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Tumor Growth Rate Estimates Are Independently Predictive of Therapy Response and Survival in Recurrent High-Grade Serous Ovarian Cancer Patients

SIMPLE SUMMARY: While latest evidence suggests that some patients with recurrent high-grade serous ovarian cancer may profit from reinduction with platinum-based chemotherapy regimens, the selection of patients who are likely to respond remains difficult. The present study therefore aimed to adapt a...

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Detalles Bibliográficos
Autores principales: Bartl, Thomas, Karacs, Jasmine, Kreuzinger, Caroline, Pfaffinger, Stephanie, Kendler, Jonatan, Ciocsirescu, Cristina, Wolf, Andrea, Reinthaller, Alexander, Meyer, Elias, Brandstetter, Maximilian, Postl, Magdalena, Langthaler, Eva, Braicu, Elena, Vergote, Ignace, Cunnea, Paula, Gourley, Charlie, Schmitt, Wolfgang D., Cacsire Castillo-Tong, Dan, Christoph, Grimm
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7959281/
https://www.ncbi.nlm.nih.gov/pubmed/33802395
http://dx.doi.org/10.3390/cancers13051076
Descripción
Sumario:SIMPLE SUMMARY: While latest evidence suggests that some patients with recurrent high-grade serous ovarian cancer may profit from reinduction with platinum-based chemotherapy regimens, the selection of patients who are likely to respond remains difficult. The present study therefore aimed to adapt a mathematical model, which used frequently available laboratory values to estimate growth rates of recurring tumors as an objectifiable surrogate of both therapy response and patient survival. After clinical validation, the model may help to personalize treatment strategies and thereby increase survival of affected patients. ABSTRACT: This study aimed to assess the predictive value of tumor growth rate estimates based on serial cancer antigen-125 (CA-125) levels on therapy response and survival of patients with recurrent high-grade serous ovarian cancer (HGSOC). In total, 301 consecutive patients with advanced HGSOC (exploratory cohort: n = 155, treated at the Medical University of Vienna; external validation cohort: n = 146, from the Ovarian Cancer Therapy–Innovative Models Prolong Survival (OCTIPS) consortium) were enrolled. Tumor growth estimates were obtained using a validated two-phase equation model involving serial CA-125 levels, and their predictive value with respect to treatment response to the next chemotherapy and the prognostic value with respect to disease-specific survival and overall survival were assessed. Tumor growth estimates were an independent predictor for response to second-line chemotherapy and an independent prognostic factor for second-line chemotherapy use in both univariate and multivariable analyses, outperforming both the predictive (second line: p = 0.003, HR 5.19 [1.73–15.58] vs. p = 0.453, HR 1.95 [0.34–11.17]) and prognostic values (second line: p = 0.042, HR 1.53 [1.02–2.31] vs. p = 0.331, HR 1.39 [0.71–2.27]) of a therapy-free interval (TFI) < 6 months. Tumor growth estimates were a predictive factor for response to third- and fourth-line chemotherapy and a prognostic factor for third- and fourth-line chemotherapy use in the univariate analysis. The CA-125-derived tumor growth rate estimate may be a quantifiable and easily assessable surrogate to TFI in treatment decision making for patients with recurrent HGSOC.