scholarly journals Establishment of an integrated model for predicting survival and guiding treatment in local recurrence nasopharyngeal carcinoma

2020 ◽  
Author(s):  
Hao-Jun Xie ◽  
Xue-Song Sun ◽  
Guo-Dong Jia ◽  
Rui Sun ◽  
Dong-Hua Luo ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Nasopharyngeal Carcinoma ◽  
Local Recurrence ◽  
Prognostic Model ◽  
Recursive Partitioning ◽  
Multivariable Analysis ◽  
Risk Groups ◽  
Individual Treatment ◽  
Binary Partition ◽  
Ebv Dna

Abstract Objective:In this study, we aimed to establish an integrated prognostic model for local recurrence nasopharyngeal carcinoma (lrNPC) patients, and evaluate the benefit of re-radiotherapy (RT) in patients with different risk levels.Materials and methods:In total, 271 patients with lrNPC were retrospectively reviewed in this study. Overall survival (OS) was the primary endpoint. Multivariate analysis was performed to select the significant prognostic factors (P<0.05). A prognostic model for OS was derived by recursive partitioning analysis (RPA) combining independent predictors using the algorithm of optimized binary partition.Results:Three independent prognostic factors (age, relapsed T [rT] stage, and Epstein-Barr virus [EBV] DNA) were identified from multivariable analysis. Five prognostic groups were derived from an RPA model that combined rT stage and EBV DNA. After further pair-wise comparisons of survival outcome in each group, three risk groups were generated. We investigated the role of re-RT in different risk groups, and found that re-RT could benefit patients in the low (P<0.001) and intermediate-risk subgroups (P=0.017), while no association between re-RT and survival benefit was found in the high-risk subgroup (P=0.328).Conclusion:Age, rT stage and EBV DNA were identified as independent predictors for lrNPC. We established an integrated RPA-based prognostic model for OS incorporating rT stage and EBV DNA, which could guide individual treatment for lrNPC.

scholarly journals Selection and Validation of Chemotherapy Beneficiaries among Elderly Nasopharyngeal Carcinoma (NPC) Patients Treated with Intensity-Modulated Radiation Therapy (IMRT): A Large Real-World Study

2021 ◽  
Author(s):  
Yan-Ling Wu ◽  
Kai-Bin Yang ◽  
Ying Huang ◽  
Jing-Rong Shi ◽  
Qing-shui He ◽  
...  
Keyword(s):  
Nasopharyngeal Carcinoma ◽  
Real World ◽  
Poor Prognosis ◽  
Recursive Partitioning ◽  
Intensity Modulated Radiation Therapy ◽  
Risk Groups ◽  
Good Prognosis ◽  
Prognosis Group ◽  
Ebv Dna ◽  
Good Prognosis Group

Abstract Purpose: Using real-world evidence, this study aimed to identify elderly nasopharyngeal carcinoma (NPC) patients who would benefit from chemotherapy.Methods and Materials: 1,714 elderly NPC patients between April 2007 and December 2017 were identified. Recursive partitioning analysis (RPA) was used to generate risk-stratified outcomes. Prognostic factors were performed for individual comparisons of different risk groups to assess chemotherapy benefits.Results: The median follow-up was 59.3 (0.39-170.09) months. Epstein Barr virus (EBV) DNA and T stage were included in the RPA-generated risk stratification, categorizing patients into a good-prognosis group (EBV DNA ≤ 4,000 copies/mL & T1-2), and a poor-prognosis group (EBV DNA ≤ 4,000 copies/mL & T3-4 and EBV DNA > 4,000 copies/mL & any T). Over survival (OS) was significantly higher in the good-prognosis group compared with the training set (HR = 0.309, 95% CI = 0.184-0.517; P < 0.001), and validated in the testing set (HR = 0.276, 95% CI = 0.113-0.670; P = 0.002). In the poor-prognosis group, a significantly improved OS for chemoradiotherapy (CRT) compared with RT alone was observed (HR = 0.70, 95% CI = 0.55-0.88; P = 0.003). Patients who received induction chemotherapy (IC) + concurrent chemoradiotherapy (CCRT) and CCRT had a significantly improved OS compared with RT alone (IC+CCRT vs. RT alone: P = 0.002; CCRT vs. RT alone: P = 0.008) but not in the IC+RT group (P = 0.306). The 5-year OS for CRT vs. RT-alone with ACE-27 scores of 0, 1 and 2 were 76.0% vs. 70.0% (P = 0.014), 80.5% vs. 68.2% (P = 0.150) and 58.5% vs. 62.2% (P = 0.490), respectively; for those aged 60-64, 65-70 and ≥70 years old they were 80.9% vs. 75.9% (P = 0.068), 73.3% vs. 63.4% (P = 0.270) and 64.8% vs. 67.1% (P = 0.820), respectively.Conclusions: For elderly NPC patients a simple screening cutoff for chemotherapy beneficiaries might be EBV DNA＜4000 copies/ml & T3-4 and EBV DNA ≥4000 copies/ml & any T, but not for those >70 years old and with an ACE-27 score > 1. IC+CCRT and CCRT were effective forms of chemotherapy.

scholarly journals Circulating cell‐free epstein–barr virus DNA levels and clinical features in Moroccan patients with nasopharyngeal carcinoma

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Amina Gihbid ◽  
Raja Benzeid ◽  
Abdellah Faouzi ◽  
Jalal Nourlil ◽  
Nezha Tawfiq ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Lymph Node ◽  
Nasopharyngeal Carcinoma ◽  
Epstein Barr Virus ◽  
Disease Stage ◽  
Barr Virus ◽  
Ebv Dna ◽  
Epstein Barr ◽  
Pre Treatment ◽  
Moroccan Patients

Abstract Background The identification of effective prognosis biomarkers for nasopharyngeal carcinoma (NPC) is crucial to improve treatment and patient outcomes. In the present study, we have attempted to evaluate the correlation between pre-treatment plasmatic Epstein-Barr virus (EBV) DNA load and the conventional prognostic factors in Moroccan patients with NPC. Methods The present study was conducted on 121 histologically confirmed NPC patients, recruited from January 2017 to December 2018. Circulating levels of EBV DNA were measured before therapy initiation using real-time quantitative PCR. Results Overall, undifferentiated non-keratinizingcarcinoma type was the most common histological type (90.1 %), and 61.8 % of patients were diagnosed at an advanced disease stage (IV). Results of pre-treatment plasma EBV load showed that 90.9 % of patients had detectable EBV DNA, with a median plasmatic viral load of 7710 IU/ml. The correlation between pre-treatment EBV DNA load and the conventional prognostic factors showed a significant association with patients’ age (p = 0.01), tumor classification (p = 0.01), lymph node status (p = 0.003), metastasis status (p = 0.00) and overall cancer stage (p = 0.01). Unexpectedly, a significant higher level of pre-treatment EBV DNA was also found in plasma of NPC patients with a family history of cancer (p = 0.04). The risk of NPC mortality in patients with high pretreatment EBVDNA levels was significantly higher than that of those with low pre-treatment plasma EBV-DNA levels (p < 0.05). Furthermore, patients with high pre-treatment EBV-DNA levels (≥ 2000, ≥ 4000) had a significant low overall survival (OS) rates (p < 0.05). Interestingly, lymph node involvement, metastasis status and OS were found to be the most important factors influencing the EBV DNA load in NPC patients. Conclusions The results of the present study clearly showed a high association between pre-treatment EBV DNA load, the crucial classical prognostic factors (T, N, M and disease stage) of NPC and OS, suggesting that pre-treatment EBV DNA can be a useful prognostic biomarker in clinical decision-making and improving NPC treatment in Morocco.

Refining TNM-8 M1 categories with anatomic subgroups for previously untreated de novo metastatic nasopharyngeal carcinoma.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 6046-6046
Author(s):  
Sik-Kwan Chan ◽  
Cheng Lin ◽  
Shao Hui Huang ◽  
Tin Ching Chau ◽  
Qiaojuan Guo ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Nasopharyngeal Carcinoma ◽  
Bone Metastases ◽  
Validation Cohort ◽  
De Novo ◽  
Multivariable Analysis ◽  
Term Survival ◽  
Training Cohort ◽  
Study Results ◽  
Multivariable Analyses

6046 Background: The eighth edition TNM (TNM-8) classified de novo metastatic (metastatic disease at presentation) nasopharyngeal carcinoma (NPC) as M1 without further subdivision. However, survival heterogeneity exists and long-term survival has been observed in a subset of this population. We hypothesize that certain metastatic characteristics could further segregate survival for de novo M1 NPC. Methods: Patients with previously untreated de novo M1 NPC prospectively treated in two academic institutions (The University of Hong Kong [n = 69] and Provincial Clinical College of Fujian Medical University [n = 114] between 2007 and 2016 were recruited and re-staged based on TNM-8 in this study. They were randomized in 2:1 ratio to generate a training cohort (n = 120) and validation cohort (n = 63) respectively. Univariable and multivariable analyses (MVA) were performed for the training cohort to identify the anatomic prognostic factors of overall survival (OS). We then performed recursive partitioning analysis (RPA) which incorporated the anatomic prognostic factors identified in multivariable analyses and derived a new set of RPA stage groups (Anatomic-RPA groups) which predicted OS in the training cohort. The significance of Anatomic-RPA groups in the training cohort was then validated in the validation cohort. UVA and MVA were performed again on the validation cohorts to identify significant OS prognosticators. Results: The training and the validation cohorts had a median follow-up of 27.2 months and 30.2 months, respectively, with the 3-year OS of 51.6% and 51.1%, respectively. Univariable analysis (UVA) and multivariable analysis (MVA) revealed that co-existing liver and bone metastases was the only factor prognostic of OS. Anatomic-RPA groups based on the anatomic prognostic factors identified in UVA and MVA yielded good segregation (M1a: no co-existing liver and bone metastases and M1b: co-existing both liver and bone metastases; median OS 39.5 and 23.7 months respectively; P =.004). RPA for the validation set also confirmed good segregation with co-existing liver and bone metastases (M1a: no co-existing liver and bone metastases and M1b: co-existing liver and bone metastases), with median OS 47.7 and 16.0 months, respectively; P =.008). It was also the only prognostic factor in UVA and MVA in the validation cohort. Conclusions: Our Anatomic-RPA M1 stage groups with anatomical factors provided better subgroup segregation for de novo M1 NPC. The study results provide a robust justification to refine M1 categories in future editions of TNM staging classification.

Treatment Outcome and Prognostic Model for Stage IE/IIE Extranodal Natural Killer/T-Cell Lymphoma, Nasal Type: A Retrospective Study in a Cohort of 305 Patients with Long Term Follow-up

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 2718-2718
Author(s):  
Yuankai Shi ◽  
Bo Jia ◽  
Xiaohui He ◽  
Youwu Shi ◽  
Mei Dong ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
T Cell ◽  
Prognostic Model ◽  
Prognostic Index ◽  
Risk Groups ◽  
Natural Killer T Cell ◽  
Combined Chemoradiotherapy ◽  
Radiotherapy Alone ◽  
Killer T Cell

Abstract Background Extranodal natural killer/T-cell lymphoma, nasal type (ENKL) is a rare and distinct subtype of non-hodgkin lymphoma (NHL). The frequency was higher in Asia than in western countries and it has become the most common subtype of peripheral T-cell lymphomas in China. The majority of ENKL patients present with early stage. Optimal treatment modalities and prognostic factors for localized ENKL have not been fully defined. This study aimed to evaluate the optimal treatment strategy and prognostic factors for localized ENKL patients. Methods Between 2003 and 2013, three hundred and five patients with stage IE/IIE ENKL were comprehensively analyzed in this study. A total of 180 patients received combined chemoradiotherapy, with 111 patients received radiotherapy alone and 14 patients recieved chemotherapy alone. Chemotherapy regimens include GDP (gemcitabine, cisplatin, and dexamethasone), CHOP (epirubicin, cyclophosphamide, vincristine, and prednisolone) and other regimens. A total dose of 50 Gy to the primary tumor was considered as radical dose for ENKL, and additional 5 to 10 Gy was administered as a boost to the residual disease. Results The complete response (CR) rate for patients received chemoradiotherapy (n=175) was significantly higher than that for patients received radiotherapy alone (n=102) (89.1 % vs.77.5 %, P = 0.009) or chemotherapy alone (n=14) (89.1 % vs.21.4 %, P< 0.001). The median follow up time for all 305 patients was 38.7 (1.1 to 393) months. For 228 stage IE paranasal extension or IIE patients, 3-year overall survival (OS) in combined chemoradiotherapy (n=154), radiotherapy alone (n=60) and chemotherapy alone (n=14) groups were 85.7%, 73.3% and 57.1% respectively (chemoradiotherapy vs. radiotherapy, P=0.003; chemoradiotherapy vs. chemotherapy, P<0.001). For patients received combined chemoradiotherapy, GDP regimen (n=54) (included 10 patients with pegaspargase) could significantly improve 3-year progression-free survival (PFS) compared with CHOP-like (n=110) (included 10 patients with asparaginase) (88.9% vs. 70.9%, P =0.015).Patients received radiotherapy first followed by chemotherapy (n=84) was associated with superior 3-year PFS compared with patients initially received chemotherapy (n=96) (81.0% vs. 69.8%, P=0.034). But for 54 patients received GDP regimen, induction chemotherapy (n=17) could increase 3-year PFS (100.0% vs. 83.8%, P=0.112) and OS (100.0% vs. 86.5%, P=0.180). We identified 3 risk groups based on 3 prognostic factors (stage II, LDH elevated and paranasal extension) with different survival outcomes. The 3-year OS rates were 93.5%, 85.0% and 62.2% respectively for patients with no risk factors, 1 or 2 factors and 3 factors (P<0.001). Conclusions Combined chemoradiotherapy is the most optimal therapy strategy for stage IE paranasal extension or IIE ENKL patients. GDP or combined with pegaspargase regimen shows promising efficacy, significant superior to the traditional CHOP regimen. The sequence of chemotherapy and radiotherapy for patients received novel chemotherapy regimens still needs further assessment in phase 3 clinical trials. We identified 3 risk groups based on 3 prognostic factors (stage II, LDH elevated and paranasal extension) with different survival outcomes and this novel prognostic model may better predict prognosis than previous International Prognostic Index (IPI) and Korean Prognostic Index (KPI) score for ENKL patients with limited stage. Disclosures No relevant conflicts of interest to declare.

Development and validation of a prognostic model for overall survival in chemotherapy-naive men with metastatic castration-resistant prostate cancer (mCRPC) from the phase 3 prevail clinical trial.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 5022-5022
Author(s):  
Andrew J. Armstrong ◽  
Ping Lin ◽  
Celestia S. Higano ◽  
Cora N. Sternberg ◽  
Guru Sonpavde ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Overall Survival ◽  
Prognostic Factors ◽  
High Risk ◽  
Prognostic Model ◽  
Risk Groups ◽  
Multivariable Model ◽  
Training Set ◽  
Phase 3 ◽  
Testing Set

5022 Background: Prognostic models require updating to reflect contemporary medical practice. In a post hoc analysis of the phase 3 PREVAIL trial (enzalutamide vs placebo), we identified prognostic factors for overall survival (OS) in chemotherapy-naive men with mCRPC. Methods: Patients were randomly divided 2:1 into training (n = 1159) and testing (n = 550) sets. Using the training set, 23 predefined candidate prognostic factors (including treatment) were analyzed in a multivariable Cox model with stepwise procedures and in a penalized Cox proportional hazards model using the adaptive least absolute shrinkage and selection operator (LASSO) penalty (data cutoff June 1, 2014). A multivariable model predicting OS was developed using the training set; the predictive accuracy was assessed in the testing set using time-dependent area under the curve (tAUC). The testing set was stratified based on risk score tertiles (low, intermediate, high), and OS was analyzed using Kaplan-Meier methodology. Results: Demographics, disease characteristics, and OS were balanced between the training and testing sets; median OS was 32.7 months for both datasets. There were no enzalutamide treatment-prognostic factor interactions (predictors). The final multivariable model included 11 prognostic factors: prostate-specific antigen, treatment, hemoglobin, neutrophil-lymphocyte ratio, liver metastases, time from diagnosis to randomization, lactate dehydrogenase, ≥ 10 bone metastases, pain, albumin, and alkaline phosphatase. The tAUC was 0.74 in the testing set. Median (95% confidence interval [CI]) OS for the low-, intermediate-, and high-risk groups (testing set) were not yet reached (NYR) (NYR–NYR), 34.2 months (31.5–NYR), and 21.1 months (17.5–25.0). The hazard ratios (95% CI) for OS in the low- and intermediate-risk groups vs the high-risk group were 0.20 (0.14–0.29) and 0.40 (0.30–0.53), respectively. Conclusions: Our validated prognostic model incorporates factors routinely collected in chemotherapy-naive men with mCRPC treated with enzalutamide and identifies subsets of men with widely differing survival times. Clinical trial information: NCT01212991.

scholarly journals Development of a Novel Simple Model to Predict Mortality in Patients With Systemic Lupus Erythematosus Admitted to the Intensive Care Unit

2021 ◽  
Vol 8 ◽  
Author(s):  
Jinyan Guo ◽  
Zhen Huang ◽  
Maoxin Huang ◽  
Yujie He ◽  
Bing Han ◽  
...  
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Prognostic Factors ◽  
Risk Score ◽  
Lupus Erythematosus ◽  
Prognostic Model ◽  
Risk Groups ◽  
Systemic Lupus ◽  
Icu Mortality

Background: Patients with systemic lupus erythematosus (SLE) may sometimes require admission to the intensive care unit (ICU), and the outcome is poor. The aim of this study was to explore the clinical features of patients with SLE in the ICU, identify prognostic factors, and develop and evaluate a prognostic model to predict in-ICU mortality of patients with SLE.Patients and Methods: This was a single center retrospective study in a tertiary medical institution in China. A total of 480 SLE patients with 505 ICU admissions from 2010 to 2019 were screened, and 391 patients were enrolled. The clinical feature and outcomes of the patients were analyzed. According to the random number table, patients were divided into two mutually exclusively groups named derivation (n = 293) and validation (n = 98). Prognostic factors were identified by a Cox model with Markov Chain Monte Carlo simulation and evaluated by latent analysis. The risk score was developed based on the derivation group and evaluated using the validation group.Results: Among the 391 patients, 348 (89.0%) patients were females. The median age of patients was 34 years, and the median course of SLE was 6 months. The median APACHE II and SLEDAI were 17 and 10, respectively. The average in-ICU mortality was 53.4% (95% CI, 48.5–58.4%). A total of 186 patients were admitted to the ICU due to infection. Pneumonia (320/391, 81.8%) was the most common clinical manifestation, followed by renal disease (246/391, 62.9%). Nine prognostic factors were identified. The model had C statistic of 0.912 (95% CI, 0.889–0.948) and 0.807 (95% CI 0.703–0.889), with predictive range of 5.2–98.3% and 6.3–94.7% for the derivation and validation groups, respectively. Based on distribution of the risk score, 25.3, 49.5, and 25.2% of patients were stratified into the high, average, and low-risk groups, with corresponding in-ICU mortality of 0.937, 0.593, and 0.118, respectively.Conclusion: Nine prognostic factors including age, white blood cell count, alanine transaminase, uric acid, intracranial infection, shock, intracranial hemorrhage, respiratory failure, and cyclosporin A/tacrolimus usage were identified. A prognostic model was developed and evaluated to predict in-ICU mortality of patients with SLE. These findings may help clinicians to prognostically stratify patients into different risk groups of in-ICU mortality, and provide patients with intensive and targeted management.

Poor-prognosis nasopharyngeal carcinoma as defined by a molecularly distinct subgroup and prediction by a miRNA expression signature.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 6056-6056
Author(s):  
Lan Zhao ◽  
Feng Gao ◽  
Wang Wei ◽  
Xin Duan ◽  
Yuchen Zhang ◽  
...  
Keyword(s):  
High Risk ◽  
Nasopharyngeal Carcinoma ◽  
Clinical Outcomes ◽  
Distant Metastasis ◽  
Mirna Expression ◽  
Poor Prognosis ◽  
Prognostic Model ◽  
Cox Regression ◽  
Risk Groups ◽  
Training Cohort

6056 Background: Nasopharyngeal carcinoma (NPC) is a highly invasive and metastatic cancer, with diverse molecular characteristics and clinical outcomes. Our aim in this study is to dissect the molecular heterogeneity of NPC, followed by construction of a prognostic model for prediction of distant metastasis. Methods: For molecular subtyping of NPC using miRNA expression data, we selected 86 stage II (AJCC 7th Edition) NPC patients from GSE32960 as training cohort. The remaining 226 NPC patients from GSE32960 and 246 NPC patients from GSE70970 were used as two validation cohorts. Consensus clustering was employed for unsupervised classification of the training cohort. Classifier was built using support vector machine (SVM), and was validated in the two validation cohorts. Univariate and multivariate Cox regression analyses were employed for feature selection and constructing a prognostic model for predicting high-risk distant metastasis, respectively. Results: We identified three NPC subtypes (NPC1, 2, and 3) that are molecularly distinct and clinically relevant. NPC1 (~45%) is enriched for cell cycle related pathways, and patients classified to NPC1 have an intermediate survival; NPC3 (~19%) is enriched for immune related pathways, and has good clinical outcomes. More importantly, NPC2 (~36%) is associated with poor prognosis, and is characterized by upregulation of epithelial-mesenchymal transition (EMT). Out of the total 25 differentially expressed miRNAs in NPC2, miR-142, miR-26a, miR-141 and let-7i have significant prognostic power (p < 0.05), as determined by univariate Cox regression analysis. For identification of high-risk distant metastasis, we built a multivariate Cox regression model using the selected 4 miRNAs. Our model can robustly stratify NPC patients into high- and low- risk groups both in GSE32960 (HR 3.1, 95% CI 1.8-5.4, p = 1.2e-05) and GSE70970 (HR 2.2, 95% CI 1.1-4.5, p = 0.022) cohorts. Conclusions: We proposed for the first time that NPC can be stratified into three subtypes. Using a panel of 4 miRNAs, we established a prognostic model that can robustly stratify NPC patients into high- and low- risk groups of distant metastasis.

Development and validation of a prognostic model for overall survival in chemotherapy-naïve men with metastatic castration-resistant prostate cancer (mCRPC) from the phase III PREVAIL clinical trial.

2017 ◽  
Vol 35 (6_suppl) ◽  
pp. 138-138
Author(s):  
Andrew J. Armstrong ◽  
Ping Lin ◽  
Celestia S. Higano ◽  
Cora N. Sternberg ◽  
Guru Sonpavde ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
High Risk ◽  
Prognostic Model ◽  
Specific Antigen ◽  
Risk Groups ◽  
Phase Iii ◽  
Multivariable Model ◽  
Training Set ◽  
Testing Set

138 Background: Prognostic models require updating to reflect contemporary medical practice. In a post hoc analysis of the phase 3 PREVAIL trial (enzalutamide vs placebo), we identified prognostic factors for overall survival (OS) in chemotherapy-naïve men with mCRPC. Methods: Patients were randomly divided 2:1 into training (n = 1159) and testing (n = 550) sets. Using the training set, 23 predefined candidate prognostic factors (including treatment) were analyzed in a multivariable Cox model with stepwise procedures and in a penalized Cox proportional hazards model using the adaptive least absolute shrinkage and selection operator (LASSO) penalty (data cutoff June 1, 2014). A multivariable model predicting OS was developed using the training set; the predictive accuracy was assessed in the testing set using time-dependent area under the curve (tAUC). The testing set was stratified based on risk score tertiles (low, intermediate, high), and OS was analyzed using Kaplan-Meier methodology. Results: Demographics, disease characteristics, and OS were balanced between the training and testing sets; median OS was 32.7 months for both datasets. There were no enzalutamide treatment-prognostic factor interactions (predictors). The final multivariable model included 11 prognostic factors: prostate-specific antigen, treatment, hemoglobin, neutrophil-lymphocyte ratio, liver metastases, time from diagnosis to randomization, lactate dehydrogenase, ≥ 10 bone metastases, pain, albumin, and alkaline phosphatase. The tAUC was 0.74 in the testing set. Median (95% confidence interval [CI]) OS for the low-, intermediate-, and high-risk groups (testing set) were not yet reached (NYR) (NYR–NYR), 34.2 months (31.5–NYR), and 21.1 months (17.5–25.0). The hazard ratios (95% CI) for OS in the low- and intermediate-risk groups vs the high-risk group were 0.20 (0.14–0.29) and 0.40 (0.30–0.53), respectively. Conclusions: Our validated prognostic model incorporates factors routinely collected in chemotherapy-naïve men with mCRPC treated with enzalutamide and identifies subsets of men with widely differing survival times.

A New Prognostic Model for Extranodal Natural Killer/T Cell Lymphoma, Nasal Type

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 1769-1769
Author(s):  
Qingqing Cai ◽  
Xiaolin Luo ◽  
Ken H. Young ◽  
Huiqiang Huang ◽  
Guanrong Zhang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
High Risk ◽  
Prognostic Model ◽  
Cell Lymphoma ◽  
Prognostic Index ◽  
Roc Curves ◽  
Risk Groups ◽  
Survival Outcomes ◽  
Nasal Type

Abstract Background Extranodal natural killer (NK)/T–cell lymphoma, nasal type (ENKTL) is an aggressive disease with a poor prognosis. A better risk stratification is beneficial for clinical management in affected patients. Our recent study has shown that fasting blood glucose (FBG) was a novel, prognostic factor, (Cai et al, British Journal of Cancer, 108: 380–386,2013). This finding has not been integrated in the previous prognostic models for ENKTL Therefore, we aimed to design a new prognostic model, including FBG, for ENKTL which supports to identify high–risk patients eligible for advanced or more aggressive therapy. Patients and methods 158 newly diagnosed patients with ENKTL were analyzed between January 2003 and January 2011 at Sun Yat–sen University Cancer Center, China. Overall survival (OS) and progression free survival (PFS) were estimated using the Kaplan–Meier method. The significance of differences between survival was tested using the Log–rank test. Significant variables in the univariate analysis were selected as variables for the multivariate analysis of survival. The latter was performed by the Cox regression mode. We constructed receiver operating characteristic (ROC) curves and compared the areas under the ROC curves of total protein (TP), FBG, Korean Prognostic Index (KPI) and their combinations in comparison to the survival outcome. Results Of 158 patients, 156 patients had complete clinical information for the parameters of the International Prognostic Index (IPI) model and KPI model. The estimated 5–year overall survival rate in 158 patients was 59.2%. Independent prognostic factors included TP < 60 g/L, FBG > 100 mg/dL, KPI score ≥ 2. A new prognostic model was constructed by combining these prognostic factors: Group 1 (64 cases, 41.0%), no adverse factors; Group 2 (58 cases, 37.2%), one adverse factor; and Group 3 (34 cases, 21.8%), two or three adverse factors. The 5–year overall survival of these groups were 88.9%, 35.6% and 12.7%, respectively (p < 0.001). The survival curves according to the new prognostic model are shown in Fig. 1. The new model categorized three groups with significantly different survival outcomes. The new prognostic model was also efficient in discriminating the patients with low to low–intermediate risk IPI group and high–intermediate to high risk IPI group into three subgroups with different survival outcomes (p < 0.001). The KPI model balanced the distribution of patients into different risk groups better than IPI prognostic model (score 0: 12 cases, 7.7%; score 1: 38 cases, 24.4%; score 2: 42 cases, 26.9%; score 3–4: 64 cases, 41.0%), and it was able to differentiate patients with different survival outcomes (p < 0.001). In addition, the new prognostic model had a better prognostic value than did KPI model alone (p < 0.001), suggesting that TP and FBG reinforced the prognostic ability of KPI model (Table 1). Conclusions The new prognostic model we proposed for ENKTL, including the new prognostic indicator total protein and FBG, demonstrated balanced distribution of patients into different risk groups with better prognostic discrimination as compared to KPI model alone. Disclosures: No relevant conflicts of interest to declare.

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