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Development and external validation of nomograms to predict the risk of skeletal metastasis at the time of diagnosis and skeletal metastasis-free survival in nasopharyngeal carcinoma.

ABSTRACT: BACKGROUND:The skeletal system is the most common site of distant metastasis in nasopharyngeal carcinoma (NPC); various prognostic factors have been reported for skeletal metastasis, though most studies have focused on a single factor. We aimed to establish nomograms to effectively predict skeletal metastasis at initial diagnosis (SMAD) and skeletal metastasis-free survival (SMFS) in NPC. METHODS:A total of 2685 patients with NPC who received bone scintigraphy (BS) and/or 18F-deoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) and 2496 patients without skeletal metastasis were retrospectively assessed to develop individual nomograms for SMAD and SMFS. The models were validated externally using separate cohorts of 1329 and 1231 patients treated at two other institutions. RESULTS:Five independent prognostic factors were included in each nomogram. The SMAD nomogram had a significantly higher c-index than the TNM staging system (training cohort, P = 0.005; validation cohort, P < 0.001). The SMFS nomogram had significantly higher c-index values in the training and validation sets than the TNM staging system (P < 0.001 and P = 0.005, respectively). Three proposed risk stratification groups were created using the nomograms, and enabled significant discrimination of SMFS for each risk group. CONCLUSION:The prognostic nomograms established in this study enable accurate stratification of distinct risk groups for skeletal metastasis, which may improve counseling and facilitate individualized management of patients with NPC.

SUBMITTER: Yang L

PROVIDER: S-EPMC5586019 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Development and external validation of nomograms to predict the risk of skeletal metastasis at the time of diagnosis and skeletal metastasis-free survival in nasopharyngeal carcinoma.

Yang Lin L Xia Liangping L Wang Yan Y He Shasha S Chen Haiyang H Liang Shaobo S Peng Peijian P Hong Shaodong S Chen Yong Y

BMC cancer 20170906 1

<h4>Background</h4>The skeletal system is the most common site of distant metastasis in nasopharyngeal carcinoma (NPC); various prognostic factors have been reported for skeletal metastasis, though most studies have focused on a single factor. We aimed to establish nomograms to effectively predict skeletal metastasis at initial diagnosis (SMAD) and skeletal metastasis-free survival (SMFS) in NPC.<h4>Methods</h4>A total of 2685 patients with NPC who received bone scintigraphy (BS) and/or 18F-deox ...[more]

PMID: 28874126

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Project description:ImportanceAdrenocortical carcinoma (ACC) is a rare but aggressive endocrine tumor, and the prognostic factors associated with long-term outcomes after surgical resection remain poorly defined.ObjectivesTo define clinicopathological variables associated with recurrence-free survival (RFS) and overall survival (OS) after curative surgical resection of ACC and to propose nomograms for individual risk prediction.Design, setting, and participantsNomograms to predict RFS and OS after surgical resection of ACC were proposed using a multi-institutional cohort of patients who underwent curative-intent surgery for ACC at 13 major institutions in the United States between March 17, 1994, and December 22, 2014. The dates of our study analysis were April 15, 2015, to May 12, 2015.Main outcomes and measuresThe discriminative ability and calibration of the nomograms to predict RFS and OS were tested using C statistics, calibration plots, and Kaplan-Meier curves.ResultsIn total, 148 patients who underwent surgery for ACC were included in the study. The median patient age was 53 years, and 65.5% (97 of 148) of the patients were female. One-third of the patients (35.1% [52 of 148]) had a functional tumor, and the median tumor size was 11.2 cm. Most patients (77.7% [115 of 148]) underwent R0 resection, and 8.8% (13 of 148) of the patients had N1 disease. Using backward stepwise selection of clinically important variables with the Akaike information criterion, the following variables were incorporated in the prediction of RFS: tumor size of at least 12 cm (hazard ratio [HR], 3.00; 95% CI, 1.63-5.70; P < .001), positive nodal status (HR, 4.78; 95% CI, 1.47-15.50; P = .01), stage III/IV (HR, 1.80; 95% CI, 0.95-3.39; P = .07), cortisol-secreting tumor (HR, 2.38; 95% CI, 1.27-4.48; P = .01), and capsular invasion (HR, 1.96; 95% CI, 1.02-3.74; P = .04). Factors selected as predicting OS were tumor size of at least 12 cm (HR, 1.78; 95% CI, 1.00-3.17; P = .05), positive nodal status (HR, 5.89; 95% CI, 2.05-16.87; P = .001), and R1 margin (HR, 2.83; 95% CI, 1.51-5.30; P = .001). The discriminative ability and calibration of the nomograms revealed good predictive ability as indicated by the C statistics (0.74 for RFS and 0.70 for OS).Conclusions and relevanceIndependent predictors of survival and recurrence risk after curative-intent surgery for ACC were selected to create nomograms predicting RFS and OS. The nomograms were able to stratify patients into prognostic groups and performed well on internal validation.

Project description:Objective:Klatskin tumors are rare, malignant tumors of the biliary system with a poor prognosis for patient survival. The current understanding of these tumors is limited to a small number of case reports or case series; therefore, we examined prognostic factors of this disease. Methods:A population cohort study was conducted in patients selected from the Surveillance, Epidemiology, and End Results (SEER) database with a Klatskin tumor that was histologically diagnosed between 2004 to 2014. Propensity-matching (PSM) analysis was performed to determine the overall survival (OS) among those with a Klatskin tumor (KCC), intrahepatic cholangiocarcinoma (ICCA), or hepatocellular carcinoma (HCC). The nomogram was based on 317 eligible Klatskin tumor patients and its predictive accuracy and discriminatory ability were determined using the concordance index (C-index). Results:Kaplan-Meier analysis showed that patients with Klatskin tumors had significantly worse overall survival rates (1-year OS = 26.2%, 2-year OS = 10.7%, 3-year OS = 3.4%) than those with intrahepatic cholangiocarcinoma (1-year OS = 62.2%, 2-year OS = 36.4%, 3-year OS = 19.1%, p < 0.001) or hepatocellular carcinoma (1-year OS = 72.4% , 2-year OS = 48.5%, 3-year OS = 36.2%, p < 0.001). A poor prognosis was also significantly associated with older age, higher grade, SEER historic stage, and lymph node metastasis. Local destruction of the tumor (HR = 0.635, 95% CI [0.421-0.956], p = 0.03) and surgery (HR = 0.434, 95% [CI 0.328-0.574], p < 0.001) were independent protective factors. Multivariate Cox analysis showed that older age, SEER historic stage, and lymph node metastases (HR = 1.468, 95% CI [1.008-2.139], p = 0.046) were independent prognostic factors of poor survival rates in Klatskin tumor patients, while cancer-directed surgery was an independent protective factor (HR = 0.555, 95% CI [0.316-0.977], p = 0.041). The prognostic and protective factors were included in the nomogram (C-index for survival = 0.651; 95% CI [0.607-0.695]). Conclusions:The Klatskin tumor group had poorer rates of OS and cancer-specific survival than the ICCA and HCC groups. Early detection and diagnosis were associated with a higher rate of OS in Klatskin tumor patients.

Project description:ObjectivesThis study aims to establish nomograms to accurately predict the overall survival (OS) and progression-free survival (PFS) in patients with non-small cell lung cancer (NSCLC) who received chemotherapy alone as the first-line treatment.Materials and methodsIn a training cohort of 121 NSCLC patients, radiomic features were extracted, selected from intra- and peri-tumoral regions, and used to build signatures (S1 and S2) using a Cox regression model. Deep learning features were obtained from three convolutional neural networks and utilized to build signatures (S3, S4, and S5) that were stratified into over- and under-expression subgroups for survival risk using X-tile. After univariate and multivariate Cox regression analyses, a nomogram incorporating the tumor, node, and metastasis (TNM) stages, radiomic signature, and deep learning signature was established to predict OS and PFS, respectively. The performance was validated using an independent cohort (61 patients).ResultsTNM stages, S2 and S3 were identified as the significant prognosis factors for both OS and PFS; S2 (OS: (HR (95%), 2.26 (1.40-3.67); PFS: (HR (95%), 2.23 (1.36-3.65)) demonstrated the best ability in discriminating patients with over- and under-expression. For the OS nomogram, the C-index (95% CI) was 0.74 (0.70-0.79) and 0.72 (0.67-0.78) in the training and validation cohorts, respectively; for the PFS nomogram, the C-index (95% CI) was 0.71 (0.68-0.81) and 0.72 (0.66-0.79). The calibration curves for the 3- and 5-year OS and PFS were in acceptable agreement between the predicted and observed survival. The established nomogram presented a higher overall net benefit than the TNM stage for predicting both OS and PFS.ConclusionBy integrating the TNM stage, CT radiomic signature, and deep learning signatures, the established nomograms can predict the individual prognosis of NSCLC patients who received chemotherapy. The integrated nomogram has the potential to improve the individualized treatment and precise management of NSCLC patients.

Dataset Information

Development and external validation of nomograms to predict the risk of skeletal metastasis at the time of diagnosis and skeletal metastasis-free survival in nasopharyngeal carcinoma.

Publications

Development and external validation of nomograms to predict the risk of skeletal metastasis at the time of diagnosis and skeletal metastasis-free survival in nasopharyngeal carcinoma.

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