The multi-institutional myeloma group clinico-genomic risk stratification system: A blinded validation

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 8521-8521
Author(s):  
S. A. Tuchman ◽  
W. Chng ◽  
A. Anguiano ◽  
W. T. Barry ◽  
F. Zhan ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Stratification ◽  
Validation Cohort ◽  
Staging System ◽  
Discovery Cohort ◽  
Oncogenic Pathway ◽  
Pathway Activation ◽  
Stratification System ◽  
Genomic Risk ◽  
Risk Stratification System

8521 Background: Several clinical and molecular prognostic factors (e.g, International Staging System [ISS] stage, plasma cell labeling index, genomic models) exist for multiple myeloma (MM). We hypothesized that exploiting gene signatures representative of oncogenic pathway deregulation (i.e., Ras, Myc, etc.), would improve MM prognostication and also aid with the identification of novel therapeutic targets. Methods: Using a discovery cohort (n=47) of patients with MM and corresponding gene expression data, we built upon current molecular risk-stratification and devised a Bayesian genomic (“metagene”) model for prognosis. We validated that model in an independent patient cohort (n=207). Finally, we incorporated ISS staging and clinical variables to construct a combined Clinico-Genomic Risk Stratification System. We further validated the combined model in a separate cohort (n=72), in a blinded manner. Results: Using gene signatures predictive of oncogenic pathway activation in the discovery cohort, we identified specific patterns (metagenes) of signaling pathway activation with prognostic relevance. In an independent validation cohort, this metagene-based model accurately predicted event free survival (EFS) independently of ISS (multivariate hazard ratio [HR] 3.4 for ISS stage, and 5.4 for the metagene model, p=0.002). Using multivariate risk modeling, we incorporated ISS staging and the metagene model into a Clinico-Genomic System and successfully stratified the validation cohort into three groups (low, intermediate, and high risk) with markedly different EFS (HR 4.2 for intermediate risk and 14.0 for high risk vs. the low risk cohort, p<0.0001). In an additional blinded validation, the Clinico-Genomic System again accurately predicted median overall survival (68.7 [low risk] vs 24.7 [intermediate risk] vs 18.7 months [high risk], p<0.0001); more accurately than either ISS or other reported genomic models. Conclusions: A combined Clinico-Genomic Risk Stratification System, building on patterns of oncogenic pathway activation and ISS staging system, improves upon current prognostic models in MM and identifies novel pathway targets for future therapeutic consideration. No significant financial relationships to disclose.

The Influence of Age on Disease Outcome in 2015 ATA High Risk Differentiated Thyroid Cancer Patients

2021 ◽  
Author(s):  
Evert F.s. van Velsen ◽  
Robin P. Peeters ◽  
Merel T. Stegenga ◽  
F.j. van Kemenade ◽  
Tessa M. van Ginhoven ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
High Risk ◽  
Risk Stratification ◽  
Differentiated Thyroid Cancer ◽  
Response To Therapy ◽  
Disease Outcome ◽  
High Risk Patients ◽  
Risk Patients ◽  
Stratification System ◽  
Risk Stratification System

Objective Recent research suggests that the addition of age improves the 2015 American Thyroid Association (ATA) Risk Stratification System for differentiated thyroid cancer (DTC). The aim of our study was to investigate the influence of age on disease outcome in ATA High Risk patients with a focus on differences between patients with papillary (PTC) and follicular thyroid cancer (FTC). Methods We retrospectively studied adult patients with High Risk DTC from a Dutch university hospital. Logistic regression and Cox proportional hazards models were used to estimate the effects of age (at diagnosis) and several age cutoffs (per five years increment between 20 and 80 years) on (i) response to therapy, (ii) developing no evidence of disease (NED), (iii) recurrence, and (iv) disease specific mortality (DSM). Results We included 236 ATA High Risk patients (32% FTC) with a median follow-up of 6 years. Age, either continuously or dichotomously, had a significant influence on having an excellent response after initial therapy, developing NED, recurrence, and DSM for PTC and FTC. For FTC, an age cutoff of 65 or 70 years showed the best statistical model performance, while this was 50 or 60 years for PTC. Conclusions In a population of patients with High Risk DTC, older age has a significant negative influence on disease outcomes. Slightly different optimal age cutoffs were identified for the different outcomes, and these cutoffs differed between PTC and FTC. Therefore, the ATA Risk Stratification System may further improve should age be incorporated as an additional risk factor.

scholarly journals Development and validation of a prognostic nomogram for predicting overall survival in patients with primary bladder sarcoma: a SEER-based retrospective study

BMC Urology ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Shijie Li ◽  
Xuefeng Liu ◽  
Xiaonan Chen
Keyword(s):  
Overall Survival ◽  
Risk Stratification ◽  
Cox Regression ◽  
Staging System ◽  
Tnm Staging ◽  
Calibration Curves ◽  
Tnm Staging System ◽  
Primary Bladder ◽  
Stratification System ◽  
Risk Stratification System

Abstract Background Primary bladder sarcoma (PBS) is a rare malignant tumor of the bladder with a poor prognosis, and its disease course is inadequately understood. Therefore, our study aimed to establish a prognostic model to determine individualized prognosis of patients with PBS. Patients and Methods Data of 866 patients with PBS, registered from 1973 to 2015, were extracted from the surveillance, epidemiology, and end result (SEER) database. The patients included were randomly split into a training (n = 608) and a validation set (n = 258). Univariate and multivariate Cox regression analyses were employed to identify the important independent prognostic factors. A nomogram was then established to predict overall survival (OS). Using calibration curves, receiver operating characteristic curves, concordance index (C-index), decision curve analysis (DCA), net reclassification improvement (NRI) and integrated discrimination improvement (IDI), the performance of the nomogram was internally validated. We compared the nomogram with the TNM staging system. The application of the risk stratification system was tested using Kaplan–Meier survival analysis. Results Age at diagnosis, T-stage, N-stage, M-stage, and tumor size were identified as independent predictors of OS. C-index of the training cohort were 0.675, 0.670, 0.671 for 1-, 3- and 5-year OS, respectively. And that in the validation cohort were 0.701, 0.684, 0.679, respectively. Calibration curves also showed great prediction accuracy. In comparison with TNM staging system, improved net benefits in DCA, evaluated NRI and IDI were obtained. The risk stratification system can significantly distinguish the patients with different survival risk. Conclusion A prognostic nomogram was developed and validated in the present study to predict the prognosis of the PBS patients. It may assist clinicians in evaluating the risk factors of patients and formulating an optimal individualized treatment strategy.

scholarly journals Risk Stratification for Diffuse Large B-Cell Lymphoma by Integrating Interim Evaluation and International Prognostic Index: A Multicenter Retrospective Study

2021 ◽  
Vol 11 ◽  
Author(s):  
Xue Shi ◽  
Xiaoqian Liu ◽  
Xiaomei Li ◽  
Yahan Li ◽  
Dongyue Lu ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Stratification ◽  
Risk Group ◽  
International Prognostic Index ◽  
Prognostic Index ◽  
B Cell Lymphoma ◽  
Risk Groups ◽  
High Risk Group ◽  
Stratification System ◽  
Risk Stratification System

The baseline International Prognostic Index (IPI) is not sufficient for the initial risk stratification of patients with diffuse large B-cell lymphoma (DLBCL) treated with R‐CHOP (rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone). The aims of this study were to evaluate the prognostic relevance of early risk stratification in DLBCL and develop a new stratification system that combines an interim evaluation and IPI. This multicenter retrospective study enrolled 314 newly diagnosed DLBCL patients with baseline and interim evaluations. All patients were treated with R-CHOP or R-CHOP-like regimens as the first-line therapy. Survival differences were evaluated for different risk stratification systems including the IPI, interim evaluation, and the combined system. When stratified by IPI, the high-intermediate and high-risk groups presented overlapping survival curves with no significant differences, and the high-risk group still had &gt;50% of 3-year overall survival (OS). The interim evaluation can also stratify patients into three groups, as 3-year OS and progression-free survival (PFS) rates in patients with stable disease (SD) and progressive disease (PD) were not significantly different. The SD and PD patients had significantly lower 3-year OS and PFS rates than complete remission and partial response patients, but the percentage of these patients was only ~10%. The IPI and interim evaluation combined risk stratification system separated the patients into low-, intermediate-, high-, and very high-risk groups. The 3-year OS rates were 96.4%, 86.7%, 46.4%, and 40%, while the 3-year PFS rates were 87.1%, 71.5%, 42.5%, and 7.2%. The OS comparison between the high-risk group and very high-risk group was marginally significant, and OS and PFS comparisons between any other two groups were significantly different. This combined risk stratification system could be a useful tool for the prognostic prediction of DLBCL patients.

scholarly journals Prognostic analysis and beneficiary identification of adjuvant external beam radiotherapy for stage pT4b sigmoid colon cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yaobin Lin ◽  
Lei Wang ◽  
Lingdong Shao ◽  
Xueqing Zhang ◽  
Huaqin Lin ◽  
...  
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Risk Stratification ◽  
Sigmoid Colon ◽  
External Beam Radiotherapy ◽  
Sigmoid Colon Cancer ◽  
High Risk Patients ◽  
Risk Patients ◽  
Stratification System ◽  
Risk Stratification System

AbstractThe clinical efficacy of adjuvant radiotherapy in sigmoid colon cancer remains questioned. To evaluate the clinical efficacy of adjuvant external beam radiotherapy (EBRT) for patients with pathologic stage T4b sigmoid colon cancer. Patients with stage pT4b sigmoid colon cancer receiving adjuvant EBRT or not followed by surgery between 2004 and 2016 were extracted from the Surveillance, Epidemiology, and End Results database. Analysis of overall survival (OS) was performed using Kaplan–Meier curves and prognostic factors were identified using Cox proportional hazards regression models with 95% confidence intervals within the entire cohort. A risk-stratification system was then developed based on the β regression coefficient. Among 2073 patients, 284 (13.7%) underwent adjuvant EBRT. The median OS in the group receiving adjuvant EBRT was significantly longer than that in the non-radiotherapy group (p < 0.001). Age, serum carcinoembryonic antigen (CEA) level, perineural invasion, lymph node dissection (LND) number, and adjuvant EBRT were independent factors associated with OS. A risk‐stratification system was generated, which showed that low‐risk patients had a higher 5-year survival rate than high-risk patients (75.6% vs. 42.3%, p < 0.001). Adjuvant EBRT significantly prolonged the 5-year survival rate of high-risk patients (62.6% vs. 38.3%, p = 0.009) but showed no survival benefit among low‐risk patients (87.7% vs. 73.2%, p = 0.100). Our risk‐stratification model comprising age, serum CEA, perineural invasion, and LND number predicted the outcomes of patients with stage pT4b sigmoid colon cancer based on which subgroup of high-risk patients should receive adjuvant EBRT.

scholarly journals A Novel Validated Recurrence Stratification System Based on 18F-FDG PET/CT Radiomics to Guide Surveillance After Resection of Pancreatic Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Miaoyan Wei ◽  
Bingxin Gu ◽  
Shaoli Song ◽  
Bo Zhang ◽  
Wei Wang ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
High Risk ◽  
Risk Stratification ◽  
Cancer Patients ◽  
Fdg Pet ◽  
Resectable Pancreatic Cancer ◽  
Pet Ct ◽  
Stratification System ◽  
Fdg Pet Ct ◽  
Risk Stratification System

objectiveDespite the heterogeneous biology of pancreatic cancer, similar surveillance schemas have been used. Identifying the high recurrence risk population and conducting prompt intervention may improve prognosis and prolong overall survival.MethodsOne hundred fifty-six resectable pancreatic cancer patients who had undergone 18F-FDG PET/CT from January 2013 to December 2018 were retrospectively reviewed. The patients were categorized into a training cohort (n = 109) and a validation cohort (n = 47). LIFEx software was used to extract radiomic features from PET/CT. The risk stratification system was based on predictive factors for recurrence, and the index of prediction accuracy was used to reflect both the discrimination and calibration.ResultsOverall, seven risk factors comprising the rad-score and clinical variables that were significantly correlated with relapse were incorporated into the final risk stratification system. The 1-year recurrence-free survival differed significantly among the low-, intermediate-, and high-risk groups (85.5, 24.0, and 9.1%, respectively; p &lt; 0.0001). The C-index of the risk stratification system in the development cohort was 0.890 (95% CI, 0.835–0.945).ConclusionThe 18F-FDG PET/CT-based radiomic features and clinicopathological factors demonstrated good performance in predicting recurrence after pancreatectomy in pancreatic cancer patients, providing a strong recommendation for an adequate adjuvant therapy course in all patients. The high-risk recurrence population should proceed with closer follow-up in a clinical setting.

scholarly journals A Nomogram for Predicting Survival in Patients With Breast Cancer Liver Metastasis: A Population-Based Study

2021 ◽  
Vol 11 ◽  
Author(s):  
Yu Xiong ◽  
Xia Shi ◽  
Qi Hu ◽  
Xingwei Wu ◽  
Enwu Long ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
Liver Metastasis ◽  
Risk Stratification ◽  
Staging System ◽  
Tnm Staging ◽  
Tnm Staging System ◽  
Stratification System ◽  
Breast Cancer Liver Metastasis ◽  
Risk Stratification System

ObjectiveThe prognosis of patients with breast cancer liver metastasis (BCLM) was poor. We aimed at constructing a nomogram to predict overall survival (OS) for BCLM patients using the SEER (Surveillance Epidemiology and End Results) database, thus choosing an optimized therapeutic regimen to treat.MethodsWe identified 1173 patients with BCLM from the SEER database and randomly divided them into training (n=824) and testing (n=349) cohorts. The Cox proportional hazards model was applied to identify independent prognostic factors for BCLM, based on which a nomogram was constructed to predict 1-, 2-, and 3-year OS. Its discrimination and calibration were evaluated by the Concordance index (C-index) and calibration plots, while the accuracy and benefits were assessed by comparing it to AJCC-TNM staging system using the decision curve analysis (DCA). Kaplan-Meier survival analyses were applied to test the clinical utility of the risk stratification system.ResultsGrade, marital status, surgery, radiation therapy, chemotherapy, CS tumor size, tumor subtypes, bone metastatic, brain metastatic, and lung metastatic were identified to be independent prognostic factors of OS. In comparison with the AJCC-TNM staging system, an improved C-index was obtained (training group: 0.701 vs. 0.557, validation group: 0.634 vs. 0.557). The calibration curves were consistent between nomogram-predicted survival probability and actual survival probability. Additionally, the DCA curves yielded larger net benefits than the AJCC-TNM staging system. Finally, the risk stratification system can significantly distinguish the ones with different survival risk based on the different molecular subtypes.ConclusionWe have successfully built an effective nomogram and risk stratification system to predict OS in BCLM patients, which can assist clinicians in choosing the appropriate treatment strategies for individual BCLM patients.

scholarly journals Clinical Value of Lymph Node Ratio Integration with the 8th Edition of the UICC TNM Classification and 2015 ATA Risk Stratification Systems for Recurrence Prediction in Papillary Thyroid Cancer

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Jandee Lee ◽  
Seul Gi Lee ◽  
Kwangsoon Kim ◽  
Seung Hyuk Yim ◽  
Haengrang Ryu ◽  
...  
Keyword(s):  
Risk Stratification ◽  
Lymph Node Ratio ◽  
Staging System ◽  
Tnm Staging ◽  
Papillary Thyroid ◽  
Clinical Value ◽  
Tnm Staging System ◽  
Node Ratio ◽  
Stratification System ◽  
Risk Stratification System

Abstract Recently, the 2015 American Thyroid Association (ATA) risk stratification and the 8th edition of the American Joint Committee on Cancer/Union for International Cancer Control (AJCC/UICC) TNM staging system were released. This study was conducted to assess the clinical value of the lymph node ratio (LNR) as a predictor of recurrence when integrated with these newly released stratification systems, and to compare the predictive accuracy of the modified systems with that of the newly released systems. The optimal LNR threshold value for predicting papillary thyroid cancer (PTC) recurrence was 0.17857 using the Contal and O’Quigley method. The 8th edition of the AJCC/UICC TNM staging system with the LNR and the 2015 ATA risk stratification system with the LNR were significant predictors of recurrence. Furthermore, calculation of the proportion of variance explained (PVE), the Akaike information criterion (AIC), Harrell’s c index, and the incremental area under the curve (iAUC) revealed that the 8th edition of the TNM staging system with the LNR, and the 2015 ATA risk stratification system with the LNR, showed the best predictive performance. Integration of the LNR with the TNM staging and the ATA risk stratification systems should improve prediction of recurrence in patients with PTC.

scholarly journals OR21-07 The 2015 American Thyroid Association Risk Stratification System Is a Predictor of Persistent Disease in Real-World Clinical Practice

2020 ◽  
Vol 4 (Supplement_1) ◽  
Author(s):  
Giorgio Grani ◽  
Marco Alfo’ ◽  
Valeria Ramundo ◽  
Efisio Puxeddu ◽  
Emanuela Arvat ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
High Risk ◽  
Risk Stratification ◽  
Real World ◽  
Initial Treatment ◽  
Response To Treatment ◽  
American Thyroid Association ◽  
Structural Disease ◽  
Stratification System ◽  
Risk Stratification System

Abstract Background. Management and follow-up of differentiated thyroid cancer (DTC) are guided by the likelihood of disease persistence or recurrence. The American Thyroid Association (ATA) practice guidelines provide a risk-estimation system based on data mainly derived by retrospective, single-center, and small cohorts. Aim. To validate the ATA risk-stratification system in predicting persistent structural disease. Methods. We analyzed data from the Italian Thyroid Cancer Observatory’s observational, web-based database, which prospectively enrolls newly diagnosed DTC patients in 40 Italian centers. For the present study we selected consecutive cases satisfying the inclusion criteria: 1) histological diagnosis of DTC, including papillary, follicular, and poorly differentiated tumors; 2) registration in the ITCO database between January 1, 2013 and April 23, 2019; 3) clinical evaluation between 6 and 18 month after primary treatment, including enough data to estimate the response to the initial treatment. Exclusion criteria were: histological diagnosis of NIFTP, medullary, or anaplastic thyroid cancer. The response to the initial treatment was categorized as excellent, biochemical incomplete, structural incomplete, or indeterminate based on imaging findings (neck ultrasound and other imaging studies, if performed), basal or stimulated serum thyroglobulin levels, and anti-Tg antibody levels. To model the response to treatment, we used a cumulative link model; given the hierarchical structure of the data, with patients nested within centers, we used a mixed-effect model, with a center-specific intercept summarizing unobserved center-specific characteristics. Results. Complete data about initial treatment and response to treatment after 6-18 months since initial treatment was available for 2071 patients. According to the ATA system, 1109 patients (53.6%) were classified as low-risk, 796 (38.4%) as intermediate, and 166 (8.0%) as high-risk. Excellent response was recorded in 1576 (76.1%) patients, indeterminate in 376 (18.2%), biochemical incomplete in 33 (1.6%), and structural incomplete in 86 (4.2%).The ATA risk stratification system is a significant predictor of response to treatment after 6-18 months: classification as intermediate- and high-risk increased the likelihood of a response worse than excellent (OR 1.68 [95% confidence intervals, CI 1.34-2.10] and 3.23 [95% CI 2.23-4.67], respectively), and a persistent structural disease (OR 4.67 [95% CI 2.59-8.43] and 16.48 [95% CI 7.87-34.5], respectively. In both analyses, the effect of the center (taking into account center-specific features) was negligible and not statistically significant. Conclusion. The 2015 ATA risk stratification system is a reliable predictor of short-term outcomes in patients with DTC, also if applied in a real-world setting consisting of several different clinical sites.

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