ArticleAngiogenesis2019
A new prognostic model for survival in second line for metastatic renal cell carcinoma: development and external validation.
Article in Angiogenesis, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 3 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
A Randomized Trial Of Temsirolimus Versus Sorafenib As Second-Line Therapy In Patients With Advanced Renal Cell Carcinoma Who Have Failed First-Line Sunitinib Therapy
Axitinib (ag-013736) as second line therapy for metastatic renal cell cancer: axis trial
Who cites it
3 citing papers in PubMed.
- Establishment and Validation of a Machine Learning Prediction Model Based on Big Data for Predicting the Risk of Bone Metastasis in Renal Cell Carcinoma Patients.Computational and mathematical methods in medicine · 2022Article
- Effects of early vs delayed progression on clinical and economic outcomes in patients with metastatic renal cell carcinoma treated with tyrosine kinase inhibitors as first-line therapy: results from the IMPACT RCC claims data analysis.Journal of managed care & specialty pharmacy · 2021Article
- A novel definition of microvessel density in renal cell carcinoma: Angiogenesis plus vasculogenic mimicry.Oncology letters · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn patients with metastatic renal cell carcinoma (mRCC), the oncologic benefit of second-line treatment for high volume tumors or presence of more than five risk factors remain to be defined. Our aim was to develop and externally validate a new model most likely to correctly predict overall survival (OS) categories in second line.
methodmRCC patients treated within clinical trials at Gustave Roussy Cancer Campus (GRCC) formed the discovery set. Patients from two phase III trials from Pfizer database (PFIZERDB), AXIS (NCT00678392), and INTORSECT (NCT00474786), formed the external validation set. New prognostic factors were analyzed using a multivariable Cox model with a backward selection procedure. Performance of the GRCC model and the prognostic classification scheme derived from it, measuring by R
resultsTwo hundred and twenty-one patients were included in the GRCC cohort and 855 patients in the PFIZERDB. Median OS was similar in the discovery and validation cohorts (16.8 [95% CI 12.9-21.7] and 15.3 [13.6-17.2] months, respectively). Backward selection procedure identified time from first to second-line treatment and tumor burden as new independent prognostic factors significantly associated to OS after adjusting for IMDC prognostic factors (HR 1.68 [1.23-2.31] and 1.43 [1.03-1.99], respectively). Dividing patients into four risk groups, based on the number of factors selected in GRCC model, median OS from the start of second line in the validation cohort was not reached (NE) [95% CI 24.9-NE] in the favorable risk group (n = 20), 21.8 months [18.6-28.2] in the intermediate-risk group (n = 367), 12.7 months [11.0-15.8] in the low poor-risk group (n = 347), and 5.5 months [4.7-6.4] in the high poor-risk group (n = 121). Finally, this model and its prognostic classification scheme provided the better fit, with higher R
conclusionA new prognostic model was developed and validated to estimate overall survival of patients with previously treated mRCC. This model is an easy-to-use tool that allows accurate estimation of patient survival to inform decision making and follow-up after first line for mRCC.
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Registered trials
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