Accuracy For Overall Survival Research Articles

The repertoire of tumor-infiltrating lymphocytes within the microenvironment of oral squamous cell carcinoma reveals immune dysfunction.

The role of tumor-infiltrating lymphocytes (TILs) in the immune remodeling of tumor microenvironments (TME) in oral squamous cell carcinoma (OSCC) remains controversial. In this study, we pursued a comprehensive characterization of the repertoire of TILs and then analyzed its clinical significance and potential prognostic value. Fresh tumor tissue samples and peripheral blood from 83 OSCC patients were collected to comprehensively characterize the phenotypes and frequencies of TILs by flow cytometry. Archived paraffin-embedded tissues derived from 159 OSCC patients were analyzed by immunohistochemistry to further assess the TIL repertoire. The clinical significance of TILs and their potential prognostic value were further analyzed. A series of unique features of TILs were observed. IL-17 was highly expressed in betel nut chewers, and CD20 was abundantly expressed in patients who did not drink alcohol; high expression of CD138, PD-L1, and Foxp3 was associated with poor prognosis. The Th17/Treg ratio was an independent prognostic factor for patient survival with greater predictive accuracy for overall survival. Our results suggest an antigen-driven immune response; however, the immune dysfunction within the microenvironment in OSCC and the Th17/Treg balance may play important roles in the modulation of antitumor immunity.

Identifying a ten-microRNA signature as a superior prognosis biomarker in colon adenocarcinoma

BackgroundIncreasing studies have suggested that aberrant expression of microRNAs might play essential roles in the progression of cancers. In this study, we sought to construct a high-specific and superior microRNAs signature to improve the survival prediction of colon adenocarcinoma (COAD) patients.MethodsThe genome-wide miRNAs, mRNA and lncRNA expression profiles and corresponding clinical information of COAD were collected from the TCGA database. Differential expression analysis, Kaplan–Meier curve and time-dependent ROC curve were calculated and performed using R software and GraphPad Prism7. Univariate and multivariate Cox analysis was performed to evaluate the prognostic ability of signature. Functional enrichment analysis was analyzed using STRING database.ResultsWe identified ten prognosis-related microRNAs, including seven risky factors (hsa-miR-197, hsa-miR-32, hsa-miR-887, hsa-miR-3199-2, hsa-miR-4999, hsa-miR-561, hsa-miR-210) and three protective factors (hsa-miR-3917, hsa-miR-3189, hsa-miR-6854). The Kaplan–Meier survival analysis showed that the patients with high risk score had shorter overall survival (OS) in test series. And the similar results were observed in both validation and entire series. The time-dependent ROC curve suggested this signature have high accuracy of OS for COAD. The Multivariate Cox regression analysis and stratification analysis suggested that the ten-microRNA signature was an independent factor after being adjusted with other clinical characteristics. In addition, we also found microRNA signature have higher AUC than other signature. Furthermore, we identified some miRNA-target genes that affect lymphatic metastasis and invasion of COAD patients.ConclusionIn this study, we established a ten-microRNA signature as a potentially reliable and independent biomarker for survival prediction of COAD patients.

PCN146 VALIDATION OF PREDICTED SURVIVAL ESTIMATES FROM PREVIOUS DATA CUTS OF THE PHASE III CHECKMATE 025 STUDY IN ADVANCED RENAL CELL CARCINOMA

CheckMate 025 (CM-025; NCT01668784) is a randomized phase 3 trial investigating nivolumab and everolimus in pre-treated metastatic renal cell carcinoma (RCC). It has the longest follow-up of any phase III study of immunotherapy in pre-treated metastatic RCC. This study investigates the accuracy of overall survival (OS) modelling from previous data cuts of the CM-025 study. Parametric models were fitted to CM-025 trial data with minimum follow-up of 14.0 months, 26.1 months, and 39.4 months, using methods described in NICE Technical Support Document 14. Estimated survival rates and restricted mean survival (RMS) durations under each of the fitted models were compared against corresponding rates and RMS durations observed within the trial to assess predictive accuracy. Observed 3-year OS rates were 39.1% and 29.5% for nivolumab and everolimus, respectively. Predicted 3-year OS rates from the chosen parametric models (log-logistic) fitted to data at minimum follow-up of 14.0 months, 26.1 months, and 39.4 months were 39.1%, 39.0% and 39.6% for nivolumab, and 29.8%, 29.3%, and 30.0% for everolimus, respectively. The exponential and Weibull functions provided poorer fits, under predicting the 3-year rate for nivolumab by up to 4.3%. Observed 3-year RMS was 23.8 months and 20.6 months for nivolumab and everolimus respectively. Three-year RMS estimated for the data cut with 39.4 months minimum follow-up were 23.6 months for nivolumab and 20.6 months for everolimus. Nivolumab has consistently demonstrated superior and sustained OS compared with everolimus for pre-treated RCC patients over the long-term. OS rate predictions and RMS from the chosen functions fitted to previous data cuts of CM-025 were consistent with the longer-term observed data. This confirms that the base case parametric models fitted to previous data cuts submitted to reimbursement authorities were highly accurate.

Genome-wide mutation profiling and related risk signature for prognosis of papillary renal cell carcinoma.

The papillary renal cell carcinoma (pRCC) is a rare subtype of renal cell carcinoma with limited investigation. Our study aimed to explore a robust signature to predict the prognosis of pRCC from the perspective of mutation profiles. In this study, we downloaded the simple nucleotide variation data of 288 pRCC samples from The Cancer Genome Atlas (TCGA) database. "GenVisR" package was utilized to visualize gene mutation profiles in pRCC. The PPI network was conducted based on the STRING database and the modification was performed via Cytoscape software (Version 3.7.1). Top 50 mutant genes were selected and Cox regression method was conducted to identify the hub prognostic mutant signature in pRCC using "survival" package. Mutation Related Signature (MRS) risk score was established by multivariate Cox regression method. Receiver Operating Characteristic (ROC) curve drawn by "timeROC" was conducted to assess the predictive accuracy of overall survival (OS) and Kaplan-Meier analysis was then performed. Relationships between mutants and expression levels were compared by Wilcox rank-sum test. Function enrichment pathway analysis for mutated genes was performed by "org.Hs.eg.db", "clusterProfiler", "ggplot2" and "enrichplot" packages. Gene Set Enrichment Analysis was exploited using the MRS as the phenotypes, which worked based on the JAVA platform. All statistical analyses were achieved by R software (version 3.5.2). P value <0.05 was considered to be significant. The mutation landscape in waterfall plot revealed that a list of 49 genes that were mutated in more than 10 samples, of which 6 genes (TTN, MUC16, KMT2C, MET, OBSCN, LRP2) were mutated in more than 20 samples. Besides, non-synonymous was the most frequent mutation effect, and missense mutation was one of the most common mutation types in mutated genes across 248 samples. The AUC of MRS model consisted of 17 prognostic mutant signatures was 0.907 in 3-year OS prediction. Moreover, pRCC patients with high level of MRS showed the worse survival outcomes compared with that in low-level MRS group (P=0). In addition, correlation analysis indicated that 6 mutated genes (BAP1, OBSCN, NF2, SETD2, PBRM1, DNAH1) were significantly associated with corresponding expression levels. Last, functional enriched pathway analysis showed that these mutant genes were involved in multiple cancer-related crosstalk, including PI3K-AKT signaling pathway, JAK-STAT signaling pathway, extracellular matrix (ECM)-receptor interaction or cell cycle. In summary, our study was the first attempt to explore the mutation-related signature for predicting survival outcomes of pRCC based on the high-throughput data, which might provide valuable information for further uncovering the molecular pathogenesis in pRCC.

Incorporating MicroRNA into Molecular Phenotypes of Circulating Tumor Cells Enhances the Prognostic Accuracy for Patients with Metastatic Breast Cancer.

The molecular phenotype of circulating tumor cells (CTCs) was associated with clinical outcome of patients with breast cancer. CTCs isolated from patients with metastatic breast cancer (MBC) display a unique microRNA (miRNA) expression profile. The aim of this study was to enhance the prognostic accuracy of the CTC phenotype in patients with MBC, by incorporating miRNA into a combined prediction model. CTCs were detected by CellSearch and enriched by magnetic cell sorting. miRNA deep sequencing and quantitative polymerase chain reaction were used to screen and verify potentially CTC-specific miRNA candidates. Patients with MBC were enrolled from two independent cohorts, and overall survival (OS) and chemotherapy response were analyzed. We screened and identified that miR-106b was an upregulated molecule in patients with MBC with CTC ≥5/7.5 mL (n = 16) compared with patients with CTC = 0/7.5 mL (n = 16) and healthy donors (n = 8). The expression of CTC-specific miR-106b correlated with vimentin and E-cadherin in CTC and acted as an independent factor for predicting OS (hazard ratio 2.157, 95% confidence interval [CI] 1.098-4.239, p = .026). Although CTC-specific miR-106b, E-cadherin, and vimentin showed a prognostic potential independently, the prognostic performance for OS based on the combination of three markers was significantly enhanced in Cohort 1 (area under the curve [AUC] 0.752, 95% CI 0.658-0.847, n = 128) and further validated in Cohort 2 (AUC 0.726, 95% CI 0.595-0.856, n = 91). Besides, a combined model incorporating miR-106b was associated with therapy response. The phenotypic assemblies of CTC incorporating miR-106b show enhanced prognostic accuracy of overall survival in patients with MBC. In order to enhance the prognostic accuracy of the circulating tumor cell (CTC) phenotype in patients with metastatic breast cancer (MBC), this study screened and identified a CTC-specific microRNA (miRNA), miR-106b, as an upregulated molecule based on the comparison of miRNA profile between CTCs, primary tumors, and healthy blood donors. By incorporating miR-106b into a combined prediction model, the prognostic accuracy of the CTC phenotype for patients with MBC was greatly improved in both the training and validation cohorts. This work provides clinical evidence supporting the prognostic potential of CTC-specific miRNA for patients with MBC. These results indicate that developing CTC-specific miRNAs as new biomarkers will help to further optimize personalized therapy.

Modification of American Joint Committee on cancer prognostic groups for renal cell carcinoma.

BackgroundTo compare the predictive value of the current AJCC stage grouping for renal cell carcinoma (RCC) to our modifications.Patients and methodsA total of 2120 patients with RCC from Fudan University Shanghai Cancer Center (FUSCC) database and 74 506 counterparts from SEER database were included. Cox regression was used to calculate the relative impacts between prognostic groups. The predictive accuracy of overall survival (OS) was assessed using the concordance index (C‐index), which was compared by likelihood ratio test.ResultsIn FUSCC cohort, the 5‐year‐OS rate for T3N0M0 patients was higher than T1‐3N1M0 (72.7% vs 38.1%). The 5‐year‐OS rate for T4N0M0 was 36.2%, which was close to T1‐3N1M0 but not to T4N1M0 (0%) and TanyNanyM1 (12.6%). The elements of AJCC groups were regrouped according to the ranks of hazard ratios. The modified stages II (T3N0M0), III (T1‐3N1M0, T4N0M0), and IV (T4N1M0, TanyNanyM1) exhibited greater survival stratification than AJCC groups. The modifications were validated in SEER cohort and yielded similar survival outcomes. The predictive accuracy of OS in modified prognostic groups was significantly higher than AJCC groups in stages II‐IV subgroups in both FUSCC (C‐index: 0.801 vs 0.779, P < 0.001) and SEER cohort (C‐index: 0.770 vs 0.764, P < 0.001).ConclusionsThe modified AJCC prognostic groups for RCC provided significantly improved survival prediction compared with the 8th AJCC edition. A precise risk stratification of modified stages II‐IV disease provides an important basis for risk‐equivalent treatment recommendation.

A novel scoring system predicts postsurgical survival and adjuvant chemotherapeutic benefits in patients with pancreatic adenocarcinoma: Implications for AJCC-TNM staging

BackgroundWe evaluated the application of the latest 8th American Joint Committee on Cancer (AJCC) staging system in Chinese patients and determined whether the addition of biologic markers could improve the prediction of postsurgical survival in pancreatic adenocarcinoma (PC). MethodsThis multicenter study involved 1,223 consecutive patients who underwent margin-negative pancreatectomy for PC. A scoring system was devised based on AJCC pathologic parameters and biologic markers and defined using a Cox proportional hazards model. Prognostic accuracies were evaluated by concordance index (C-index) and Akaike information criterion (AIC). ResultsThe 8th edition AJCC staging system had a better survival distribution of PC with different stages and a similar C-index (0.62 in the training cohort, 0.60 in the validation cohort) than the 7th edition (0.59 in the training cohort, 0.58 in the validation cohort). Nevertheless, survival of resected patients with stage IIA or IIB disease was indistinguishable. Incorporation of postoperative carbohydrate antigen 19-9 (CA19-9) levels and tumor grade into the 8th edition AJCC staging system generated a scoring system with better predictive accuracy for overall survival (OS) (C-index of 0.73 and AIC of 4301.05 in the training cohort, C-index of 0.71 and AIC of 3309.23 in the validation cohort). More importantly, patients with median or higher scores experienced OS benefits from adjuvant chemotherapy. ConclusionPostoperative CA19-9 levels and tumor grade are two well-known PC biologic markers that could be incorporated into a standard AJCC staging system to refine risk stratification and predict OS benefit from adjuvant chemotherapy in resected PC.

Prognostic value of tripartite motif containing 29 expression in patients with gastric cancer following surgical resection.

Tripartite motif containing 29 (TRIM29) dysregulation serves an important function in the progression of numerous types of cancer, but its function in the prognosis of patients with gastric cancer remains unknown. The present study assessed the prognostic value of TRIM29 in patients with gastric cancer following surgical resection. A total of 243 fresh gastric adenocarcinoma and adjacent normal tissues were continuously retrieved from patients who underwent curative surgery for gastric cancer at the Cancer Hospital of Henan Province (Zhengzhou, China) between January 2005 and December 2011. The reverse transcription-quantitative polymerase chain reaction was performed to assess TRIM29 expression. The association between TRIM29 expression and clinicopathological features and prognosis was subsequently evaluated. The results of the present study revealed that the expression of TRIM29 was increased in the gastric cancer tissues compared with the normal adjacent tissues, and that upregulated expression of TRIM29 was associated with tumor cell differentiation, tumor stage, lymph node metastasis, and tumor-node-metastasis (TNM) stage. In the training and validation data, high TRIM29 expression was associated with poor overall survival in patients with gastric cancer. Furthermore, multivariate analysis identified that TRIM29 expression was an independent prognostic factor for overall survival, in addition to TNM stage and Lauren classification. Combining TRIM29 expression with the TNM staging system generated a novel predictive model that exhibited improved prognostic accuracy for overall survival in patients with gastric cancer. The present study revealed that TRIM29 was an independent adverse prognostic factor in patients with gastric cancer. Incorporating TRIM29 expression level into the TNM staging system may improve risk stratification and render prognosis more accurate in patients with gastric cancer.

Tumor-infiltrating Neutrophils is Prognostic and Predictive for Postoperative Adjuvant Chemotherapy Benefit in Patients With Gastric Cancer.

This study was aimed to investigate the prognostic value of tumor-infiltrating neutrophils (TINs) and to generate a predictive model to refine postoperative risk stratification system for patients with gastric cancer. TIN presents in various malignant tumors, but its clinical significance in gastric cancer remains obscure. The study enrolled 3 independent sets of patients with gastric cancer from 2 institutional medical centers of China. TIN was estimated by immunohistochemical staining of CD66b, and its relationship with clinicopathological features and clinical outcomes were evaluated. Prognostic accuracies were evaluated by C-index and Akaike information criterion. TINs in gastric cancer tissues ranged from 0 to 192 cells/high magnification filed (HPF), 0 to 117 cells/HPF, and 0 to 142 cells/HPF in the training, testing, and validation sets, respectively. TINs were negatively correlated with lymph node classification (P = 0.007, P = 0.041, and P = 0.032, respectively) and tumor stage (P = 0.019, P = 0.013, and P = 0.025, respectively) in the 3 sets. Moreover, multivariate analysis identified TINs and tumor node metastasis (TNM) stage as 2 independent prognostic factors for overall survival. Incorporation of TINs into well-established TNM system generated a predictive model that shows better predictive accuracy for overall survival. More importantly, patients with higher TINs were prone to overall survival benefit from postoperative adjuvant chemotherapy. These results were validated in the independent testing and validation sets. TIN in gastric cancer was identified as an independent prognostic factor, which could be incorporated into standard TNM staging system to refine risk stratification and predict for overall survival benefit from postoperative chemotherapy in patients with gastric cancer.

Stathmin 1 expression predicts prognosis and benefits from adjuvant chemotherapy in patients with gallbladder carcinoma.

BackgroundAbnormal expression of Stathmin 1(STMN1) plays an important role in the proliferation and migration of gallbladder carcinoma (GBC). The purpose of current study is to investigate the prognostic significance of STMN1 in GBC patients after surgery.MethodsSTMN1 expression was evaluated with immunohistochemistry (IHC) on tissue microarrays from 70 GBC patients from a single institution between 2009 and 2013. The correlation between STMN1 expression and clinicopathological profiles and the prognosis was statistically inspected.ResultsHigh expression of STMN1 in tumoral tissue was associated with poor tumor differentiation (P<0.001), lymph node metastasis (P=0.028), advanced TNM stage (P=0.011) and short overall survival (P<0.001). Cox multivariate analysis identified the STMN1 expression as an independent prognostic factor. Integrating STMN1 expression with current TNM staging system generate a better clinical predictive model for GBC. Moreover, the postoperative adjuvant chemotherapy (ACT) showed significant benefit in TNM III- IV stage patients with low STMN1 expression.ConclusionSTMN1 might be an independent adverse prognostic factor in GBC patients after surgery, which could be combined with TNM staging system to improve the predictive accuracy for overall survival. Low expression of STMN1 stratified a subgroup of advanced GBC patients who could benefit from ACT.

Decreased expression of STING predicts poor prognosis in patients with gastric cancer

STING (stimulator of interferon genes) has recently been found to play an important role in host defenses against virus and intracellular bacteria via the regulation of type-I IFN signaling and innate immunity. Chronic infection with Helicobacter pylori is identified as the strongest risk factor for gastric cancer. Thus, we aim to explore the function of STING signaling in the development of gastric cancer. Immunohistochemistry was used to detect STING expression in 217 gastric cancer patients who underwent surgical resection. STING protein expression was remarkably decreased in tumor tissues compared to non-tumor tissues, and low STING staining intensity was positively correlated with tumor size, tumor invasion depth, lymph mode metastasis, TNM stage, and reduced patients’ survival. Multivariate analysis identified STING as an independent prognostic factor, which could improve the predictive accuracy for overall survival when incorporated into TNM staging system. In vitro studies revealed that knock-down of STING promoted colony formation, viability, migration and invasion of gastric cancer cells, and also led to a defect in cytosolic DNA sensing. Besides, chronic H. pylori infection up-regulated STING expression and activated STING signaling in mice. In conclusion, STING was proposed as a novel independent prognostic factor and potential immunotherapeutic target for gastric cancer.

SU-F-R-04: Radiomics for Survival Prediction in Glioblastoma (GBM)

Purpose: To develop a quantitative radiomics approach for survival prediction of glioblastoma (GBM) patients treated with chemoradiotherapy (CRT). Methods: 28 GBM patients who received CRT at our institution were retrospectively studied. 255 radiomic features were extracted from 3 gadolinium-enhanced T1 weighted MRIs for 2 regions of interest (ROIs) (the surgical cavity and its surrounding enhancement rim). The 3 MRIs were at pre-treatment, 1-month and 3-month post-CRT. The imaging features comprehensively quantified the intensity, spatial variation (texture), geometric property and their spatial-temporal changes for the 2 ROIs. 3 demographics features (age, race, gender) and 12 clinical parameters (KPS, extent of resection, whether concurrent temozolomide was adjusted/stopped and radiotherapy related information) were also included. 4 Machine learning models (logistic regression (LR), support vector machine (SVM), decision tree (DT), neural network (NN)) were applied to predict overall survival (OS) and progression-free survival (PFS). The number of cases and percentage of cases predicted correctly were collected and AUC (area under the receiver operating characteristic (ROC) curve) were determined after leave-one-out cross-validation. Results: From univariate analysis, 27 features (1 demographic, 1 clinical and 25 imaging) were statistically significant (p<0.05) for both OS and PFS. Two sets of features (each contained 24 features) were algorithmically selected from all features to predict OS and PFS. High prediction accuracy of OS was achieved by using NN (96%, 27 of 28 cases were correctly predicted, AUC = 0.99), LR (93%, 26 of 28 cases were correctly predicted, AUC = 0.95) and SVM (93%, 26 of 28 cases were correctly predicted, AUC = 0.90). When predicting PFS, NN obtained the highest prediction accuracy (89%, 25 of 28 cases were correctly predicted, AUC = 0.92). Conclusion: Radiomics approach combined with patients’ demographics and clinical parameters can accurately predict survival in GBM patients treated with CRT.

Increased Expression of CSF-1 Associates With Poor Prognosis of Patients With Gastric Cancer Undergoing Gastrectomy.

Clinical significance of diametrically polarized tumor-associated macrophages in gastric cancer has been elucidated in our previous study, whereas the role of cytokines that orchestrate tumor-associated macrophages polarization in gastric cancer remains elusive. The study aims to evaluate the prognostic value of colony-stimulating factor-1 expression in patients with gastric cancer. We examined the colony-stimulating factor-1 expression in tumor tissues by immunohistochemical staining in retrospectively enrolled 365 patients with gastric cancer undergoing gastrectomy at Zhongshan Hospital during 2008. Kaplan-Meier analysis and Cox regression models were used to evaluate the prognostic value of colony-stimulating factor-1 expression and its association with clinicopathological factors. A predictive nomogram by integrating colony-stimulating factor-1 expression with the TNM staging system was generated for overall survival evaluation of the patients. High colony-stimulating factor-1 expression predicted an unfavorable outcome in gastric cancer. The colony-stimulating factor-1 expression in tumor tissue could give a further discrimination for the prognosis of gastric cancer patients. Cox multivariate analysis identified the colony-stimulating factor-1 expression as an independent prognostic factor. The generated nomogram performed well in predicting the 3- and 5-year overall survival of gastric cancer patients.T he colony-stimulating factor-1 is a potential independent adverse prognosticator for gastric cancer patients, which could be integrated with the tumor-associated macrophages staging system to improve the predictive accuracy for overall survival, especially in advanced tumors.

Increased expression of C-C motif ligand 2 associates with poor prognosis in patients with gastric cancer after gastrectomy.

Previous studies have demonstrated the clinical significance of polarized tumor-associated macrophages (TAMs) in gastric cancer whereas the cytokines orchestrating TAM polarization remain elusive. This study aims to evaluate the prognostic value of C-C motif ligand 2 (CCL2) expression in gastric cancer patients after surgery. We examined CCL2 expression in tumor tissues by immunohistochemical staining in retrospectively enrolled 414 gastric cancer patients receiving gastrectomy at Zhongshan Hospital during 2008. We used Kaplan-Meier analysis and Cox regression models to assess the prognostic value of CCL2 expression. We generated a predictive nomogram from integrating CCL2 expression with the TNM staging system to evaluate 3- and 5-year overall survival. High intratumor CCL2 expression associated with adverse clinical outcome. Intratumor CCL2 expression provided additional prognostic value in gastric cancer patients. CCL2 expression, as well as well-established TNM staging parameters, was identified as independent prognostic factor for overall survival. The generated nomogram corresponded well with the ideal model in predicting the 3- and 5-year overall survival of gastric cancer patients. CCL2, an identified potential independent adverse prognosticator, could be integrated with TNM staging system to improve the predictive accuracy for overall survival in gastric cancer patients especially with advanced stages.

A new PET/CT volumetric prognostic index for non-small cell lung cancer.

Whole-body metabolic tumor volume (MTVWB) has been shown of prognostic value for non-small cell lung cancer (NSCLC) beyond that of TNM stage, age, gender, performance status, and treatment selection. The current TNM staging system does not incorporate tumor volumetric information. We propose a new PET/CT volumetric prognostic (PVP) index that combines the prognostic value of MTVWB and TNM stage. Based on 328 consecutive NSCLC patients with a baseline PET/CT scan before treatment, from which MTVWB was measured semi-automatically, we estimated hazard ratios (HRs) for ln(MTVWB) and TNM stage from a Cox proportional hazard regression model that consisted of only ln(MTVWB) and TNM stage as prognostic variables of overall survival. We used the regression coefficients, which gave rise to the HRs, as weights to formulate the PET/CT volumetric prognostic (PVP) index. We also compared the prognostic value of the PVP index against that of TNM stage alone and ln(MTVWB) alone with univariate and multivariate survival analyses and C-statistics. Univariate analysis C-statistic for the PVP index (C=0.71) was statistically significantly greater than those for TNM stage alone (C=0.67, p<0.01) and for ln(MTVWB) alone (C=0.69, p=0.033). Multivariate analyses showed that the PVP index yielded significantly greater discriminatory power (C=0.74) than similar models based on either TNM stage (C=0.72, p<0.01) or ln(MTVWB) (C=0.73, p<0.01). Lower values of the PVP index were associated with significantly better overall survival (adjusted HR=2.70, 95%CI [2.16, 3.37]). The PVP index provides a practical means for clinicians to combine the prognostic value of MTVWB and TNM stage and offers significantly better prognostic accuracy for overall survival of NSCLC patients than the current TNM staging system or metabolic tumor burden alone.

Abstract 2353: A comparative meta-analysis of prognostic gene signatures for late-stage ovarian cancer

Abstract Numerous gene signatures of patient prognosis for late-stage, high-grade serous ovarian cancer (HSOC) have been proposed, but diverse data and methods make these difficult to compare or prioritize for clinical application. However, the corresponding volume of publicly available expression data creates an opportunity to validate previous findings and to develop more robust signatures. To establish the current state of HSOC prognostic gene signatures, we undertook a systematic review and meta-analysis of the publicly available microarray data and published prognostic gene signatures. This effort generated a curated database of 1,319 clinically annotated HSOC microarray assays from 10 studies (Ganzfried et al., DATABASE 2013) and implementations of 14 published prognostic signatures for evaluation in independently available data. For each published prognostic signature we evaluated 1) its reproducibility, 2) its prognostic accuracy for overall survival in independent datasets, and 3) the prognostic value of the genes used in each signature relative to random gene sets. Twelve published models performed better than 97.5% of randomized risk scores, and six out-performed 97.5% of random signatures of the same size trained on the same data. The four top-ranked models achieved overall validation C-Indices of 0.56 to 0.60, and shared anti-correlation with expression of immune response pathways. Most models demonstrated lower accuracy in new datasets than in validation sets presented in their publication. This analysis provides definitive support for several prognostic models, but confirms that these require improvement to be of clinical value. This work addresses outstanding controversies in the ovarian cancer literature, including whether the prognostic signature proposed by The Cancer Genome Atlas Consortium (Nature 2011) improved on existing signatures, the impact of batch effects on a frequently re-used, high-profile dataset (Dressman et al., J Clin Oncol 2007), and the prognostic value of a recently proposed DNA damage repair signature (Kang et al., J Natl Cancer Inst 2012). Finally, this work provides a reproducible framework for meta-analytic evaluation of gene signatures. Citation Format: Levi Waldron, Markus Riester, Michael Birrer, Giovanni Parmigiani. A comparative meta-analysis of prognostic gene signatures for late-stage ovarian cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2353. doi:10.1158/1538-7445.AM2014-2353

Multicenter validation of the prognostic value of patient age in patients treated with radical cystectomy

Small studies have suggested that older patients have worse outcomes following radical cystectomy (RC) for urothelial carcinoma of the bladder (UCB). We evaluated the association of patient age with clinical outcomes in a large multi-institutional RC series. Data were collected from 4,429 patients treated with RC and lymphadenectomy for UCB without neoadjuvant chemotherapy. Age at RC was analyzed both as a continuous and categorical variable. Higher age at RC, analyzed as a continuous or categorical variable, was associated with advanced pathologic stage (P < 0.001), higher tumor grade (P = 0.045), presence of lymphovascular invasion (P = 0.018), and positive soft-tissue surgical margin status (P = 0.004). Elderly patients were less likely to receive postoperative chemotherapy (P < 0.001). In multivariable analyses, higher age was associated with disease recurrence, cancer-specific, and overall mortality (P < 0.001). Patients ≥ 80 years had a significantly greater risk of cancer-specific mortality than patients <50 years (HR 1.763, P < 0.001). Age minimally improved the accuracy of a base model that included standard pathologic features for prediction of disease recurrence (+0.2-0.3%) and cancer-specific survival (+0.3%). Conversely, age improved the predictive accuracy for overall survival by a sizeable margin (+4.2-4.5%). This large external validation study confirms that advanced patient age is minimally but significantly associated with worse prognosis after RC. Nevertheless, a large proportion of elderly patients benefitted from RC with curative intent. We need to improve our understanding of the reasons for the worse UCB outcomes in this growing segment of the population and to develop strategies to improve cancer care in the elderly.