A new evidence-based risk stratification system for cutaneous squamous cell carcinoma into low, intermediate, and high risk groups with implications for management

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 >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.

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Development of a Prognostic Nomogram and Risk Stratification System for Upper Thoracic Esophageal Squamous Cell Carcinoma

10.21203/rs.3.rs-958976/v1 ◽

2021 ◽

Author(s):

Yu Lin ◽

Binglin Zheng ◽

Junqiang Chen ◽

Qiuyuan Huang ◽

Yuling Ye ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

Prognostic Factors ◽

Esophageal Squamous Cell Carcinoma ◽

Risk Stratification ◽

Risk Groups ◽

Training Cohort ◽

Stratification System ◽

Ajcc Staging ◽

Upper Thoracic ◽

Risk Stratification System

Abstract BackgroundEffective tools evaluating the prognosis for patients with upper thoracic esophageal carcinoma is lacking. We aimed to develop a nomogram model to predict overall survival (OS) and construct a risk stratification system of upper thoracic esophageal squamous cell carcinoma (ESCC) patients.MethodsNewly diagnosed 568 patients with upper thoracic ESCC at Fujian Medical University Cancer Hospital between February 2004 and December 2016 was taken as a training cohort, and additional 155 patients with upper ESCC from Sichuan Cancer Hospital Institute between January 2011 and December 2013 were used as a validation cohort. A nomogram was established using Cox proportional hazard regression to identify prognostic factors for OS. The predictive power of nomogram model was evaluated by using 4 indices: concordance statistics (C-index), time-dependent ROC (ROCt) curve, net reclassification index (NRI) and integrated discrimination improvement (IDI). Decision curve analysis (DCA) was used to evaluate clinical usefulness of prediction models. Patients were categorized into three risk groups by X-tile software on the survival scores of the training cohort.ResultsMultivariate analysis revealed that gender, clinical T stage, clinical N stage and primary gross tumor volume (GTVp) were independent prognostic factors for OS in the training cohort. The nomogram based on these factors showed favorable prognostic efficacy in the both training and validation cohorts, with C-index of 0.622, 0.713, and AUC value of 0.709, 0.739, respectively, which appeared superior to those of the American Joint Committee on Cancer (AJCC) staging system. In addition, NRI and IDI of the nomogram presented better discrimination ability to predict survival than those of AJCC staging. Furthermore, DCA curve of the nomogram exhibited greater clinical performance than that of AJCC staging. Finally, the nomogram fairly distinguished the OS rates among low, moderate, and high risk groups, whereas the OS curves of clinical stage could not be well separated among clinical AJCC stage. ConclusionsWe built an effective nomogram model for predict OS of upper thoracic ESCC, which may improve clinicians’ abilities to predict individualized survival and facilitate to further stratify the management of patients at risk.

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