A Jackknife Estimator of Variance for Cox Regression for Correlated Survival Data

Biometrics ◽  
1996 ◽  
Vol 52 (1) ◽  
pp. 291 ◽  
Author(s):  
Stuart R. Lipsitz ◽  
Michael Parzen
Keyword(s):  
Survival Data ◽  
Cox Regression ◽  
Jackknife Estimator

scholarly journals Establishment and Validation of an MTORC1 Signaling-Related Gene Signature to Predict Overall Survival in Patients with Hepatocellular Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Zheng Yao ◽  
Song Wen ◽  
Jun Luo ◽  
Weiyuan Hao ◽  
Weiren Liang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Decision Tree ◽  
Survival Data ◽  
Cox Regression ◽  
Gene Signature ◽  
Related Gene ◽  
Cox Regression Analysis ◽  
Cancer Hallmarks ◽  
Mtorc1 Signaling

Background. Accurate and effective biomarkers for the prognosis of patients with hepatocellular carcinoma (HCC) are poorly identified. A network-based gene signature may serve as a valuable biomarker to improve the accuracy of risk discrimination in patients. Methods. The expression levels of cancer hallmarks were determined by Cox regression analysis. Various bioinformatic methods, such as GSEA, WGCNA, and LASSO, and statistical approaches were applied to generate an MTORC1 signaling-related gene signature (MSRS). Moreover, a decision tree and nomogram were constructed to aid in the quantification of risk levels for each HCC patient. Results. Active MTORC1 signaling was found to be the most vital predictor of overall survival in HCC patients in the training cohort. MSRS was established and proved to hold the capacity to stratify HCC patients with poor outcomes in two validated datasets. Analysis of the patient MSRS levels and patient survival data suggested that the MSRS can be a valuable risk factor in two validated datasets and the integrated cohort. Finally, we constructed a decision tree which allowed to distinguish subclasses of patients at high risk and a nomogram which could accurately predict the survival of individuals. Conclusions. The present study may contribute to the improvement of current prognostic systems for patients with HCC.

Analysis of chemotherapy efficacy according to histology in malignant pleural mesothelioma (MPM) patients (p).

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e20563-e20563
Author(s):  
Susana Cedres Perez ◽  
Juan David Assaf Pastrana ◽  
Patricia Iranzo ◽  
Ana Callejo ◽  
Nuria Pardo ◽  
...  
Keyword(s):  
Prognostic Factor ◽  
Survival Data ◽  
Cox Regression ◽  
Asbestos Exposure ◽  
Performance Status ◽  
University Hospital ◽  
First Line ◽  
Neutrophil Lymphocyte Ratio ◽  
The Impact ◽  
Line Chemotherapy

e20563 Background: MPM is a highly aggressive pleural tumor associated with asbestos exposure and with limited survival despite systemic therapy. Histology is a prognostic factor and recently CheckMate 743 trial demonstrated survival benefit of immunotherapy in first line with some differences in the efficacy of chemotherapy according to histology. However, randomized trials who led to the approval of antifolate in mesothelioma did not include analysis of outcomes by histology. The objective of this study is to characterize the impact of chemotherapy according to histology in p with MPM at our institution. Methods: We review 189 MPM p diagnosed at Vall d´Hebron University Hospital between November 2002 and April 2020. Associations between clinical variables and outcome were assessed with Cox regression models and survival data were calculated by the Kaplan-Meier method. Results: Patient’s characteristics: median age 68 years (y) (45-88 y), males: 70%, performance status (PS)1: 69%, asbestos exposure: 75%, epithelioid subtype: 76%. First line chemotherapy was offered to 85% of p (66% cisplatin-pemetrexed and 27% carboplatin-pemetrexed). Median overall survival (OS) in overall population was 21.3 m (95%CI17.2-24.3). Epithelioid histology, PS 0, neutrophil-lymphocyte ratio <5 and treatment with cisplatin vs carboplatin were associated with significant improvements in OS (p<0.001). When we analyzed the survival of patients who received first line chemotherapy according to histology, we found that patients with epithelioid tumors had better PFS and OS. Median PFS for p with epithelioid tumors treated with chemotherapy in first line was 4.8 m versus 3.6 months non-epithelioid (HR1.5 CI95% 1.1-2.3; p=0.03). OS of epithelioid p treated with first line chemotherapy was 26.7 m versus 15.0 m non-epithelioid patients (HR2.25 CI95% 1.4-3.4; p<0.001). We analyzed if the differences in survival according to histology were due to type of systemic treatment received (Table). Conclusions: In our series, p with non-epithelioid tumors presented worse prognosis. We confirmed histology is a prognostic factor with better OS for p with epithelioid tumors. Moreover, we demonstrated better efficacy of chemotherapy in epithelioid tumors, although histology is not a predictive factor for the platinum agent sensitivity (p of interaction PFS=0.09, p of interaction OS= 0.65).[Table: see text]

scholarly journals circSMARCA5 Functions as a Diagnostic and Prognostic Biomarker for Gastric Cancer

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Juan Cai ◽  
Zhiqiang Chen ◽  
Xueliang Zuo
Keyword(s):  
Gastric Cancer ◽  
Clinical Significance ◽  
Survival Data ◽  
Cox Regression ◽  
Characteristic Curve ◽  
Disease Free Survival ◽  
Migration And Invasion ◽  
Circular Rnas ◽  
Functional Roles ◽  
Potential Biomarker

Background. Circular RNAs have been implicated in various malignancies and can function as potential biomarkers for cancers. Reportedly, circSMARCA5 was downregulated in hepatocellular carcinoma and glioblastoma multiforme, but upregulated in prostate cancer. The functional roles and clinical significance of circSMARCA5 still remain unknown in the context of gastric cancer (GC). Methods. Expression levels of circSMARCA5 were detected by qRT-PCR. Clinical data including patient basic information, clinicopathological features, and survival data were obtained. The Kaplan-Meier methods, multivariate Cox regression models, and the receiver operating characteristic curve were used to assess the clinical significance of circSMARCA5 in GC. Cell proliferation assays and transwell assays were performed to elucidate the functional roles of circSMARCA5 in GC. Results. The circSMARCA5 level was decreased in GC tissues and cell lines. The low expression level of circSMARCA5 was correlated to poorer overall survival and disease-free survival. Low circSMARCA5 expression was revealed as an independent unfavorable predictive factor for GC. The results indicated that circSMARCA5 had a moderate ability for discrimination between GC patients and controls with an area under the curve of 0.806. Upregulation of circSMARCA5 dampened the proliferation, migration, and invasion of GC cells, whereas circSMARCA5 knockdown promoted GC progression. Discussion. Our results demonstrated that circSMARCA5 was decreased and exerted tumor-suppressive effects in GC. circSMARCA5 can function as a potential biomarker for GC prognosis and diagnosis.

scholarly journals The what, when and how of orthopaedic registers: an introduction into register-based research

2019 ◽  
Vol 4 (6) ◽  
pp. 337-343 ◽  
Author(s):  
Claus Varnum ◽  
Alma Bečić Pedersen ◽  
Per Hviid Gundtoft ◽  
Søren Overgaard
Keyword(s):  
Survival Analysis ◽  
Selection Bias ◽  
Survival Data ◽  
Cox Regression ◽  
Research Question ◽  
Cox Regression Analysis ◽  
Information Bias ◽  
Kaplan Meier ◽  
Routinely Collected Health Data ◽  
Competing Events

Establishment of orthopaedic registers started in 1975 and many registers have been initiated since. The main purpose of registers is to collect information on patients, implants and procedures in order to monitor and improve the outcome of the specific procedure. Data validity reflects the quality of the registered data and consists of four major aspects: coverage of the register, registration completeness of procedures/patients, registration completeness of variables included in the register and accuracy of registered variables. Survival analysis is often used in register studies to estimate the incidence of an outcome. The most commonly used survival analysis is the Kaplan–Meier survival curves, which present the proportion of patients who have not experienced the defined event (e.g. death or revision of a prosthesis) in relation to the time. Depending on the research question, competing events can be taken into account by using the cumulative incidence function. Cox regression analysis is used to compare survival data for different groups taking differences between groups into account. When interpreting the results from observational register-based studies a number of factors including selection bias, information bias, chance and confounding have to be taken into account. In observational register-based studies selection bias is related to, for example, absence of complete follow-up of the patients, whereas information bias is related to, for example, misclassification of exposure (e.g. risk factor of interest) or/and outcome. The REporting of studies Conducted using Observational Routinely-collected Data guidelines should be used for studies based on routinely-collected health data including orthopaedic registers. Linkage between orthopaedic registers, other clinical quality databases and administrative health registers may be of value when performing orthopaedic register-based research. Cite this article: EFORT Open Rev 2019;4 DOI: 10.1302/2058-5241.4.180097

scholarly journals Prognostic Factors in Patients With Osteosarcoma With the Surveillance, Epidemiology, and End Results Database

2020 ◽  
Vol 19 ◽  
pp. 153303382094770
Author(s):  
Peng Fu ◽  
Yu Shi ◽  
Gang Chen ◽  
Yaohua Fan ◽  
Yanhong Gu ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Survival Data ◽  
Risk Model ◽  
Cox Regression ◽  
Survival Rates ◽  
Rare Type ◽  
Hazards Model ◽  
Kaplan Meier ◽  
Endpoint Event ◽  
Prognostic Risk Factors

Background: Osteosarcoma is a rare type of bone tumor, and this study aimed to assess the clinicopathologic features and prognoses of osteosarcoma patients. Methods: Clinicopathologic and survival data of 1025 patients between 2010 and 2016, 230 between 2008 and 2009 were downloaded and analyzed from the SEER database. Patients’ survival was analyzed using the Kaplan-Meier analysis; prognostic factors were assessed using the Cox regression hazards model. The 1-, 3-, and 5-year survival rates were estimated with nomogram. Competitive risk models were used to identify prognostic risk factors related to endpoint events of osteosarcoma patients. Results: Overall, 722 samples were obtained from the extremities, 134 from the axial bones, and 119 from the cranial and mandible in SEER (2010-2016 cohort). After the preliminary diagnosis, the median survival time of patients with osteosarcoma was 39 months, and the 1-, 3-, and 5-year survival rates were 87.3%, 67.2%, and 58.0%, respectively (P < 0.001). The competitive risk model revealed no competitive risks of the endpoint event. Conclusion: Our study found out the prognostic factors in patients with Osteosarcoma by Cox regression hazards model, after that, nomogram was established to predict the 1-, 3-, and 5-year survival rates, which may help oncologists to understand the highly malignant tumor.

Unemployment and the rate of new contacts with mental health services in South London

2016 ◽  
Vol 33 (S1) ◽  
pp. S173-S174
Author(s):  
V. Bhavsar ◽  
M. Hotopf ◽  
J. Boydell ◽  
S. Hatch ◽  
Keyword(s):  
Mental Health ◽  
Mental Health Services ◽  
Health Services ◽  
Survey Data ◽  
Survival Data ◽  
Illicit Drugs ◽  
Suicide Attempts ◽  
Mental Health Problems ◽  
Cox Regression ◽  
First Contact

IntroductionUnemployment is a risk factor for later development of mental health problems, but characterisation of this in real world clinical data is limited. This study aimed to investigate the association between employment status and time-to-first-contact with mental health services using survey data linked to electronic health records(EHR).MethodsSELCoH (n = 1698, 2008–2010) was a representative population survey of South East London, with a 71.9% household participation rate. Anonymised survey data for participants was linked with EHR, generating survival data for time-to-first-contact. Cox regression was used to assess associations between unemployment and time to first contact with mental health services.ResultsThe rate in the unemployed was 22.84 contacts per 1000 person-years, and in those not unemployed, it was 10 contacts per 1000 person-years. The crude (age-adjusted) hazard ratio (HR) for unemployment was 3.09 (95% CI: 1.66–5.75). The HR for contact for unemployment, after adjusting for age, gender, ethnicity and education, was 2.8 (95% CI: 1.44–5.47). On addition of symptoms of common mental disorder, post-traumatic stress, psychosis and suicide attempts, to the model, unemployed participants remained at elevated risk (HR:2.65, 95% CI: 1.33–5.27). Finally, illicit drugs and alcohol had minimal influence on estimates, giving a fully-adjusted estimate for the association between unemployment and rate of contact of 2.6 (95% CI: 1.31–5.14).ConclusionsUnemployment was associated with a greater than two-fold increase in risk of accessing mental health care for the first time within the observation time, after adjustment for sociodemographic confounders, psychopathology, and substance use. Explanations for this association could include unobserved confounding, health behaviours associated with unemployment or effects of unemployment on stress processing.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Tumor response category for the indicator of prognosis: Analysis of survival data in a Four-Arm Cooperative Study (FACS) for advanced non-small cell lung cancer (NSCLC)

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 8088-8088
Author(s):  
H. Watanabe ◽  
R. Leki ◽  
K. Mori ◽  
Y. Takada ◽  
Y. Nishiwaki ◽  
...  
Keyword(s):  
Survival Data ◽  
Advanced Nsclc ◽  
Tumor Response ◽  
Cox Regression ◽  
Surrogate Endpoint ◽  
Response Category ◽  
Phase Iii ◽  
Cox Regression Analysis ◽  
Overall Response ◽  
Prognostic Groups

8088 Background: Tumor response, categorized into CR (complete response), PR (partial response), SD (stable disease) and PD (progressive disease), is a surrogate endpoint for survival and could be expected as a possible indicator of the prognosis. To evaluate whether the tumor response category might be used as an indicator of the prognosis, we conducted an analysis of the best overall response and survival data obtained from FACS, a phase III randomized trial comparing four platinum-based regimens for advanced NSCLC. Methods: A total of 602 patients (pts) with advanced NSCLC from 44 hospitals in Japan were registered in FACS. A retrospective review of the FACS database, including the tumor response and survival, was conducted. The tumor response as evaluated by the investigators was applied with and without confirmation of complete or partial responses at the determination of best overall response. Survival was calculated by the Kaplan-Meier method, and differences among prognostic groups were analyzed by Cox regression analysis. Results: Forty-five pts were excluded from the analysis due to nonavailability of sufficient data. The results are shown in the Table . The response categories of CR, PR and SD could not be categorized into prognostic groups, either with or without confirmation. There were, otherwise, two distinct prognostic groups: non-PD (CR, PR and SD) and PD. Conclusions: The disease control rate was a more sensitive indicator of the prognosis than the response rate in pts with advanced NSCLC registered in FACS. [Table: see text] [Table: see text]

Analysis of mismatch repair (MMR) proteins expression in a series of malignant pleural mesothelioma (MPM) patients.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e20062-e20062
Author(s):  
Susana Cedres ◽  
Santiago Ponce Aix ◽  
Ana Callejo ◽  
Nuria Pardo ◽  
Alejandro Navarro ◽  
...  
Keyword(s):  
Protein Expression ◽  
Survival Data ◽  
Cox Regression ◽  
Asbestos Exposure ◽  
Performance Status ◽  
Predictive Biomarkers ◽  
University Hospital ◽  
Tumor Biomarker ◽  
Neutrophil Lymphocyte Ratio ◽  
Mmr Proteins

e20062 Background: The increasing incidence and poor outcome associated with MPM demand identification of effective treatment options. Promising results have been reported with immunotherapy (IO) in a small proportion of MPM patients (p). MMR deficiency (dMMR) has been well described in several malignancies and was recently approved as a tumor biomarker for IO with anti-PD-1 checkpoint inhibitor. Next generation sequencing (NGS) data demonstrated that 2% of MPM harbor microsatellite instability. The aim of this study is to characterize MMR by immunohistochemistry (IHC) in a series of MPM p. Methods: Tumors of 159 MPM p from Vall d´Hebron University Hospital and October 12th University Hospital diagnosed between 2002 and 2017 were reviewed. Formalin-fixed, paraffin-embedded tissue was stained for MLH1, MSH2, MSH6 and PMS2 and tumors were classified as dMMR when any MMR protein expression was negative and MMR intact when all MMR proteins were positively expressed. Associations between clinical variables and outcome were assessed with Cox regression models and survival data were calculated by the Kaplan-Meier method. Results: P characteristics: median age: 69 years (29-88 years), males: 71%, performance status (PS) 1:69%, asbestos exposure: 52%, stage III at diagnosis: 42%, epithelial subtype: 65%, systemic treatment 81% (57% chemotherapy with cisplatin plus pemetrexed in first line), 50% received second line and 28% third line. MMR protein expression was analyzed in 158 samples with enough tissue and was positive in all of the cases. The median overall survival (mOS) in all population was 15 months (m) (13.5-18.8m). In a multivariate model factors associated to improved mOS were PS 0 vs PS2 (13 v 2 m, HR 12.8, p < 0.01), neutrophil-lymphocyte ratio (NLR) < 5 (18 v 9 m in NLR ≥5,HR 1.5, p < 0.05) and epitheliod vs sarcomatoid histology (18 vs 4 m HR 4.7, p < 0.01). Thirteen p received IO with anti-CTLA4 or anti-PD-1 blockade in clinical trials, 58% had a response or stable disease for more than 6 m, with median progression-free survival (PFS) of 5.7 m (2.1-26.1m). Conclusions: In our series we were unable to identify any MPM patient with dMMR by IHC. Further studies are needed to elucidate novel predictive biomarkers benefit from IO in MPM.

Molecular Staging of Intracranial Ependymoma in Children and Adults

2010 ◽  
Vol 28 (19) ◽  
pp. 3182-3190 ◽  
Author(s):  
Andrey Korshunov ◽  
Hendrik Witt ◽  
Thomas Hielscher ◽  
Axel Benner ◽  
Marc Remke ◽  
...  
Keyword(s):  
Genetic Markers ◽  
Survival Data ◽  
Copy Number ◽  
Cox Regression ◽  
Prognostic Significance ◽  
Staging System ◽  
Comparative Genomic ◽  
Molecular Staging ◽  
Copy Number Aberrations ◽  
Intracranial Ependymoma

Purpose The biologic behavior of intracranial ependymoma is unpredictable on the basis of current staging approaches. We aimed at the identification of recurrent genetic aberrations in ependymoma and evaluated their prognostic significance to develop a molecular staging system that could complement current classification criteria. Patients and Methods As a screening cohort, we studied a cohort of 122 patients with ependymoma before standardized therapy by using array-based comparative genomic hybridization. DNA copy-number aberrations identified as possible prognostic markers were validated in an independent cohort of 170 patients with ependymoma by fluorescence in situ hybridization analysis. Copy-number aberrations were correlated with clinical, histopathologic, and survival data. Results In the screening cohort, age at diagnosis, gain of 1q, and homozygous deletion of CDKN2A comprised the most powerful independent indicators of unfavorable prognosis. In contrast, gains of chromosomes 9, 15q, and 18 and loss of chromosome 6 were associated with excellent survival. On the basis of these findings, we developed a molecular staging system comprised of three genetic risk groups, which was then confirmed in the validation cohort. Likelihood ratio tests and multivariate Cox regression also demonstrated the clear improvement in predictive accuracy after the addition of these novel genetic markers. Conclusion Genomic aberrations in ependymomas are powerful independent markers of disease progression and survival. By adding genetic markers to established clinical and histopathologic variables, outcome prediction can potentially be improved. Because the analyses can be conducted on routine paraffin-embedded material, it will now be possible to prospectively validate these markers in multicenter clinical trials on population-based cohorts.

scholarly journals A Novel Autophagy-Related Prognostic Risk Model and a Nomogram for Survival Prediction of Oral Cancer Patients

2022 ◽  
Vol 2022 ◽  
pp. 1-13
Author(s):  
Hongjun Fei ◽  
Xiongming Chen
Keyword(s):  
Survival Data ◽  
Prognostic Model ◽  
Risk Model ◽  
Cox Regression ◽  
Characteristic Curve ◽  
Interaction Network ◽  
Receiver Operator Characteristic Curve ◽  
Functional Enrichment ◽  
Survival Prediction ◽  
Sequencing Data

Background. This study is aimed at constructing a risk signature to predict survival outcomes of ORCA patients. Methods. We identified differentially expressed autophagy-related genes (DEARGs) based on the RNA sequencing data in the TCGA database; then, four independent survival-related ARGs were identified to construct an autophagy-associated signature for survival prediction of ORCA patients. The validity and robustness of the prognostic model were validated by clinicopathological data and survival data. Subsequently, four independent prognostic DEARGs that composed the model were evaluated individually. Results. The expressions of 232 autophagy-related genes (ARGs) in 127 ORCA and 13 control tissues were compared, and 36 DEARGs were filtered out. We performed functional enrichment analysis and constructed protein–protein interaction network for 36 DEARGs. Univariate and multivariate Cox regression analyses were adopted for searching prognostic ARGs, and an autophagy-associated signature for ORCA patients was constructed. Eventually, 4 desirable independent survival-related ARGs (WDR45, MAPK9, VEGFA, and ATIC) were confirmed and comprised the prognostic model. We made use of multiple ways to verify the accuracy of the novel autophagy-related signature for survival evaluation, such as receiver-operator characteristic curve, Kaplan–Meier plotter, and clinicopathological correlational analyses. Four independent prognostic DEARGs that formed the model were also associated with the prognosis of ORCA patients. Conclusions. The autophagy-related risk model can evaluate OS for ORCA patients independently since it is accurate and stable. Four prognostic ARGs that composed the model can be studied deeply for target treatment.

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