kumar, Metlapalli Venkata Sravanthi, Dongliang Wang, Danning Huang, Abirami Sivapiragasam. Is There A Survival Benefit With Adjuvant Chemotherapy Use In Elderly Breast Cancer Patients? A Retrospective Study Using The National Cancer Database [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-02-11.

Beta generated slash distribution: derivation, properties and application to lifetime data

In this paper, we introduce a new distribution called beta generated slash distribution by applying the slash construction idea to the existing beta distribution of first kind. The statistical properties of the distribution such as moments, skewness, kurtosis, median, moment generating function, mean deviations, Lorenz and Bonferroni curves, order statistics, Mills ratio, hazard rate functions have been discussed. The location-scale form of the beta generated slash distribution is also established. The hazard rate function is seen to assume different shapes depending upon the values of the parameters. The method of maximum likelihood is used to estimate the unknown parameters of beta generated slash distribution and a simulation study is conducted to check the performance of these estimates. Finally, the proposed distribution is applied to a real-life data set on failure times and the goodness-of-fit of the fitted distribution is compared with four other competing distributions to show its flexibility and advantage particularly in modeling heavy tailed data sets.

A statistical framework for a new Kavya-Manoharan Bilal distribution using ranked set sampling and simple random sampling

In survival and stochastic lifespan modeling, numerous families of distributions are sometimes considered unnatural, unjustifiable theoretically, and occasionally superfluous. Here, a novel parsimonious survival model is developed using the Bilal distribution (BD) and the Kavya-Manoharan (KM) parsimonious transformation family. In addition to other analytical properties, the forms of probability density function (PDF) and behavior of the distributions' hazard rates are analyzed. The insights are theoretical as well as practical. Theoretically, we offer explicit equations for the single and product moments of order statistics from Kavya-Manoharan Bilal Distribution. Practically, maximum likelihood (ML) technique, which is based on simple random sampling (SRS) and ranked set sampling (RSS) sample schemes, is employed to estimate the parameters. Numerical simulations are used as the primary methodology to compare the various sampling techniques.

The single and double inverse Pareto–Burr XII distribution: Properties, estimation methods, and real-life data applications

Researchers consistently improve statistical tools to provide a flexible method to fit or predict. The solution needs to be more suitable since the approach is sometimes complex and complicated. Generally, statistical tools are generated from ordinary least squares and wavelet methods. However, the reliability tool provides a good fit comparable to state-of-the-art methods, including the complex posterior setting of hyperparameters. In this article, a flexible extension of the Burr XII model, which is the odd inverse Pareto–Burr XII (OIPBXII) distribution, is studied and investigated using statistical tools such as Markov chain Monte Carlo methods. The mathematical properties of the probability density distribution of OIPBXII are derived, and it shows a behavior shape, decreasing, increasing, J-shaped, reversed-J-shaped, bathtub, upside-down bathtub, decreasing–increasing–decreasing hazard rates, and right-skewed, symmetrical, and concave down densities. The OIPBXII parameters are investigated by using seven classical approaches to estimation. Extensive simulation results are presented to explore the performance of these methods for small and large samples. An application to two real-life sets of data from engineering and medicine is analyzed, showing the flexibility of the OIPBXII distribution as compared to existing Burr XII distributions.

Topp-Leone Exponentiated Burr XII Distribution: Theory and Application to Real-Life Data Sets

This paper introduces a novel compound distribution, named the Topp Leone Exponentiated Burr XII (TLEBXII) Distribution, aimed at generating a more flexible family of probability distributions. By taking the Exponentiated Burr XII distribution as the base and the Topp Leone exponentiated G family as the generator, this new distribution seeks to enhance modeling capabilities in various statistical applications. We present general expressions for the density and distribution functions of the TLEBXII model and explore its fundamental properties, including survival and hazard rate functions, moments, moment-generating functions, and entropy. Additionally, we discuss the methodology for estimating the model parameters through maximum likelihood estimation. The utility and superior performance of the TLEBXII distribution are demonstrated through its application to two real datasets, where it shows significant improvements over existing models. This paper underscores the potential of the TLEBXII distribution in providing a robust tool for statistical modeling and analysis.

Inverse unit exponential probability distribution: Classical and Bayesian inference with applications

This article examines the new inverse unit exponential distribution, utilizing both classical and Bayesian methodologies; it begins by presenting the general properties of the proposed model, highlighting characteristic features, such as the presence of a reverse-J or increasing and inverted bathtub-shaped hazard rate function. Furthermore, it explores various statistical properties of the suggested distribution. It employs 12 methods to estimate the associated parameters. A Monte Carlo simulation is conducted to evaluate the accuracy of the estimation procedure. Even for small samples, the results indicate that biases and mean square errors decrease as the sample size increases, demonstrating the robustness of the estimation method. The application of the suggested distribution to real datasets is then discussed. Empirical evidence, using model selection criteria and goodness-of-fit test statistics, supports the assertion that the suggested model outperforms several existing models considered in the study. This article extends its analysis to the Bayesian framework. Using the Hamiltonian Monte Carlo with the no U-turn sampling algorithm, 8000 real samples are generated. The convergence assessment reveals that the chains are convergent and the samples are independent. Subsequently, using the posterior samples, the parameters of the proposed model are estimated, and credible intervals and highest posterior density intervals are computed to quantify uncertainty. The applicability of the suggested model to real data under both classical and Bayesian methodologies provides insights into its statistical properties and performance compared to existing models.

Generalization of Odd Ramos-Louzada generated family of distributions: Properties, characterizations, and applications to diabetes and cancer survival datasets

Probability distributions offer the best description of survival data and as a result, various lifetime models have been proposed. However, some of these survival datasets are not followed or sufficiently fitted by the existing proposed probability distributions. This paper presents a novel Kumaraswamy Odd Ramos-Louzada-G (KumORL-G) family of distributions together with its statistical features, including the quantile function, moments, probability-weighted moments, order statistics, and entropy measures. Some relevant characterizations were obtained using the hazard rate function and the ratio of two truncated moments. In light of the proposed KumORL-G family, a five-parameter sub-model, the Kumaraswamy Odd Ramos-Louzada Burr XII (KumORLBXII) distribution was introduced and its parameters were determined with the maximum likelihood estimation (MLE) technique. Monte Carlo simulation was performed and the numerical results were used to evaluate the MLE technique. The proposed probability distribution's significance and applicability were empirically demonstrated using various complete and censored datasets on the survival times of cancer and diabetes patients. The analytical results showed that the KumORLBXII distribution performed well in practice in comparison to its sub-models and several other competing distributions. The new KumORL-G for diabetes and cancer survival data is found extremely efficient and offers an enhanced and novel technique for modeling survival datasets.

ARCSINE RAYLIEGH PARETO DISTRIBUTION: PROPERTIES AND APPLICATION TO CARBON FIBERS DATA SETS

In this paper, we introduce a new modified distribution called arcsine Rayliegh Pareto (ASRP) Distribution. We derived its mathematical and statistical properties, including survival function, hazard function, entropy, moment, moment generating function, and order statistics. We also used maximum likelihood estimation for estimating the parameters of the distribution. The plots of the cdf, pdf, hazard rate function, and survival function were illustrated with right skewed probability density function, cumulative distribution function with monotone increasing function, which converge at one. The value of some goodness of fit measure (i.e. AIC, AICc, and BIC) were computed, as well as the KS, A, and W statistic. Finally, we suggested that the new modified model outperform better than the other standard distribution using Carbon fibers data sets.

Statistical Reliability Assessment with Generalized Intuitionistic Fuzzy Burr XII Distribution

Intuitionistic fuzzy sets provide a viable framework for modelling lifetime distribution characteristics, particularly in scenarios with measurement imprecision. This is accomplished by utilizing membership and non-membership degrees to accurately express the complexities of data uncertainty. Nonetheless, the complexities of some cases necessitate a more advanced approach of imprecise data, motivating the use of generalized intuitionistic fuzzy sets (GenIFSs). The use of GenIFSs represents a flexible modeling strategy that is characterized by the careful incorporation of an extra level of hesitancy, which effectively clarifies the underlying ambiguity and uncertainty present in reliability evaluations. The study employs a methodology based on generalized intuitionistic fuzzy distributions to thoroughly examine the uncertainty related to the parameters and reliability characteristics present in the Burr XII distribution. The goal is to provide a more accurate evaluation of reliability measurements by addressing the inherent ambiguity in the distribution’s shape parameter. Various reliability measurements, such as reliability, hazard rate, and conditional reliability functions, are derived for the Burr XII distribution. This extensive analysis is carried out within the context of the generalized intuitionistic fuzzy sets paradigm, improving the understanding of the Burr XII distribution’s reliability measurements and providing important insights into its performance for the study of various types of systems. To facilitate understanding and point to practical application, the findings are shown graphically and contrasted across various cut-set values using a valuable numerical example.