Prognosis of hepatocellular carcinoma (HCC): Comparison of four staging systems in two French clinical trials

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 4589-4589 ◽  
Author(s):  
S. Collette ◽  
F. Bonnetain ◽  
X. Paoletti ◽  
M. Doffoel ◽  
O. Bouche ◽  
...  
Keyword(s):  
Predictive Accuracy ◽  
Cox Model ◽  
External Validation ◽  
Selection Procedure ◽  
Alcoholic Cirrhosis ◽  
Information Criteria ◽  
Carcinome Hépatocellulaire ◽  
Forward Selection ◽  
Prognostic Information ◽  
Staging Systems

4589 Background: The aims of our study were to compare performances of 4 staging systems and to explore how to improve prognostic classification among French patients with HCC whose main aetiology is alcoholic cirrhosis. Methods: We have pooled 2 RCTs in palliative condition from Federation Francophone de Cancerologie Digestive (FFCD): - FFCD 9403 comparing tamoxifen vs symptomatic treatment and - FFCD 9402 comparing chemoembolization + tamoxifen vs tamoxifen alone. They had respectively included 416 and 122 patients. Performance of Okuda, Cancer of the Liver Italian Program (CLIP), Barcelona Clinic Liver Cancer group (BCLC) and GRoupe d’Etude et de Traitement du Carcinome Hépatocellulaire scores have been compared using: Akaike information criteria (AIC), discriminatory ability (Harrell’s c and the Royston’s D statistics), monocity of gradients and predictive accuracy (Schemper statistics Vs). To explore how to improve classifications univariate and multivariate Cox model were performed. Variables with univariate p< 0.10 have been retained for multivariate analyses. A forward selection procedure has then been implemented. Bootstraps validation was performed to test the robustness of our results. Analyses were done for each trial and for the pooled database with trial stratification. Results: Median OS was 5,3 months (IC 95%: [4,6; 6,2]), 402 patients had (75%) an alcoholic cirrhosis aetiology . As shown in Table 1 , CLIP staging had the best properties, followed by Okuda and BCLC. Performances of all staging systems were rather disappointing. WHO staging for CLIP or alphafetoprotein for BCLC allowed a significant improvement of prognostic information. Conclusions: Our results suggest that CLIP staging seems to be most adapted to french patients, it could be better by associating WHO PS. An external validation of our result will be performed on another trial in palliative condition. [Table: see text] No significant financial relationships to disclose.

scholarly journals HBV-DNA Load-Related Peritumoral Inflammation and ALBI Scores Predict HBV Associated Hepatocellular Carcinoma Prognosis after Curative Resection

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Rui Liao ◽  
Cheng-You Du ◽  
Jian-Ping Gong ◽  
Fang Luo
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Function ◽  
Curative Resection ◽  
Predictive Accuracy ◽  
Hepatitis Virus ◽  
External Validation ◽  
Hbv Dna ◽  
Discriminative Ability ◽  
Staging Systems ◽  
Bclc Staging

Background. Both persistent inflammatory activity and liver function damage contribute to a poor prognosis of hepatocellular carcinoma (HCC). This study aimed to develop nomograms that incorporate hepatitis virus B (HBV)-related peritumoral inflammation score (PIS) and liver function based on ALBI score to predict postoperative outcomes of HCC.Methods.The prognostic roles of HBV-related preoperative PIS and ALBI scores in HCC recurrence were examined, and then two nomograms were constructed. The predictive accuracy and discriminative ability of the nomograms were compared with AJCC and BCLC staging systems of HCC.Results.PIS (HBV-PIS) and ALBI scores (HBV-ALBI) with different HBV-DNA loads had association with overall survival (OS) and/or recurrence-free survival (RFS) of HCC. The independent predictors of OS and RFS were incorporated into the corresponding nomograms. In the training cohort, the C-indexes of OS and RFS nomograms were 0.751 and 0.736, respectively. ROC analyses showed that both OS and RFS nomograms had larger AUC (0.775 and 0.739, respectively) than AJCC and BCLC staging systems. These results were verified by the internal and external validation cohorts.Conclusion. The proposed nomograms, including HBV-DNA load-related PIS and ALBI scores, were accurate in predicting survival for HCC after curative resection.

Somatosensory and Auditory Brain Stem Conduction after Head Injury: A Comparison with Clinical Features in Prediction of Outcome

Neurosurgery ◽  
1990 ◽  
Vol 26 (2) ◽  
pp. 278-285 ◽  
Author(s):  
Kenneth Lindsay ◽  
Aydin Pasaoglu ◽  
David Hirst ◽  
Gwen Allardyce ◽  
Ian Kennedy ◽  
...  
Keyword(s):  
Head Injury ◽  
Brain Stem ◽  
Evoked Potential ◽  
Predictive Accuracy ◽  
Normal Subjects ◽  
Prediction Of Outcome ◽  
Prognostic Information ◽  
Additional Information ◽  
Auditory Brain Stem ◽  
The Difference

Abstract Evoked potential conduction times in brain stem auditory (BCT) and central somatosensory pathways (CCT) were recorded from 23 normal subjects and 101 patients with severe head injury. Abnormalities in the CCT and the BCT findings correlated with the clinical indices of brain damage (coma score, motor response, pupil response, and spontaneous and reflex eye movements) in the head-injured patients and each correlated with outcome at 6 months from the injury. The CCT in the “best” hemisphere produced the strongest correlation with outcome (P&lt;0.001). The correlation of the CCT with outcome was stronger in the 47 patients examined 2 to 3 days after the injury (P&lt;0.001) compared to the 34 patients examined within 24 hours after the injury (P&lt;0.02). No such difference was noted for the BCT. Serial studies within the first 2 weeks of injury did not show a consistent pattern and repetition of the investigation over this period did not provide any additional information. We used an INDEP-SELECT discriminant analysis program to determine whether information from the evoked potential data could improve prediction of outcome based on clinical data alone. With the addition of the CCT, the predictive accuracy (expressed as the correct classification probability) increased only slightly from 77 to 80%, and the difference was not significant. We conclude that central somatosensory and auditory brain stem conduction times provide useful prognostic information in paralyzed or sedated patients, but when neurological examination is feasible the benefits of evoked potential analysis do not justify the effort involved in data collection.

External Validation of the Cardiac Surgery Score in a Quaternary Hospital in the United States of America

2021 ◽  
pp. 088506662110668
Author(s):  
Asha Singh ◽  
Chen Liang ◽  
Stephanie L. Mick ◽  
Chiedozie Udeh
Keyword(s):  
United States ◽  
Cardiac Surgery ◽  
United States Of America ◽  
Predictive Accuracy ◽  
External Validation ◽  
Cleveland Clinic ◽  
Area Under The Curve ◽  
The United States ◽  
Mortality Data ◽  
The Usa

Background The Cardiac Surgery Score (CASUS) was developed to assist in predicting post-cardiac surgery mortality using parameters measured in the intensive care unit. It is calculated by assigning points to ten physiologic variables and adding them to obtain a score (additive CASUS), or by logistic regression to weight the variables and estimate the probability of mortality (logistic CASUS). Both additive and logistic CASUS have been externally validated elsewhere, but not yet in the United States of America (USA). This study aims to validate CASUS in a quaternary hospital in the USA and compare the predictive performance of additive to logistic CASUS in this setting. Methods Additive and logistic CASUS (postoperative days 1-5) were calculated for 7098 patients at Cleveland Clinic from January 2015 to February 2017. 30-day mortality data were abstracted from institutional records and the Death Registries for Ohio State and the Centers for Disease Control. Given a low event rate, model discrimination was assessed by area under the curve (AUROC), partial AUROC (pAUC), and average precision (AP). Calibration was assessed by curves and quantified using Harrell's Emax, and Integrated Calibration Index (ICI). Results 30-day mortality rate was 1.37%. For additive CASUS, odds ratio for mortality was 1.41 (1.35-1.46, P <0.001). Additive and logistic CASUS had comparable pAUC and AUROC (all >0.83). However, additive CASUS had greater AP, especially on postoperative day 1 (0.22 vs. 0.11). Additive CASUS had better calibration curves, and lower Emax, and ICI on all days. Conclusions Additive and logistic CASUS discriminated well for postoperative 30-day mortality in our quaternary center in the USA, however logistic CASUS under-predicted mortality in our cohort. Given its ease of calculation, and better predictive accuracy, additive CASUS may be the preferred model for postoperative use. Validation in more typical cardiac surgery centers in the USA is recommended.

A new staging system for radiotherapy-based treatment of hepatocellular carcinoma: A multicenter cohort study.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e16155-e16155
Author(s):  
Ting-Shi Su ◽  
Shi-Xiong Liang ◽  
Li-Qing Li ◽  
Qiu-Hua Liu ◽  
Xiao-Fei Zhu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
External Validation ◽  
Staging System ◽  
Time Dependent ◽  
Multicenter Cohort Study ◽  
Discriminatory Ability ◽  
Training Cohort ◽  
Multicenter Cohort ◽  
Staging Systems

e16155 Background: External beam radiation therapy has been used as a palliative to radical treatment of hepatocellular carcinoma (HCC) depending on different tumor status, liver function and patient's general state of health. The existing models of HCC staging cannot perfectly predict the prognosis of radiotherapy. In this study, we aimed to set up a new staging system for radiotherapy-based treatment by incorporating bilirubin-albumin (ALBI) grade and tumor status for the prognostic classifications of HCC. Methods: This multicenter cohort study included 878 HCC patients who received radiotherapy-based treatment. A new staging system was established: stage I, solitary nodule without macrovascular invasion or 2-3 nodules with no more than 3.0 cm each other and PS 0-2 (Ia: ALBI-1 grade; Ib: ALBI-2 or 3 grade); stage II: 2-3 nodules with anyone more than 3.0 cm or ≥4 nodules and PS 0-2 (IIa: ALBI-1 grade; IIb: ALBI-2 grade); stage III: macrovascular invasion or regional lymph node metastasis or distant metastasis and PS 0-2 (IIIa: ALBI-1 grade; IIIb:ALBI-2 grade); stage IV: ALBI-3 grade without stage I patient or/and PS score 3-4. The new modified staging system and the existing staging systems, such as the BCLC, TNM, CNLC staging systems were used for prognostic analysis. All patients were separated into different stages and substages. The long-term overall survival outcomes and time-dependent receiver operating characteristic (ROC) were analyzed. Results: A training cohort of 595 patients underwent stereotactic body radiotherapy (SBRT) from 2011 to 2017 and an external validation cohort of 283 patients underwent intensity-modulated radiotherapy (IMRT) from 2000 to 2013 were included into establishing and validating the new staging system. In the training cohort, the median follow-up time was 55 months (range, 6–100 months), and the new staging system had a good discriminatory ability to separate patients into different stages with 4 notably different curves and substages with 7 notably different curves. BCLC staging could not differentiate stage 0 to A, and stage C to D in these selected patients. TNM staging could not completely distinguish stage IIIb to IV, but also stage Ia to Ib. CNLC staging could not differentiate among stage IIIa, IIIb, and IV. In the external validation, the median follow-up time was 95 months (range, 9–120 months), and the new staging system also had a good discriminatory ability to separate patients into different stages with 4 notably different curves and substages with 7 notably different curves. The new staging system had a better area under curve of time-dependent ROC than BCLC, TNM and CNLC staging in both SBRT and IMRT cohorts. Conclusions: The new modified (Su’s) staging system could provide a good discriminatory ability to separate patients into different stages and substages after radiotherapy treatment. It may be used to supplement the other HCC staging systems.

CDK5RAP3 as a Novel Biomarker Signature Predicting Survival and Adjuvant Chemotherapeutic benefit in Gastric Cancer

2020 ◽  
Author(s):  
Jia-Bin Wang ◽  
You-Xin Gao ◽  
Ning-Zi Lian ◽  
Yu-Bin Ma ◽  
Ping Li ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Adjuvant Chemotherapy ◽  
Cancer Patients ◽  
Cox Model ◽  
External Validation ◽  
Tumour Tissue ◽  
Tissue Samples ◽  
Significant Difference ◽  
Validation Set ◽  
Gastric Cancer Patients

Abstract Background: We previously demonstrated that CDK5RAP3 acts as a tumour suppressor in gastric cancer through negative regulation of the Wnt/β-catenin signalling pathway, but its function in chemotherapeutic responsiveness of gastric cancer has not been investigated. In this study, we aimed to examine the clinical significance of CDK5RAP3 to predict chemotherapeutic responsiveness in gastric cancer.Methods: A collection of 188 pairs of tumour tissue microarray specimens from Fujian Medical University were employed for the discovery set, and 310 tumour tissue samples of gastric cancer patients were employed for the internal validation set. Eight-five tumour tissue samples from Qinghai University Hospital were used as the external validation set 1. Transcriptomic and clinical data of 299 gastric cancer patients from TCGA were used as the external validation set 2. CDK5RAP3 expression, microsatellite instability (MSI) status, and tumour-infiltrating lymphocytes (TIL) were examined with immunohistochemistry. Clinical outcomes of patients were compared with Kaplan-Meier curves and the Cox model.Results: In a multi-centre evaluation, increased CDK5RAP3 indication of better prognosis depends mainly on MSI-L/MSS status or TILhigh. High CDK5RAP3 expression predicts sensitive therapeutic responsiveness to postoperative adjuvant chemotherapy in gastric cancer. In a stratification analysis based on CDK5RAP3 combined with TIL or MSI status, patients with CKD5RAP3low TILlow showed no significant difference in prognosis after receiving chemotherapy, whereas patients with CKD5RAP3low TILhigh, CKD5RAP3high TILlow, and CKD5RAP3high TILhigh had better responsiveness to chemotherapy. In addition, patients with CKD5RAP3high MSI-L/MSS status benefitted the most from adjuvant chemotherapy among all patients evaluated. Conclusions: CKD5RAP3 can be used as an effective marker to evaluate individualized chemotherapy regimens in gastric cancer patients dependent on their TIL and MSI status.

scholarly journals Derivation and Validation of Clinical Prediction Rules for COVID-19 Mortality in Ontario, Canada

2020 ◽  
Vol 7 (11) ◽  
Author(s):  
David N Fisman ◽  
Amy L Greer ◽  
Michael Hillmer ◽  
R Tuite
Keyword(s):  
Risk Stratification ◽  
Cox Model ◽  
External Validation ◽  
Sensitivity Analyses ◽  
Base Case ◽  
Clinical Prediction ◽  
Clinical Prediction Rules ◽  
Term Care ◽  
Prediction Rules ◽  
Validation Set

Abstract Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently causing a high-mortality global pandemic. The clinical spectrum of disease caused by this virus is broad, ranging from asymptomatic infection to organ failure and death. Risk stratification of individuals with coronavirus disease 2019 (COVID-19) is desirable for management, and prioritization for trial enrollment. We developed a prediction rule for COVID-19 mortality in a population-based cohort in Ontario, Canada. Methods Data from Ontario’s provincial iPHIS system were extracted for the period from January 23 to May 15, 2020. Logistic regression–based prediction rules and a rule derived using a Cox proportional hazards model were developed and validated using split-halves validation. Sensitivity analyses were performed, with varying approaches to missing data. Results Of 21 922 COVID-19 cases, 1734 with complete data were included in the derivation set; 1796 were included in the validation set. Age and comorbidities (notably diabetes, renal disease, and immune compromise) were strong predictors of mortality. Four point-based prediction rules were derived (base case, smoking excluded, long-term care excluded, and Cox model–based). All displayed excellent discrimination (area under the curve for all rules &gt; 0.92) and calibration (P &gt; .50 by Hosmer-Lemeshow test) in the derivation set. All performed well in the validation set and were robust to varying approaches to replacement of missing variables. Conclusions We used a public health case management data system to build and validate 4 accurate, well-calibrated, robust clinical prediction rules for COVID-19 mortality in Ontario, Canada. While these rules need external validation, they may be useful tools for management, risk stratification, and clinical trials.

scholarly journals A Modified TNM Classification for Primary Operable Colorectal Cancer

2020 ◽  
Author(s):  
Chundong Zhang ◽  
Zubing Mei ◽  
Junpeng Pei ◽  
Masanobu Abe ◽  
Xiantao Zeng ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Validation Cohort ◽  
Tnm Classification ◽  
Characteristic Curve ◽  
External Validation ◽  
Model Fitting ◽  
Information Criteria ◽  
Stage I ◽  
Internal Validation ◽  
Clinical Benefits

Abstract Background The American Joint Committee on Cancer (AJCC) 8th tumor/node/metastasis (TNM) classification for colorectal cancer (CRC) has limited ability to predict prognosis. Methods We included 45,379 eligible stage I-III CRC patients from the Surveillance, Epidemiology, and End Results Program. Patients were randomly assigned individually to a training (N =31,772) or an internal validation cohort (N =13,607). External validation was performed in 10,902 additional patients. Patients were divided according to T and N stage permutations. Survival analyses were conducted by a Cox proportional hazard model and Kaplan-Meier analysis, with T1N0 as the reference. Area under receiver operating characteristic curve (AUC) and Akaike information criteria (AIC) were applied for prognostic discrimination and model-fitting, respectively. Clinical benefits were further assessed by decision curve analyses. Results We created a modified TNM (mTNM) classification: stages I (T1-2N0-1a), IIA (T1N1b, T2N1b, T3N0), IIB (T1-2N2a-2b, T3N1a-1b, T4aN0), IIC (T3N2a, T4aN1a-2a, T4bN0), IIIA (T3N2b, T4bN1a), IIIB (T4aN2b, T4bN1b), and IIIC (T4bN2a-2b). In the internal validation cohort, compared to the AJCC 8th TNM classification, the mTNM classification showed superior prognostic discrimination (AUC = 0.675 vs. 0.667, respectively; two-sided P &lt;0.001) and better model-fitting (AIC = 70,937 vs. 71,238, respectively). Similar findings were obtained in the external validation cohort. Decision curve analyses revealed that the mTNM had superior net benefits over the AJCC 8th TNM classification in the internal and external validation cohorts. Conclusions The mTNM classification provides better prognostic discrimination than AJCC 8th TNM classification, with good applicability in various populations and settings, to help better stratify stage I-III CRC patients into prognostic groups.

scholarly journals QSAR Prediction Model to Search for Compounds with Selective Cytotoxicity Against Oral Cell Cancer

Medicines ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. 45 ◽  
Author(s):  
Junko Nagai ◽  
Mai Imamura ◽  
Hiroshi Sakagami ◽  
Yoshihiro Uesawa
Keyword(s):  
Prediction Model ◽  
Anticancer Drugs ◽  
Predictive Accuracy ◽  
Cell Cancer ◽  
External Validation ◽  
Selective Toxicity ◽  
Normal Cells ◽  
Validation Set ◽  
Structure Toxicity Relationship ◽  
Toxicity Relationship

Background: Anticancer drugs often have strong toxicity against tumours and normal cells. Some natural products demonstrate high tumour specificity. We have previously reported the cytotoxic activity and tumour specificity of various chemical compounds. In this study, we constructed a database of previously reported compound data and predictive models to screen a new anticancer drug. Methods: We collected compound data from our previous studies and built a database for analysis. Using this database, we constructed models that could predict cytotoxicity and tumour specificity using random forest method. The prediction performance was evaluated using an external validation set. Results: A total of 494 compounds were collected, and these activities and chemical structure data were merged as database for analysis. The structure-toxicity relationship prediction model showed higher prediction accuracy than the tumour selectivity prediction model. Descriptors with high contribution differed for tumour and normal cells. Conclusions: Further study is required to construct a tumour selective toxicity prediction model with higher predictive accuracy. Such a model is expected to contribute to the screening of candidate compounds for new anticancer drugs.

Identification and validation of a potent multi-mRNA signature for the prediction of early relapse in hepatocellular carcinoma

2019 ◽  
Vol 40 (7) ◽  
pp. 840-852 ◽  
Author(s):  
Jie Cai ◽  
Ying Tong ◽  
Lifeng Huang ◽  
Lei Xia ◽  
Han Guo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Messenger Rna ◽  
Validation Cohort ◽  
Expression Profiles ◽  
External Validation ◽  
Early Recurrence ◽  
Discovery Cohort ◽  
Early Relapse ◽  
Staging Systems

Abstract Early recurrence of hepatocellular carcinoma (HCC) is implicated in poor patient survival and is the major obstacle to improving prognosis. The current staging systems are insufficient for accurate prediction of early recurrence, suggesting that additional indicators for early recurrence are needed. Here, by analyzing the gene expression profiles of 12 Gene Expression Omnibus data sets (n = 1533), we identified 257 differentially expressed genes between HCC and non-tumor tissues. Least absolute shrinkage and selection operator regression model was used to identify a 24-messenger RNA (mRNA)-based signature in discovery cohort GSE14520. With specific risk score formula, patients were divided into high- and low-risk groups. Recurrence-free survival within 2 years (early-RFS) was significantly different between these two groups in discovery cohort [hazard ratio (HR): 7.954, 95% confidence interval (CI): 4.596–13.767, P < 0.001], internal validation cohort (HR: 8.693, 95% CI: 4.029–18.754, P < 0.001) and external validation cohort (HR: 5.982, 95% CI: 3.414–10.480, P < 0.001). Multivariable and subgroup analyses revealed that the 24-mRNA-based classifier was an independent prognostic factor for predicting early relapse of patients with HCC. We further developed a nomogram integrating the 24-mRNA-based signature and clinicopathological risk factors to predict the early-RFS. The 24-mRNA-signature-integrated nomogram showed good discrimination (concordance index: 0.883, 95% CI: 0.836–0.929) and calibration. Decision curve analysis demonstrated that the 24-mRNA-signature-integrated nomogram was clinically useful. In conclusion, our 24-mRNA signature is a powerful tool for early-relapse prediction and will facilitate individual management of HCC patients.

Sign in / Sign up

Export Citation Format

Share Document