Prognostic Index Model Research Articles

Clinical Characteristics and Survival in Patients with EBV Positive Diffuse Large B- Cell Lymphoma, Not Otherwise Specified: Report of 60 Cases

Introduction: Epstein Barr virus-positive (EBV+) diffuse large B- cell lymphoma (DLBCL), not otherwise specified (NOS) is a new entity recognized in the 4th edition of the 2016 classification of the WHO. Prevalence rates range from 5% in Western countries to 10-15% in Asia and South America. The IPI and Oyama score are prognostic factors for survival in this entity. The aim of this study is to evaluate the clinical characteristics and survival in EBV+ DLBCL, NOS.Methods: The study was retrospective, reviewing clinical records of patients treated at Rebagliati Martins Hospital between years 2002 - 2017. Patients of both sexes greater than or equal to eighteen years of age with the diagnosis of EBV+DLBCL, NOS were included. IRB approval was obtained prior to research. Pathological samples were reviewed by hematopathologists at our institution to confirm the diagnosis. Pertinent clinicopathological data were collected through chart review and are presented using descriptive statistics. Overall survival (OS) was determinate according to the Kaplan -Meier method, the comparison of the survival curves were made with the log-rank test. Univariate and multivariate Cox proportional-hazard regression models were fitted to evaluate hazard ratios (HR) for OS.Results: A total of 60 patients with a diagnosis of EBV+DLBCL, NOS were included in this analysis. The median age at diagnosis was 70 years (range 25-95 years), 62 % of patients were older than 60 and there was a male predominance (65%). Activated B-cell phenotype (ABC) was present in 57% of patients. Clinically, 62% presented ECOG >1, 52% had elevated serum LDH, 57% had B symptoms, 67% had an extranodal disease and 55% had stage III/IV. IPI score distribution was low-risk in 28% of patients, low-intermediate in 16%, high-intermediate in 30% and high-risk in 26% of patients. The Oyama score distribution was low risk in 20 % of patients, intermediate risk 45 % and high risk in 35% of patients. NCCN-IPI score distribution was low-risk in 5% of patients, low-intermediate in 25%, high-intermediate in 42% and high-risk in 28% of patients. 51% of patients received R-CHOP, 29% received CHOP, and 20% received other regimens. The overall response rate was 56%; 44% had a complete response and 12% had a partial response. The 5-year OS rate was 38% with a median of 9 months. In the univariate analysis, ECOG 2-4 (p=0.001), stage III/IV (p=0.001), CHOP and others regimens (p=0.025) were associated with a poor prognosis. EBV+ DLBCL, NOS patients with low, low-intermediate, high-intermediate and high-risk IPI had 5-year OS rates of 47%, 66%, 29% and 27%, respectively (p=0.006). In the NCCN-IPI score, EBV+ DLBCL, NOS patients with low/ low-intermediate, high-intermediate and high-risk had 5-year OS rates of 55%, 41%, 21%, respectively (p=0.014). In the Oyama score, EBV+ DLBCL, NOS patients with low, intermediate and high-risk had 5-year OS rates of 68%, 47%, 27%, respectively (p=0.004) In the multivariate analysis, patients with stage III/IV had a worse outcome (HR 3.8, 95% 1.6-9.2; p=0.003). The IPI score (HR 2.6, 95%CI, 1.1-6.3), NCCN-IPI score (HR3.4, 95%CI, 1.3-8.6, and Oyama score (HR 6.8, 95%CI, 1.5-31.2) were significant in the high-risk group.Conclusions: This is the largest Latin American cohort with EBV positive DLBCL, NOS reported so far. This entity is an aggressive tumor with a worse prognosis. IPI, NCCN-IPI and Oyama score are good prognostic index models for this disease. Rituximab appears to improve OS. [Display omitted] DisclosuresCastillo:Janssen: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; Millennium: Research Funding; Beigene: Consultancy, Research Funding; Genentech: Consultancy; Abbvie: Consultancy, Research Funding.

A Panel of MicroRNA Signature as a Tool for Predicting Survival of Patients with Urothelial Carcinoma of the Bladder.

Introduction and Objectives MicroRNA (miRNA) expression is altered in urologic malignancies, including urothelial carcinoma of the bladder (UCB). Individual miRNAs have been shown to modulate multiple signaling pathways that contribute to BC. To identify a panel of miRNA signature that can predict aggressive phenotype from normal nonaggressive counterpart using miRNA expression levels and to assess the prognostic value of this specific miRNA markers in patients with UCB. Methods To determine candidate miRNAs as prognostic biomarkers for dividing aggressive type of UCB, miRNA expression was profiled in patients' samples with an aggressive phenotype or nonaggressive phenotype using 3D-Gene miRNA labeling kit (Toray, Japan). To create a prognostic index model, we used the panel of 9-miRNA signature based on Cancer Genome Atlas (TCGA) data portal (TCGA Data Portal (https://tcgadata.nci.nih.gov/tcga/tcgaHome2.jsp)). miRNA expression data and corresponding clinical data, including outcome and staging information of 84 UCB patients, were obtained. The Kaplan-Meier and log-rank test were performed to quantify the survival functions in two groups. Results Deregulation of nine miRNAs (hsa-miR-99a-5p, hsa-miR-100-5p, hsa-miR-125b-5p, hsa-miR-145-5p, hsa-miR-4324, hsa-miR-34b-5p, hsa-miR-29c-3p, hsa-miR-135a-3p, and hsa-miR-33b-3p) was determined in UCB patients with aggressive phenotype compared with nonaggressive subject. To validate the prognostic power of the nine-signature miRNAs using the TCGA dataset of bladder cancer, the survival status and tumor miRNA expression of all 84 TCGA UCB patients were ranked according to the prognostic score values. Of nine miRNAs, six were associated with high risk (hsa-miR-99a-5p, hsa-miR-100-5p, hsa-miR-125b-5p, hsa-miR-4324, hsa-miR-34b-5p, and hsa-miR-135a-3p) and three were shown to be protective (hsa-miR-145-5p, hsa-miR-29c-3p, and hsa-miR-33b-3p). Patients with the high-risk miRNA signature exhibited poorer OS than patients expressing the low-risk miRNA profile (HR = 7.05, p < 0.001). Conclusions The miRNA array identified nine dysregulated miRNAs from clinical samples. This panel of nine-miRNA signature provides predictive and prognostic value of patients with UCB.

A novel prognostic index for oral cancer in Fujian province

Objective: To explore the survival factors and construct a prognostic index (PI) for oral squamous cell carcinoma (OSCC). Methods: From January 2004 to June 2016, a total of 634 patients with pathologically confirmed OSCC were recruited in a hospital of Fujian. The clinical and follow-up data of all the patients with pathologically confirmed OSCC were collected to identify the factors influencing the prognosis of OSCC. All the patients were randomly divided into two groups: modeling group (modeling dataset, n=318) and validation group (validation dataset, n=316). Randomization was carried out by using computer-generated random numbers. In the modeling dataset, survival rates were calculated using Kaplan-Meier method and compared using the log-rank test. Cox regression model was used to estimate the hazard ratio (HRs) and 95% confidence intervals (CIs) of prognosis factors. An PI for OSCC patients prognostic prediction model was developed based on β value of each significant variable obtained from the multivariate Cox regression model. Using the tertile analysis, patients were divided into high-risk group, moderate-risk group, and low-risk group according to the PI, the Akaike information criterion (AIC) and Harrell's c-statistic (C index) were used to evaluated the model's predictability. Results: Results from the multivariate Cox regression model indicated that aged ≥55 years (HR=2.22, 95%CI: 1.45-3.39), poor oral hygiene (HR=2.12, 95%CI: 1.27-3.54), first diagnosis of lymph node metastasis (HR=5.78, 95%CI: 3.60-9.27), TNM stage Ⅲ-Ⅳ (stage Ⅰ as reference) (HR=2.43, 95%CI: 1.10-5.37) and poor differentiation (well differentiation as reference) (HR=2.53, 95%CI: 1.60-4.01) were the risk factors influencing the prognosis of OSCC. The PI model had a high predictability in modeling group and validation group (AIC and C index were 1 205.80, 0.700 2 and 1 150.47, 0.737 3). Conclusion: Age, poor oral hygiene, first diagnosis of lymph node metastasis, TNM stage and histological grade were factors associated with the prognosis of OSCC, and the PI model has a certain significance in the clinical treatment of OSCC.

Distinguishable Prognostic Signatures of Left- and Right-Sided Colon Cancer: a Study Based on Sequencing Data

Background/Aims: Left- and right-sided colon cancers are considered to be two different diseases and have altered outcomes. However, specific molecules to predict the prognosis of left- and right-sided colon cancers are currently lacking. Methods: Expression profiling of colon cancer were downloaded from The Cancer Genome Atlas (TCGA). Differentially expressed genes (DEGs) of left- and right-sided colon cancers were compared by DESeq analysis. The prognostic values of DEGs were assessed by univariate and multivariate Cox regression. Prognostic index models of two side colon cancers were conducted with prognostic values genes, respectively. Interaction of DEGs was then analyzed by the protein-protein interaction (PPI). Different biology function of two sides of colon cancer was assessed by Gene Set Enrichment Analysis (GSEA). Results: A total of 167 DEGs were identified between left- and right-sided colon cancers based on TCGA data. Using univariate COX regression analysis, five genes (PHACTR3, CKMT2, CYP2W1, ERFE, HOXC4) were related to overall survival in left-sided, and eight distinguishable genes (EREG, ERFE, HOXC6, SLC22A31, TFF1, GFI1, ZG16, RASL10B) in right-sided. Further, left-sided prognostic model was established with PHACTR3 and CKMT2 (HR=2.040; 95%CI=1.004-4.145; P=0.049). Distinguishable prognostic signature for right-sided colon cancer was established based on EREG, ERFE, GFI1, and RASL10B (HR=3.530; 95%CI: 1.934-6.444; P< 0.001) in multivariate analysis. PPI analysis of 167 DEGs showed that CCL5, GNG4, GNLY, GZMH, DRD2, and FASLG genes were at the core of interaction network. In GSEA function analysis, four pathways, including antigen processing and presentation, natural killer cell mediated cytotoxicity, intestinal immune network for Iga production, and type I diabetes mellitus, were significantly enriched in the DEGs of the right-sided colon cancer. Conclusions: This study constructs a panel of potential prognostic model of left- and right-sided colon cancers, respectively. We also provide molecular biological alterations between left- and right-sided colon cancers.

A prognostic model for stratifying clinical outcomes in chemotherapy-naive metastatic castration-resistant prostate cancer patients treated with abiraterone acetate.

Recently, a prognostic index including six risk factors (RFs) (unfavourable Eastern Cooperative Oncology Group performance status [ECOG PS], presence of liver metastases, short response to luteinizing hormone-releasing hormone [LHRH] agonists/antagonists, low albumin, increased alkaline phosphatase [ALP] and lactate dehydrogenase [LDH]) was developed from the COU-AA-301 trial in post-chemotherapy metastatic castration-resistant prostate cancer (mCRPC) patients treated with abiraterone acetate. Our primary objective was to evaluate this model in a cohort of chemotherapy-naive mCRPC patients receiving abiraterone. We identified 197 chemotherapy-naive patients who received abiraterone at six BC Cancer Agency centres and who had complete information on all six RFs. Study endpoints were prostate-specific antigen (PSA) response rate (RR), time to PSA progression, time on treatment, and overall survival (OS). PSA RR and survival outcomes were compared using Χ2 test and log-rank test. Multivariable Cox proportional hazard analysis was performed to identify RFs independently associated with OS. Patients were classified into good (0-1 RFs), intermediate (2-3 RFs), and poor (4-6 RFs) prognostic groups (33%, 52%, and 15%, respectively). For good-, intermediate-, and poor-risk patients, PSA RR (≥50% decline) was 60% vs. 42% vs. 40% (p=0.05); median time to PSA progression was 7.3 vs. 5.3 vs. 5.0 months (p=0.02); and median OS was 29.4 vs. 13.8 vs. 8.7 months (p<0.0001). The six-factor prognostic index model stratifies clinical outcomes in chemotherapy-naive mCRPC patients treated with abiraterone. Identifying patients at risk of poor outcome is important for informing clinical practice and clinical trial design.

Role of Immune Microenvironmental Factors for Improving the IPI-related Risk Stratification of Aggressive B Cell Lymphoma

ObjectiveTo investigate the risk stratification of aggressive B cell lymphoma using the immune microenvironment and clinical factors. MethodsA total of 127 patients with aggressive B cell lymphoma between 2014 and 2015 were enrolled in this study. CD4, Foxp3, CD8, CD68, CD163, PD-1, and PD-L1 expression levels were evaluated in paraffin-embedded lymphoma tissues to identify their roles in the risk stratification. Eleven factors were identified for further evaluation using analysis of variance, chi-square, and multinomial logistic regression analysis. ResultsSignificant differences in 11 factors (age, Ann Arbor stage, B symptom, ECOG performance status, infiltrating CD8+ T cells, PD-L1 expression, absolute blood monocyte count, serum lactate dehydrogenase, serum iron, serum albumin, and serum β2-microglobulin) were observed among patient groups stratified by at least two risk stratification methods [International Prognostic Index (IPI), revised IPI, and NCCN-IPI models] (P < 0.05). Concordance rates were high (81.4%-100.0%) when these factors were used for the risk stratification. No difference in the risk stratification results was observed with or without the Ann Arbor stage data. ConclusionWe developed a convenient and inexpensive tool for use in risk stratification of aggressive B cell lymphomas, although further studies on the role of immune microenvironmental factors are needed.

Prognostic Index Model for Progression-Free Survival in Chemotherapy-Naïve Metastatic Castration-Resistant Prostate Cancer Treated With Abiraterone Acetate Plus Prednisone.

Radiographic progression-free survival (rPFS) is associated with overall survival (OS) in chemotherapy-naïve metastatic castration-resistant prostate cancer (mCRPC) patients. Using readily assessable baseline clinical and laboratory parameters, we developed a prognostic index model for rPFS in chemotherapy-naïve mCRPC patients without visceral disease who were treated with abiraterone acetate plus prednisone. Data from the abiraterone acetate plus prednisone arm of COU-AA-302 were used. rPFS was defined based on modified Prostate Cancer Working Group 2 criteria. Baseline variables were assessed for association with rPFS through univariate Cox modeling. The lower (LLN) and upper (ULN) limits of laboratory normal were used to dichotomize most laboratory parameters; baseline median was used to dichotomize prostate-specific antigen (PSA). Prognostic factors for rPFS were identified by multivariate Cox modeling. Model accuracy was estimated by the C-index. Presence of lymph node metastasis (hazard ratio [HR]= 1.76, P< .0001), lactate dehydrogenase > ULN (234 IU/L) (HR= 1.71, P=.0001),≥ 10 bone metastases (HR= 1.71, P= .0015), hemoglobin≤ LLN (12.7 g/dL) (HR= 1.47, P= .0030) and PSA > 39.5 ng/mL (HR= 1.42, P= .0078) were associated with poor outcome. Patients were categorized into 3 prognostic groups (good, n= 230; intermediate, n= 152; poor, n= 164) based on number of risk factors. Median rPFS was calculated (27.6, 16.6, and 8.3 months for good, intermediate, and poor, respectively). The C-index was 0.83 (95% confidence interval= 0.73-0.91). The prognostic index model for rPFS reveals differential outcomes based on factors readily available in clinical practice. If validated, this model can be integrated into clinical practice and design of risk-stratified trials.

A prognostic index to stratify survival benefit in patients of solid tumor metastases treated with stereotactic body radiotherapy.

e21578 Background: To investigate the clinical factors related to the prognosis of solid tumor metastases treated with SBRT and to create a scoring system that stratifies survival benefit. Methods: The clinical factors and follow-up data of 404 patients with metastases from solid primary (127 liver metastases, 205 lung metastases and 72 adrenal gland metastases), treated with SBRT from 2005 to 2016, were analyzed retrospectively. The prognostic index (PI) of patients was calculated based on the results of multivariate cox regression model from liver metastases cohort and pretreatment variables included were race, gender, age, KPS, primary tumor and histology, number of metastases, status of disease outside, previous treatment at SBRT site, and interval time from diagnosis to metastases. This model then was used in lung and adrenal gland metastases cohorts. Results: Median follow-upwas 24 months for liver metastases cohort. The median survival time of liver metastases was 21.8 months. Three variables were selected from liver cohort-database training as independent prognostic index for survival benefit: age (HR =1.81, p =0.03), KPS (HR =0.72, p =0.03), number of organs with active disease outside (HR =1.68, p&lt;0.01). Patients were classified into three hazard groups with significant difference. The median survival of group 1(poor) was 8.1 months, group 2 (intermediate) reached 25 months, and group 3 (excellent) reached 39.1 months (p&lt; 0.001). This prognostic index model was also been approved effectively in lung and adrenal gland metastases cohorts, which identified patient subgroups into poor and excellent prognosis. Conclusions: The prognostic index model allows solid tumor metastases patient to stratify survival benefit based on the three predictive factors. Table 1 Survival score and groupings [Table: see text]

Prognostic impact of absolute lymphocyte count/absolute monocyte count ratio and prognostic score in patients with nasal-type, extranodal natural killer/T-cell lymphoma.

Nasal-type, extranodal natural killer/T-cell lymphoma is a heterogeneous disorder with poor prognosis, requiring risk stratification in this population. The combined value of baseline absolute lymphocyte count and absolute monocyte count provided prognostic information in some malignancies. However, the evidence requires validation in extranodal natural killer/T-cell lymphoma. Aiming to investigate the prognostic significance of absolute lymphocyte count/absolute monocyte count ratio and absolute lymphocyte count/absolute monocyte count prognostic score for extranodal natural killer/T-cell lymphoma, a retrospective research was carried out. A total of 264 patients with newly diagnosed extranodal natural killer/T-cell lymphoma were analyzed in this study. The patients' absolute lymphocyte count and absolute monocyte count tested at initial diagnosis were collected. Receiver operating curve analysis showed that the optimal cut-off values for absolute lymphocyte count and absolute monocyte count were 1.0 × 109 and 0.5 × 109L-1, respectively, and for absolute lymphocyte count/absolute monocyte count ratio was 2.85. After a median follow-up of 27 months (range 1-87 months), the 3-year overall survival and progression-free survival was 75.4% and 67.6%, respectively. Patients with absolute lymphocyte count/absolute monocyte count ratio ≥ 2.85 had better 3-year overall survival and progression-free survival than those with absolute lymphocyte count/absolute monocyte count ratio <2.85 (p < 0.001). According to absolute lymphocyte count/absolute monocyte count prognostic score, significant difference has been noticed in 3-year overall survival and progression-free survival (p < 0.001) and high absolute lymphocyte count/absolute monocyte count prognostic score was associated with poorer survival. The International Prognostic Index and Korean Prognostic Index were used for prognosis and showed no significant difference. When adding absolute lymphocyte count/absolute monocyte count ratio and absolute lymphocyte count/absolute monocyte count prognostic score to the International Prognostic Index and Korean Prognostic Index model, additional prognostic information was found. These results suggest that absolute lymphocyte count/absolute monocyte count ratio and absolute lymphocyte count/absolute monocyte count prognostic score might be useful prognostic factors in extranodal natural killer/T-cell lymphoma.

Relevance of prognostic index with β2-microglobulin for patients with diffuse large B-cell lymphoma in the rituximab era.

BackgroundThe International Prognostic Index (IPI) has been a useful tool for predicting the prognosis of aggressive non-Hodgkin lymphoma in the last 20 years. Herein, we aimed to develop a new prognostic model for diffuse large B-cell lymphoma (DLBCL) in the rituximab era.MethodsBetween March 2004 and June 2012, patients with DLBCL treated with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisolone chemotherapy regimen were identified in the database of the Asan Medical Center (AMC) Lymphoma Registry. The primary and secondary endpoints were a new prognostic index for DLBCL and validation of the National Comprehensive Cancer Network-International Prognostic Index in our cohort, respectively.ResultsThe AMC cohort comprised 621 patients. The median follow-up duration was 43.3 months (range, 6.2–122.5 mo). Univariate analysis revealed that age (≤60 vs. >60 yr), lactate dehydrogenase (LDH; within normal vs. increased), Eastern Cooperative Oncology Group performance status (ECOG PS; 0 or 1 vs. ≥2), advanced stage (Ann Arbor stage I/II vs. III/IV), extra-nodal involvement (≤1 vs. >1), B symptoms (no vs. yes), and beta-2 microglobulin (β2MG, ≤2.5 vs. >2.5) can be used to predict overall survival (OS). In multivariate analysis, only age, LDH, ECOG performance status, and β2MG were significantly associated with OS, and we developed a new prognostic model with these 4 factors. The new prognostic model showed better discriminative power compared with the classic IPI.ConclusionOur new prognostic index model for DLBCL in the rituximab era has good discriminative power and is convenient to use.

Prognostic Factors and a New Prognostic Index Model for Children and Adolescents with Hodgkin's Lymphoma Who Underwent Autologous Hematopoietic Stem Cell Transplantation: A Multicenter Study of the Turkish Pediatric Bone Marrow Transplantation Study Group.

Objective:The prognostic factors and a new childhood prognostic index after autologous hematopoietic stem cell transplantation (AHSCT) in patients with relapsed/refractory Hodgkin’s lymphoma (HL) were evaluated.Materials and Methods:The prognostic factors of 61 patients who underwent AHSCT between January 1990 and December 2014 were evaluated. In addition, the Age-Adjusted International Prognostic Index and the Childhood International Prognostic Index (CIPI) were evaluated for their impact on prognosis.Results:The median age of the 61 patients was 14.8 years (minimum-maximum: 5-20 years) at the time of AHSCT. There were single relapses in 28 patients, ≥2 relapses in eight patients, and refractory disease in 25 patients. The chemosensitivity/chemorefractory ratio was 36/25. No pretransplant radiotherapy, no remission at the time of transplantation, posttransplant white blood cell count over 10x103/µL, posttransplant positron emission tomography positivity at day 100, and serum albumin of <2.5 g/dL at diagnosis were correlated with progression-free survival. No remission at the time of transplantation, bone marrow positivity at diagnosis, and relapse after AHSCT were significant parameters for overall survival.Conclusion:The major factors affecting the progression-free and overall survival were clearly demonstrated. A CIPI that uses a lactate dehydrogenase level of 500 IU/L worked well for estimating the prognosis. We recommend AHSCT at first complete remission for relapsed cases, and it should also be taken into consideration for patients with high prognostic scores at diagnosis.

A prognostic index model to predict the clinical outcomes for patients with advanced pancreatic cancer receiving systemic chemotherapy

A prognostic index model to predict the clinical outcomes for patients with advanced pancreatic cancer receiving systemic chemotherapy

Clinical model to predict progression-free survival in EGFR-mutant lung adenocarcinoma patients treated with first-generation EGFR-TKIs

Background: Albeit epidermal growth factor receptor (EGFR) mutation status might be superior to other clinical and pathological factors for predicting response to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs), the efficacy might differ a lot in patients with the same EGFR sensitive mutations. Thus, exploring factors associated with EGFR-TKIs efficacy other than EGFR mutation status is vital, especially in patients with EGFR-activating mutations. Methods: The present study retrospectively collected clinical and pathological data on a total of 128 patients with EGFR-activating lung adenocarcinoma who received first-generation EGFR-TKIs (including gefitinib, erlotinib or icotinib). Kaplan-Meier and Cox regression methods were applied to identify independent factors associated with progression-free survival (PFS) and to generate a prognostic index (PI) model. Results: The median PFS of the 128 patients was 14.9 months (95% CI, 13.2–16.5 months). A non-smoking history [hazard ratio (HR) =2.896; 95% CI, 1.501–5.558; P=0.002] and first-line EGFR-TKIs treatment (HR, 1.544; 95% CI, 0.999–2.386; P=0.05) were found to be independent predictive factors of a longer PFS with EGFR-TKIs therapy. Predictive model can be established as PI =1.063 × Smoking + 0.434 × Timing according to the results of Cox regression. Further analysis using the PI model indicated that there are differences of three groups in PFS: non-smoking and first-line therapy, non-smoking and non-first-line therapy, smoking regardless of treatment timing. Conclusions: The findings of the present study suggest that a non-smoking history and a first-line EGFR-TKIs treatment timing are independent predictors of a longer PFS in EGFR-mutant lung adenocarcinoma patients treated with first-generation EGFR-TKIs. PFS is longer for those who are never smokers and receive first-line EGFR-TKIs, compared with other groups.

183 Cutaneous lymphoma international consortium (CLIC): Uniting worldwide experts to develop and validate a prognostic index model

183 Cutaneous lymphoma international consortium (CLIC): Uniting worldwide experts to develop and validate a prognostic index model

A prognostic index model for predicting overall survival in patients with metastatic castration-resistant prostate cancer treated with abiraterone acetate after docetaxel

Few prognostic models for overall survival (OS) are available for patients with metastatic castration-resistant prostate cancer (mCRPC) treated with recently approved agents. We developed a prognostic index model using readily available clinical and laboratory factors from a phase III trial of abiraterone acetate (hereafter abiraterone) in combination with prednisone in post-docetaxel mCRPC. Baseline data were available from 762 patients treated with abiraterone-prednisone. Factors were assessed for association with OS through a univariate Cox model and used in a multivariate Cox model with a stepwise procedure to identify those of significance. Data were validated using an independent, external, population-based cohort. Six risk factors individually associated with poor prognosis were included in the final model: lactate dehydrogenase > upper limit of normal (ULN) [hazard ratio (HR) = 2.31], Eastern Cooperative Oncology Group performance status of 2 (HR = 2.19), presence of liver metastases (HR = 2.00), albumin ≤4 g/dl (HR = 1.54), alkaline phosphatase > ULN (HR = 1.38) and time from start of initial androgen-deprivation therapy to start of treatment ≤36 months (HR = 1.30). Patients were categorized into good (n = 369, 46%), intermediate (n = 321, 40%) and poor (n = 107, 13%) prognosis groups based on the number of risk factors and relative HRs. The C-index was 0.70 ± 0.014. The model was validated by the external dataset (n = 286). This analysis identified six factors used to model survival in mCRPC and categorized patients into three distinct risk groups. Prognostic stratification with this model could assist clinical practice decisions for follow-up and monitoring, and may aid in clinical trial design. NCT00638690.

Plasma Biomarker Enrichment of Clinical Prognostic Indices in Malignant Pleural Mesothelioma

ObjectivesPrognostic models for malignant pleural mesothelioma (MPM) are needed to prevent potentially futile outcomes. We combined MPM plasma biomarkers with validated clinical prognostic indices to determine whether stratification of risk for death in 194 patients with MPM improved. MethodsIndividuals were recruited from three different centers: a discovery cohort (83 patients with MPM) created by combining patients from two U.S. centers and a separate, independent cohort from Canada (111 patients with MPM). Univariable and multivariable analyses were performed on the initial discovery and independent cohorts separately. In the multivariable analyses, prognostic factors were adjusted for the European Organisation for Research and Treatment of Cancer (EORTC) prognostic index (PI) of mesothelioma. The prognostic significance of adding plasma biomarker data to the PI was determined by using the likelihood ratio test, comparing models with and without the addition of biomarker to the clinical PI. The predictive ability of the biomarker was then assessed formally using Harrell’s C-index by applying the fitted model variables of the discovery cohort to the second, independent cohort, including and not including the biomarker with the PI. ResultsHigher levels of osteopontin and mesothelin were individually associated with worse prognosis after adjusting for the PI. In the independent cohort, incorporating either plasma osteopontin or mesothelin into the baseline predictive PI model substantively and statistically significantly improved Harrell’s C-statistic. In the final prognostic model, log-osteopontin, EORTC clinical prognostic index, and hemoglobin remained as independently significant predictors and the entire prognostic model improved the optimism-corrected Harrell’s C-index significantly, from 0.718 (0.67–0.77) to 0.801 (0.77–0.84). ConclusionsThese data suggest a possible role for preoperative plasma biomarkers to improve the prognostic capability of the EORTC PI of MPM.

Development and validation of a prognostic index for allograft outcome in kidney recipients with transplant glomerulopathy

We studied 92 patients with transplant glomerulopathy to develop a prognostic index based on the risk factors for allograft failure within five years of diagnosis (Development cohort). During 60 months (median) follow up, 64 patients developed allograft failure. A chronic-inflammation score generated by combining Banff ci, ct and ti scores, serum creatinine and proteinuria at biopsy, were independent risk factors for allograft failure. Based on the Cox model, we developed a prognostic index and classified patients into risk groups. Compared to the low risk group (median allograft survival over 60 months from diagnosis), patients in the medium risk group had a hazard ratio of 2.83 (median survival 25 months), while those in the high risk group had a hazard ratio of 5.96 (median survival 3.7 months). We next evaluated the performance of the prognostic index in an independent external cohort of 47 patients with transplant glomerulopathy (Validation cohort). The hazard ratios were 2.18 (median survival 19 months) and 16.27 (median survival 1.6 months), respectively, for patients in the medium and high risk groups, compared to the low risk group (median survival 47 months). Our prognostic index model did well in measures of discrimination and calibration. Thus, risk stratification of transplant glomerulopathy based on our prognostic index may provide informative insight for both the patient and physician regarding prognosis and treatment.

The Practicability of a Novel Prognostic Index (PI) Model and Comparison with Nottingham Prognostic Index (NPI) in Stage I-III Breast Cancer Patients Undergoing Surgical Treatment.

BackgroundPrevious studies have indicated the prognostic value of various laboratory parameters in cancer patients. This study was to establish a prognostic index (PI) model for breast cancer patients based on the potential prognostic factors.MethodsA retrospective study of 1661 breast cancer patients who underwent surgical treatment between January 2002 and December 2008 at Sun Yat-sen University Cancer Center was conducted. Multivariate analysis (Cox regression model) was performed to determine the independent prognostic factors and a prognostic index (PI) model was devised based on these factors. Survival analyses were used to estimate the prognostic value of PI, and the discriminatory ability of PI was compared with Nottingham Prognostic Index (NPI) by evaluating the area under the receiver operating characteristics curves (AUC).ResultsThe mean survival time of all participants was 123.6 months. The preoperative globulin >30.0g/L, triglyceride >1.10mmol/L and fibrinogen >2.83g/L were identified as risk factors for shorter cancer-specific survival. The novel prognostic index model was established and enrolled patients were classified as low- (1168 patients, 70.3%), moderate- (410 patients, 24.7%) and high-risk groups (83 patients, 5.0%), respectively. Compared with the low-risk group, higher risks of poor clinical outcome were indicated in the moderate-risk group [Hazard ratio (HR): 1.513, 95% confidence interval (CI): 1.169–1.959, p = 0.002] and high-risk group (HR: 2.481, 95%CI: 1.653–3.724, p< 0.001).ConclusionsThe prognostic index based on three laboratory parameters was a novel and practicable prognostic tool. It may serve as complement to help predict postoperative survival in breast cancer patients.

ISS1-3-2 - Prognostic index model for overall survival in advanced unresectable pancreatic cancer from GEST study

ISS1-3-2 - Prognostic index model for overall survival in advanced unresectable pancreatic cancer from GEST study

Is Abdominal Fat Distribution Measured by Axial CT Imaging an Indicator of Complications and Mortality in Acute Pancreatitis?

BackgroundObesity is an important risk-stratifying co-morbidity for many pathological conditions. Controversy exists about its influence in outcomes after acute pancreatitis (AP). This study assessed abdominal fat distribution (subcutaneous, retroperitoneal and intra-abdominal) measured using computer tomography (CT) images and related it to outcomes in patients with AP. MethodsThe case notes of patients admitted with AP were identified from computerised records from 2008 to the 2013. Image analysis software was used to assess the individual abdominal fat distributions from CT images. ResultsA total of 79 patients were included. There was no relationship between fat distribution and either severity of, or mortality from, AP. Fat distribution was not found to be an independent risk factor on multivariate analysis. There was, however, a positive correlation between retroperitoneal and intra-abdominal fat with APACHE II scores, Ranson and Glasgow score and Multiple Organ Dysfunction score (MODS) on various days following admission (r = 0.421, p = 0.0008; r = 0.469, p < 0.0001; r = 0.398, p = 0.007; r = 0.336, p = 0.011, respectively). On multiple logistical regression analysis, the only variables associated with mortality were Balthazar Severity Index, MODS and EWS with a p value of <0.0001, 0.0019 and 0.0481, respectively. ConclusionsObese patients have worse predicted outcomes as measured by the EWS, MODS and Ranson scores. Abdominal fat distribution, however, was not shown to be directly related to AP severity or mortality. The addition of fat parameters may be of use in prognostic CT severity index models, but from this data, it does not appear to be an independent risk factor of adverse outcome.