Comparison of three risk stratification models for non-clear cell renal cell carcinoma patients treated with temsirolimus as first-line therapy
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Background/Aims: For metastatic renal cell carcinoma (RCC), various prognostic scoring systems have been developed. However, owing to the low prevalence of nonclear cell RCC, the three most commonly used tools were mainly developed based on patients with clear cell histology. Accordingly, this study applied three prognostic models to Korean non-clear cell RCC patients treated with first-line temsirolimus. Methods: This study analyzed data for 74 patients with non-clear cell RCC who were treated with temsirolimus as the first-line therapy at eight medical centers between 2011 and 2016. The receiver-operating characteristic (ROC) curves for the different prognostic models were analyzed. Results: Twenty-seven (36.5%), 24 (32.4%), and 44 patients (59.5%) were assigned to the poor prognosis groups of the Memorial Sloan-Kettering Cancer Center (MSKCC), International Metastatic RCC Database Consortium (IMDC), and Advanced Renal Cell Carcinoma (ARCC) risk stratification models, respectively. All three prognostic models reliably discriminated the risk groups to predict progression-free survival and overall survival (p < 0.001). The area under the ROC curve (AUC) for progression and survival was highest for the ARCC model (0.777; 0.734), followed by the IMDC (0.756; 0.724) and the MSKCC (0.742; 0.712) models. Furthermore, the sensitivity and specificity for predicting progression were highest with the ARCC model (sensitivity 63.6%, specificity 85.7%), followed by the MSKCC (sensitivity 58.2%, specificity 86.5%) and the IMDC models (sensitivity 56.4%, specificity 85.7%). Conclusions: All three prognostic models accurately predicted the survival of the nonclear cell RCC patients treated with temsirolimus as the first-line therapy. Furthermore, the ARCC risk model performed better than the other risk models in predicting survival.
Abstract
Background/Aims: For metastatic renal cell carcinoma (RCC), various prognostic scoring systems have been developed. However, owing to the low prevalence of nonclear cell RCC, the three most commonly used tools were mainly developed based on patients with clear cell histology. Accordingly, this study applied three prognostic models to Korean non-clear cell RCC patients treated with first-line temsirolimus. Methods: This study analyzed data for 74 patients with non-clear cell RCC who were treated with temsirolimus as the first-line therapy at eight medical centers between 2011 and 2016. The receiver-operating characteristic (ROC) curves for the different prognostic models were analyzed. Results: Twenty-seven (36.5%), 24 (32.4%), and 44 patients (59.5%) were assigned to the poor prognosis groups of the Memorial Sloan-Kettering Cancer Center (MSKCC), International Metastatic RCC Database Consortium (IMDC), and Advanced Renal Cell Carcinoma (ARCC) risk stratification models, respectively. All three prognostic models reliably discriminated the risk groups to predict progression-free survival and overall survival (p < 0.001). The area under the ROC curve (AUC) for progression and survival was highest for the ARCC model (0.777; 0.734), followed by the IMDC (0.756; 0.724) and the MSKCC (0.742; 0.712) models. Furthermore, the sensitivity and specificity for predicting progression were highest with the ARCC model (sensitivity 63.6%, specificity 85.7%), followed by the MSKCC (sensitivity 58.2%, specificity 86.5%) and the IMDC models (sensitivity 56.4%, specificity 85.7%). Conclusions: All three prognostic models accurately predicted the survival of the nonclear cell RCC patients treated with temsirolimus as the first-line therapy. Furthermore, the ARCC risk model performed better than the other risk models in predicting survival.
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