A sup-score test for the cure fraction in mixture models for long-term survivors.
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ABSTRACT:
SUBMITTER: Hsu WW
PROVIDER: S-EPMC8314275 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:In biomedical studies, testing for homogeneity between two groups, where one group is modeled by mixture models, is often of great interest. This paper considers the semiparametric exponential family mixture model proposed by Hong et al. (2017) and studies the score test for homogeneity under this model. The score test is nonregular in the sense that nuisance parameters disappear under the null hypothesis. To address this difficulty, we propose a modification of the score test, so that the resulting test enjoys the Wilks phenomenon. In finite samples, we show that with fixed nuisance parameters the score test is locally most powerful. In large samples, we establish the asymptotic power functions under two types of local alternative hypotheses. Our simulation studies illustrate that the proposed score test is powerful and computationally fast. We apply the proposed score test to an UK ovarian cancer DNA methylation data for identification of differentially methylated CpG sites.
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Project description:BackgroundIncreasing evidence of cure for some neoplasms has emerged in recent years. The study aimed to estimate population-based indicators of cancer cure.MethodsInformation on more than half a million cancer patients aged 15-74 years collected by population-based Italian cancer registries and mixture cure models were used to estimate the life expectancy of fatal tumors (LEFT), proportions of patients with similar death rates of the general population (cure fraction), and time to reach 5-year conditional relative survival (CRS) >90% or 95% (time to cure).ResultsBetween 1990 and 2000, the median LEFT increased >1 year for breast (from 8.1 to 9.4 years) and prostate cancers (from 5.2 to 7.4 years). Median LEFT in 1990 was >5 years for testicular cancers (5.8) and Hodgkin lymphoma (6.3) below 45 years of age. In both sexes, it was ≤0.5 years for pancreatic cancers and NHL in 1990 and in 2000. The cure fraction showed a 10% increase between 1990 and 2000. It was 95% for thyroid cancer in women, 94% for testis, 75% for prostate, 67% for breast cancers, and <20% for liver, lung, and pancreatic cancers. Time to 5-year CRS >95% was <10 years for testis, thyroid, colon cancers, and melanoma. For breast and prostate cancers, the 5-year CRS >90% was reached in <10 years but a small excess remained for >15 years.ConclusionsThe study findings confirmed that several cancer types are curable. Became aware of the possibility of cancer cure has relevant clinical and social impacts.
| S-EPMC6675712 | biostudies-literature
Project description:Novel cancer therapies are associated with survival patterns that differ from established therapies, which may include survival curves that plateau after a certain follow-up time point. A fraction of the patient population is then considered statistically cured and subject to the same mortality experience as the cancer-free general population. Mixture cure models have been developed to account for this characteristic. As compared to standard survival analysis, mixture cure models can often lead to profoundly different estimates of long-term survival, required for health economic evaluations. This tutorial is designed as a practical introduction to mixture cure models. Step-by-step instructions are provided for the entire implementation workflow, i.e., from gathering and combining data from different sources to fitting models using maximum likelihood estimation and model results interpretation. Two mixture cure models were developed to illustrate (1) an "uninformed" approach where the cure fraction is estimated from trial data and (2) an "informed" approach where the cure fraction is obtained from an external source (e.g., real-world data) used as an input to the model. These models were implemented in the statistical software R, with the freely available code on GitHub. The cure fraction can be estimated as an output from ("uninformed" approach) or used as an input to ("informed" approach) a mixture cure model. Mixture cure models suggest presumed estimates of long-term survival proportions, especially in instances where some fraction of patients is expected to be statistically cured. While this type of model may initially seem complex, it is straightforward to use and interpret. Mixture cure models have the potential to improve the accuracy of survival estimates for treatments associated with statistical cure, and the present tutorial outlines the interpretation and implementation of mixture cure models in R. This type of model will likely become more widely used in health economic analyses as novel cancer therapies enter the market.
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Project description:Glioblastoma (GBM) is a highly aggressive type of glioma with poor prognosis. However, a small number of patients live much longer than the median survival. A better understanding of these long-term survivors (LTS) may provide important insight into the biology of GBM. We identified 7 patients with GBM treated at Memorial Sloan-Kettering Cancer Center (MSKCC) with survival greater than 48 months. We characterized the transcriptome of each patient and determined rates of MGMT promoter methylation and IDH1 and IDH2 mutational status. We identified LTS in two independent cohorts (TCGA and REMBRANDT) and analyzed the transcriptomal characteristics of these LTS. The median overall survival of our cohort was 62.5 months. LTS were distributed between the proneural (n=2), neural (n=2), classical (n=2) and mesenchymal (n=1) subtypes. Similarly, LTS in the TCGA and REMBRANDT cohorts demonstrated diverse transcriptomal subclassification identity. The majority of the MSKCC LTS (71%) were found to have methylation of the MGMT promoter. None of the patients had an IDH1 or IDH2 mutations, and IDH mutation occurred in a minority of the TCGA LTS as well. A set of 42 genes was found to be differentially expressed in the MSKCC and TCGA LTS. While IDH mutant proneural tumors impart a better prognosis in the short-term, survival beyond 4 years does not require IDH mutation and is not dictated by a single transcriptional subclass. In contrast, MGMT methylation continues to have strong prognostic value for survival beyond 4 years. These findings have substantial impact for understanding GBM biology and progression. All tumors (n = 7) were obtained following surgical resection at the MSKCC as part of routine clinical care, and snap frozen. Tumors were obtained in accordance with Institutional Review Board policies at the MSKCC. Each sample was examined histologically by 3 independent neuropathologists and confirmed to be World Health Organization (WHO) grade IV glioma (GBM). Before analysis, tumors were sectioned and microdissected. Genomic DNA or RNA was extracted using the DNeasy kit (Qiagen) or RNeasy Lipid Tissue Mini Kit (Qiagen) as per the manufacturer’s instructions. Expression analysis of tumors was performed using the Affymetrics U133 2.0 microarray (Affymetrix). Affymetrix CEL files were imported into the Partek Genomics Suite (Partek). The TCGA gene expression data (HT-HG-U133A) was accessed from the TCGA data repositories (http://cancergenome.nih.gov, date of download 12/2013).
2014-05-02 | E-GEOD-54077 | biostudies-arrayexpress
Project description:Lung cancer survivors are at risk for physical fitness and autonomic function impairments. In a cross-sectional study of consecutive lung cancer survivors post-curative intent therapy, we assessed and identified predictors of resting heart rate variability (HRV) and heart rate recovery (HRR), defined as standard deviation of normal-to-normal-R-to-R intervals (SDNN) and root-mean-square-of-successive-differences (rMSSD) from routine outpatient single 10-s electrocardiographs (ECGs) and difference in heart rate (HR) at 1-minute following and the end of the six-minute-walk-test (6MWT), respectively. In 69 participants, the mean (SD) HRR was -10.6 (6.7) beats. Significant independent predictors of HRR were age and HR change associated with the 6MWT. In a subset of 41 participants with available ECGs, the mean (SD) SDNN and rMSSD were 19.1 (15.6) and rMSSD 18.2 (14.6) ms, respectively. Significant independent predictors of HRV were supine HR, HRR, and total lung capacity. HRV/HRR may be useful physiological measures in studies aimed at improving physical fitness and/or autonomic function in lung cancer survivors.
| S-EPMC6759398 | biostudies-literature
Project description:Glioblastoma (GBM) is a highly aggressive type of glioma with poor prognosis. However, a small number of patients live much longer than the median survival. A better understanding of these long-term survivors (LTS) may provide important insight into the biology of GBM. We identified 7 patients with GBM treated at Memorial Sloan-Kettering Cancer Center (MSKCC) with survival greater than 48 months. We characterized the transcriptome of each patient and determined rates of MGMT promoter methylation and IDH1 and IDH2 mutational status. We identified LTS in two independent cohorts (TCGA and REMBRANDT) and analyzed the transcriptomal characteristics of these LTS. The median overall survival of our cohort was 62.5 months. LTS were distributed between the proneural (n=2), neural (n=2), classical (n=2) and mesenchymal (n=1) subtypes. Similarly, LTS in the TCGA and REMBRANDT cohorts demonstrated diverse transcriptomal subclassification identity. The majority of the MSKCC LTS (71%) were found to have methylation of the MGMT promoter. None of the patients had an IDH1 or IDH2 mutations, and IDH mutation occurred in a minority of the TCGA LTS as well. A set of 42 genes was found to be differentially expressed in the MSKCC and TCGA LTS. While IDH mutant proneural tumors impart a better prognosis in the short-term, survival beyond 4 years does not require IDH mutation and is not dictated by a single transcriptional subclass. In contrast, MGMT methylation continues to have strong prognostic value for survival beyond 4 years. These findings have substantial impact for understanding GBM biology and progression.
2014-05-02 | GSE54077 | GEO
Project description:Medical breakthroughs in recent years have led to cures for many diseases. The mixture cure model (MCM) is a type of survival model that is often used when a cured fraction exists. Many have sought to identify genomic features associated with a time-to-event outcome which requires variable selection strategies for high-dimensional spaces. Unfortunately, currently few variable selection methods exist for MCMs especially when there are more predictors than samples. This study develops high-dimensional penalized Weibull MCMs, which allow for identification of prognostic factors associated with both cure status and/or survival. We demonstrated how such models may be estimated using two different iterative algorithms. The model-X knockoffs method was combined with these algorithms to control the false discovery rate (FDR) in variable selection. Through extensive simulation studies, our penalized MCMs have been shown to outperform alternative methods on multiple metrics and achieve high statistical power with FDR being controlled. In an acute myeloid leukemia (AML) application with gene expression data, our proposed approach identified 14 genes associated with potential cure and 12 genes with time-to-relapse, which may help inform treatment decisions for AML patients.
| S-EPMC9545322 | biostudies-literature
Project description:Thyroid disorders are well-studied after allogeneic haematopoietic stem cell transplantation (HSCT) following total body irradiation (TBI)-based conditioning, occurring in 15-30% of paediatric survivors. The toxic effect of TBI is known but data on the role of immunological dysregulation (ID) and chronic graft-versus-host-disease (cGvHD) are scarce. We studied functional and structural thyroid disorders in 97 paediatric ALL patients after TBI-based HSCT, assessing their correlation with patient/transplant characteristics including cGvHD, prolonged immunosuppression and ID. The 10- and 15-year cumulative incidence (CI) of functional disorders was 50 and 60%. Univariate analysis revealed TBI in 6 vs. 8 fractions (p = 0.01), an interval between ALL diagnosis and HSCT <1 year (p = 0.038), and the application of ATG (p = 0.044) as risk factors. The 10- and 15-year CI of structural disorders was 60 and 80%. No correlation between patient/transplant characteristics and structural disorders was observed. cGvHD, prolonged immunosuppression and additional radiotherapy were not associated with any thyroid disease. We observed a significant correlation between ID and the development of thyroid dysfunction in patients with structural changes (10-year CI: 77% for patients with ID vs. 56% without ID, p = 0.02). The impact of our results on thyroid follow-up evaluations and the significance of hormonal replacement therapy are discussed.
| S-EPMC8809136 | biostudies-literature
Project description:Glioblastoma (GBM) is a highly aggressive type of glioma with poor prognosis. However, a small number of patients live much longer than the median survival. A better understanding of these long-term survivors (LTS) may provide important insight into the biology of GBM. We identified 7 patients with GBM treated at Memorial Sloan-Kettering Cancer Center (MSKCC) with survival greater than 48 months. We characterized the transcriptome of each patient and determined rates of MGMT promoter methylation and IDH1 and IDH2 mutational status. We identified LTS in two independent cohorts (TCGA and REMBRANDT) and analyzed the transcriptomal characteristics of these LTS. The median overall survival of our cohort was 62.5 months. LTS were distributed between the proneural (n=2), neural (n=2), classical (n=2) and mesenchymal (n=1) subtypes. Similarly, LTS in the TCGA and REMBRANDT cohorts demonstrated diverse transcriptomal subclassification identity. The majority of the MSKCC LTS (71%) were found to have methylation of the MGMT promoter. None of the patients had an IDH1 or IDH2 mutations, and IDH mutation occurred in a minority of the TCGA LTS as well. A set of 42 genes was found to be differentially expressed in the MSKCC and TCGA LTS. While IDH mutant proneural tumors impart a better prognosis in the short-term, survival beyond 4 years does not require IDH mutation and is not dictated by a single transcriptional subclass. In contrast, MGMT methylation continues to have strong prognostic value for survival beyond 4 years. These findings have substantial impact for understanding GBM biology and progression. All tumors (n = 7) were obtained following surgical resection at the MSKCC as part of routine clinical care, and snap frozen. Tumors were obtained in accordance with Institutional Review Board policies at the MSKCC. Each sample was examined histologically by 3 independent neuropathologists and confirmed to be World Health Organization (WHO) grade IV glioma (GBM). Before analysis, tumors were sectioned and microdissected. Genomic DNA or RNA was extracted using the DNeasy kit (Qiagen) or RNeasy Lipid Tissue Mini Kit (Qiagen) as per the manufacturer’s instructions. Expression analysis of tumors was performed using the Affymetrics U133 2.0 microarray (Affymetrix). Affymetrix CEL files were imported into the Partek Genomics Suite (Partek). The TCGA gene expression data (HT-HG-U133A) was accessed from the TCGA data repositories (http://cancergenome.nih.gov, date of download 12/2013).
| S-ECPF-GEOD-54077 | biostudies-other
Project description:BackgroundLong-term childhood cancer survivors (CCS) are at increased risk of adverse cardiovascular events; however, there is a paucity of risk-stratification tools to identify those at higher-than-normal risk.Subjects, materials, and methodsThis was a population-based study using data from the Surveillance, Epidemiology, and End Results Program (1973-2013). Long-term CCS (age at diagnosis ≤19 years, survival ≥5 years) were followed up over a median time period of 12.3 (5-40.9) years. Independent predictors of cardiovascular mortality (CVM) were combined into a risk score, which was developed in a derivation set (n = 22,374), and validated in separate patient registries (n = 6,437).ResultsIn the derivation registries, older age at diagnosis (≥10 years vs. reference group of 1-5 years), male sex, non-white race, a history of lymphoma, and a history of radiation were independently associated with an increased risk of CVM among long-term CCS (p < .05). A risk score derived from this model (Childhood and Adolescence Cancer Survivor CardioVascular score [CHACS-CV], range: 0-8) showed good discrimination for CVM (Harrell's C-index [95% confidence interval (CI)]: 0.73 [0.68-0.78], p < .001) and identified a high-risk group (CHACS-CV ≥6), with cumulative CVM incidence over 30 years of 6.0% (95% CI: 4.3%-8.1%) versus 2.6% (95% CI: 1.8%-3.7%), and 0.7% (95% CI: 0.5%-1.0%) in the mid- (CHACS-CV = 4-5) and low-risk groups (CHACS-CV ≤3), respectively (plog-rank < .001). In the validation set, the respective cumulative incidence rates were 4.7%, 3.1%, and 0.8% (plog-rank < .001).ConclusionWe propose a simple risk score that can be applied in everyday clinical practice to identify long-term CCS at increased cardiovascular risk, who may benefit from early cardiovascular screening, and risk-reduction strategies.Implications for practiceChildhood cancer survivors (CCS) are known to be at increased cardiovascular risk. Currently available prognostic tools focus on treatment-related adverse events and late development of congestive heart failure, but there is no prognostic model to date to estimate the risk of cardiovascular mortality among long-term CCS. A simple clinical tool is proposed for cardiovascular risk stratification of long-term CCS based on easily obtainable information from their medical history. This scoring system may be used as a first-line screening tool to assist health care providers in identifying those who may benefit from closer follow-up and enable timely deployment of preventive strategies.
| S-EPMC6156177 | biostudies-literature