Evaluating the time‐dependent predictive accuracy for event‐to‐time outcome with a cure fraction

2020 ◽  
Vol 19 (6) ◽  
pp. 955-974
Author(s):  
Ziwen Wang ◽  
Xiaoguang Wang
Keyword(s):  
Predictive Accuracy ◽  
Time Dependent ◽  
Cure Fraction

Histopathologic-Based Prognostic Factors of Colorectal Cancers Are Associated With the State of the Local Immune Reaction

2011 ◽  
Vol 29 (6) ◽  
pp. 610-618 ◽  
Author(s):  
Bernhard Mlecnik ◽  
Marie Tosolini ◽  
Amos Kirilovsky ◽  
Anne Berger ◽  
Gabriela Bindea ◽  
...  
Keyword(s):  
Predictive Accuracy ◽  
Early Stage ◽  
Univariate Analysis ◽  
Prognostic Significance ◽  
Tnm Staging ◽  
Time Dependent ◽  
Colorectal Cancers ◽  
Tumor Extension ◽  
T Stage ◽  
Immune Score

Purpose The prognosis of patients with colorectal cancer has sometimes proved uncertain; thus, the prognostic significance of immune criteria was compared with that of the tumor extension criteria using the American Joint Committee on Cancer/International Union Against Cancer–TNM (AJCC/UICC-TNM) staging system. Patients and Methods We studied the intratumoral immune infiltrates in the center of the tumor and in the invasive margin of 599 specimens of stage I to IV colorectal cancers from two independent cohorts. We analyzed these findings in relation to the degree of tumor extension and to the frequency of recurrence. Results Growth of the primary tumor and metastatic spread were associated with decreased intratumoral immune T-cell densities. Sixty percent of patients with high densities of CD8+ cytotoxic T-lymphocyte infiltrate presented with stage Tis/T1 tumor, whereas no patients with low densities presented with such early-stage tumor. In patients who did not relapse, the density of CD8 infiltrates was inversely correlated with T stage. In contrast, in patients whose tumor recurred, the number of CD8 cells was low regardless of the T stage of the tumor. Univariate analysis showed that the immune score was significantly associated with differences in disease-free, disease-specific, and overall survival (hazard ratio [HR], 0.64, 0.60, and 0.70, respectively; P < .005). Time-dependent receiver operating characteristic curve analysis illustrated the predictive accuracy of the immune parameters (c-index = 65.3%, time-dependent c-index [Cτ] = 66.5%). A final stepwise model for Cox multivariate analysis supports the advantage of the immune score (HR, 0.64; P < .001; Cτ = 67.9%) compared with histopathologic features in predicting recurrence as well as survival. Conclusion Assessment of CD8+ cytotoxic T lymphocytes in combined tumor regions provides an indicator of tumor recurrence beyond that predicted by AJCC/UICC-TNM staging.

scholarly journals Analysis of genome-wide mutation profile and establishment of risk signature for prognosis of bladder cancer

2020 ◽  
Author(s):  
Yanyun Zhao ◽  
Rong Ma ◽  
Fangxiao Liu ◽  
Liwen Zhang ◽  
Xuemei Lv ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Cox Regression ◽  
Predictive Accuracy ◽  
Predictive Ability ◽  
Time Dependent ◽  
Net Benefit ◽  
Data Set ◽  
Clinical Prognosis ◽  
Cox Regression Analysis ◽  
Mutation Profile

Abstract Background: Emerging studies have shown that a variety of gene mutations occur in development and progression of cancer and highly mutation genes could play oncogenic or tumor suppressive roles in cancer. Therefore, our aim is to explore mutation genes which affect the prognosis of bladder.Methods: Mutation profile was obtained and analyzed from TCGA data set. A mutation-based signature was established by multivariable Cox regression analysis. Kaplan-Meier was performed to assess the prognostic power of signature. Time-dependent ROC was conducted to evaluate predictive accuracy of signature for bladder cancer patients.Results: There are 20177 genes have alteration in 403 bladder patients and 662 of them were frequently variation (mutation frequency > 5%). In this study, we assessed the prognostic predictive ability of 662 highly mutated genes and identified a mutation signature as an independent indicator for predicting the prognosis of bladder. The time-dependent ROC showed that AUC were 0.893, 0.896, 0.916 and 0.965 at 1, 3, 5 and 10 year, respectively. Stratified analysis and Multivariate Cox analysis showed that this mutation signature was reliable and independent biomarker. Furthermore, the nomogram predictive model can be used to effectively predict clinical prognosis of bladder patients. The decision analysis curve showed patients with risk threshold of 0.03-0.92 potentially yielded clinical net benefit. Finally, we identified several signaling pathways that associated with risk score by GSEA and KEGG analysis including PI3K-Akt signaling pathway and so on.Conclusions: In general, this study provide an optimal mutation signature as potential prognosis biomarker for bladder patients.

On the validity of time‐dependent AUC estimation in the presence of cure fraction

2019 ◽  
Vol 61 (6) ◽  
pp. 1430-1447 ◽  
Author(s):  
Kassu M. Beyene ◽  
Anouar El Ghouch ◽  
Abderrahim Oulhaj
Keyword(s):  
Time Dependent ◽  
Cure Fraction ◽  
Auc Estimation

scholarly journals A direct method to evaluate the time-dependent predictive accuracy for biomarkers

Biometrics ◽  
2015 ◽  
Vol 71 (2) ◽  
pp. 439-449 ◽  
Author(s):  
Weining Shen ◽  
Jing Ning ◽  
Ying Yuan
Keyword(s):  
Predictive Accuracy ◽  
Direct Method ◽  
Time Dependent ◽  
A Direct Method

scholarly journals DNAJC10 Correlates with Tumor Immune Characteristics and Predicts the Prognosis of Glioma Patients

2021 ◽  
Author(s):  
Feng Liu ◽  
Zewei Tu ◽  
Junzhe Liu ◽  
Xiaoyan Long ◽  
Bing Xiao ◽  
...  
Keyword(s):  
T Cell ◽  
Immune Cell ◽  
Cox Regression ◽  
Predictive Accuracy ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Time Dependent ◽  
Prognostic Role

Abstract Background: A role of DNAJC10 has been reported in several cancers, but its function in glioma is not clear. The purpose of this study was to investigate the prognostic role and the underlying functions of DNAJC10 in glioma.Methods: Reverse transcription and quantitative polymerase chain reaction and western blotting were performed to quantify the relative DNAJC10 mRNA and protein expressions of clinical samples. Wilcoxon rank sum tests were used to compare DNAJC10 expression between or among glioma subgroups with different clinicopathological features. The overall survival (OS) rates of glioma patients with different DNAJC10 expression were compared with the Kaplan-Meier method (two-sided log-rank test). The prognosis-predictive accuracy of the DNAJC10 was evaluated by time-dependent receiver operating characteristic (ROC) curves. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes annotations were conducted using the “clusterProfiler” package. Single-sample gene set enrichment analysis was used to estimate immune cell infiltrations and immune-related function levels. The independent prognostic role of DNAJC10 was determined by univariate and multivariate Cox regression analyses. A DNAJC10-based nomogram model was established using multivariate Cox regression in the R package “rms.” Results: Higher DNAJC10 expression was observed in gliomas. It was upregulated in tumors with higher World Health Organization grade, isocitrate dehydrogenase wild-type status, 1p/19q non-co-deletion, and methylguanine-DNA methyltransferase unmethylated gliomas. Patients with gliomas with higher DNAJC10 expression had poorer prognoses than those with low-DNAJC10 gliomas. The predictive accuracy of 1/3/5-year OS of DNAJC10 was stable and robust using a time-dependent ROC model. Functional enrichment analysis recognized that T cell activation and T cell receptor signaling were enriched in higher DNAJC10 gliomas. Immune cell and stromal cell infiltrations, tumor mutation burden, copy number alteration burden, and immune checkpoint genes were also positively correlated with glioma DNAJC10 expression. A DNAJ10-based nomogram model was established and showed strong prognosis-predictive ability.Conclusion: Higher DNAJC10 expression correlates with poor prognosis of patients with glioma and is a potential and useful prognostic biomarker.

scholarly journals SURVIVAL MODELS IN THE CONTEXT OF MULTIPLICATIVE AND ADDITIVE HAZARDS

2019 ◽  
Vol 37 (3) ◽  
pp. 306
Author(s):  
Suely Ruiz GIOLO ◽  
Jaqueline Aparecida RAMINELLI
Keyword(s):  
Survival Analysis ◽  
Primary Biliary Cirrhosis ◽  
Goodness Of Fit ◽  
Operating Characteristic ◽  
Graphical Representation ◽  
Predictive Accuracy ◽  
Time Dependent ◽  
Survival Models ◽  
Biliary Cirrhosis ◽  
Additive Hazards

In survival analysis, multiplicative and additive hazards models provide the two principal frameworks to study the association between the hazard and covariates. When these models are considered for analyzing a given survival dataset, it becomes relevant to evaluate the overall goodness-of-fit and how well each model can predict those subjects who subsequently will or will not experience the event. In this paper, this evaluation is based on a graphical representation of the Cox-Snell residuals and also on a time-dependent version of the area under the receiver operating characteristic (ROC) curve, denoted by AUC(t). A simulation study is carried out to evaluate the performance of the AUC(t) as a tool for comparing the predictive accuracy of survival models. A dataset from the Mayo Clinic trial in primary biliary cirrhosis  (PBC) of the liver is also considered to illustrate the usefulness of these tools to compare survival models formulated under distinct hazards frameworks.

Neutrophil-lymphocyte score: A novel prognostic scoring system that utilized the dynamic change of neutrophil, lymphocyte, and albumin and its comparison to other indices.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 3048-3048
Author(s):  
Songzhu Zhao ◽  
Mingjia Li ◽  
Daniel Spakowicz ◽  
Sandip H. Patel ◽  
Andrew Johns ◽  
...  
Keyword(s):  
Scoring System ◽  
Prognostic Value ◽  
Predictive Accuracy ◽  
Dynamic Change ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Time Dependent ◽  
Advanced Lung Cancer ◽  
Lymphocyte Ratio ◽  
Lymphocyte To Monocyte Ratio

3048 Background: Indications for immune checkpoint inhibitor (ICI) in cancer care are expanding rapidly. There is increasing need for accurate decision tool to better guide treatment. We have constructed a new prognostic scoring system, neutrophil-lymphocyte score (NRS), based on the nonlinear dynamic change of neutrophil to lymphocyte ratio (NLR) in relation to survival over the first cycle of ICI treatment. We compared this novel system to existing indices such as NLR, lymphocyte to monocyte ratio (LMR), platelet to lymphocyte ratio (PLR), Advanced Lung Cancer Inflammation Index (ALI), and Systemic Immune-inflammation Index (SII). Methods: This is a retrospective analysis of 837 patients at Ohio State University from 2011-18. Neutrophil (ANC), lymphocyte (ALC), platelet (plt), monocyte (AMC), albumin (alb), and body mass index (BMI) were collected at baseline. Repeat labs were collected at cycle 2. NLR = ANC/ALC, ALI = BMI x alb / NLR, LMR = ALC/AMC, SII = platelet x NLR, PLR = plt/ALC. NLR Ratio = baseline NLR / repeat NLR. Based on the association between NLR and the overall survival, we assigned 1 point (p) for baseline NLR < 0.7, 6p for 0.7 to < 2, 5p for 2 to < 3, 4 p for 3 to < 4, 3 for 4 to 5, 2p for 5 to < 9, and 1p for ≥9. We also assigned 1p for NLR ratio < 0.6, 2p for 0.6 to < 0.8, 3p for 0.8 to < 1.2, 5p for 1.25 to < 1.4, 3p for 1.4 to < 1.6, and 2p for ≥1.6. NLS = sum of these 2 scores . NLS_A = NLS*alb. Time-dependent receiver operator characteristic (ROC) curves with integrated time-dependent area under the curve (TD AUC) values were used to evaluate the predictive accuracy of each index for survival. Results: For baseline and repeat values, all indices were statistically significant (P < 0.001) in predicting survival. Baseline integrated TD AUC were: ALI 0.704, NLR 0.692, SII 0.663, LMR 0.645, and PLR 0.612. All of the repeat indices at cycle 2 had higher prognostic value than their baseline counterparts. Integrated TD AUC for indices at cycle 2 were: ALI 0.740 (with baseline BMI), NLR 0.729, SII 0.694, LMR 0.671, and PLR 0.652. NLS_A was a composite score based on the dynamic change of NLR from cycle 1 to 2 and the treatment alb with integrated TD-AUC at 0.754. Conclusions: Indices constructed from ANC, ALC, AMC, Plt, alb, and BMI can be obtained inexpensively and provide great prognostic value for pts on ICI. We have constructed a novel scoring system (NLS_A) and demonstrated its improvement over the current prognostic indices. Studies with a larger cohort are needed to further improve and validate this system.

Predicting Criminal Recidivism in Adult Male Offenders

2010 ◽  
Vol 37 (8) ◽  
pp. 860-882 ◽  
Author(s):  
Natalie J. Jones ◽  
Shelley L. Brown ◽  
Edward Zamble
Keyword(s):  
Risk Assessment ◽  
Cox Regression ◽  
Predictive Accuracy ◽  
Area Under The Curve ◽  
Time Dependent ◽  
Community Supervision ◽  
Male Offenders ◽  
Parole Officers ◽  
Dynamic Factors ◽  
Time Dependent Covariates

In an attempt to bridge the gap between research and practice in the domain of criminal risk assessment, this study compared the predictive accuracy of dynamic risk assessments attained via an exhaustive research protocol to that achieved by the proxy ratings generated by parole officers. After an initial prerelease assessment, 127 male offenders under community supervision in Ontario, Canada, were assessed by parole officers and researchers at three different intervals (i.e., 1, 3, and 6 months postrelease). Cox regression survival analyses with time-dependent covariates and receiver operating characteristic analyses revealed moderate to high levels of predictive accuracy in both research-based and parole officer ratings (area under the curve [AUC] = .79 and .76, respectively). The strongest prediction model combined the research-based time-dependent dynamic factors with static items (AUC = .86), thus offering provisional support for the inclusion of prospectively rated dynamic factors in risk assessment protocols.

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