Literature DB >> 33802395

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

Thomas Bartl1,2, Jasmine Karacs2, Caroline Kreuzinger2, Stephanie Pfaffinger2, Jonatan Kendler2, Cristina Ciocsirescu1, Andrea Wolf2, Alexander Reinthaller1, Elias Meyer3, Maximilian Brandstetter1, Magdalena Postl1, Eva Langthaler4, Elena Braicu5, Ignace Vergote6, Paula Cunnea7, Charlie Gourley8, Wolfgang D Schmitt9, Dan Cacsire Castillo-Tong2, Grimm Christoph1.   

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.

Entities:  

Keywords:  growth rate; ovarian cancer; platinum-resistant; recurrence; therapy response

Year:  2021        PMID: 33802395      PMCID: PMC7959281          DOI: 10.3390/cancers13051076

Source DB:  PubMed          Journal:  Cancers (Basel)        ISSN: 2072-6694            Impact factor:   6.639


  22 in total

1.  Optimal cut-point and its corresponding Youden Index to discriminate individuals using pooled blood samples.

Authors:  Enrique F Schisterman; Neil J Perkins; Aiyi Liu; Howard Bondell
Journal:  Epidemiology       Date:  2005-01       Impact factor: 4.822

Review 2.  Other paradigms: growth rate constants and tumor burden determined using computed tomography data correlate strongly with the overall survival of patients with renal cell carcinoma.

Authors:  Wilfred D Stein; Hui Huang; Michael Menefee; Maureen Edgerly; Herb Kotz; Andrew Dwyer; James Yang; Susan E Bates
Journal:  Cancer J       Date:  2009 Sep-Oct       Impact factor: 3.360

3.  Definitions for response and progression in ovarian cancer clinical trials incorporating RECIST 1.1 and CA 125 agreed by the Gynecological Cancer Intergroup (GCIG).

Authors:  Gordon John Sampson Rustin; Ignace Vergote; Elizabeth Eisenhauer; Eric Pujade-Lauraine; Michael Quinn; Tate Thigpen; Andreas du Bois; Gunnar Kristensen; Anders Jakobsen; Satoru Sagae; Kathryn Greven; Mahesh Parmar; Michael Friedlander; Andres Cervantes; Jan Vermorken
Journal:  Int J Gynecol Cancer       Date:  2011-02       Impact factor: 3.437

Review 4.  Management of Platinum-Resistant, Relapsed Epithelial Ovarian Cancer and New Drug Perspectives.

Authors:  Eric Pujade-Lauraine; Susana Banerjee; Sandro Pignata
Journal:  J Clin Oncol       Date:  2019-08-12       Impact factor: 44.544

5.  Estimation of tumour regression and growth rates during treatment in patients with advanced prostate cancer: a retrospective analysis.

Authors:  Julia Wilkerson; Kald Abdallah; Charles Hugh-Jones; Greg Curt; Mace Rothenberg; Ronit Simantov; Martin Murphy; Joseph Morrell; Joel Beetsch; Daniel J Sargent; Howard I Scher; Peter Lebowitz; Richard Simon; Wilfred D Stein; Susan E Bates; Tito Fojo
Journal:  Lancet Oncol       Date:  2016-12-13       Impact factor: 41.316

6.  Incorporation of bevacizumab in the primary treatment of ovarian cancer.

Authors:  Robert A Burger; Mark F Brady; Michael A Bookman; Gini F Fleming; Bradley J Monk; Helen Huang; Robert S Mannel; Howard D Homesley; Jeffrey Fowler; Benjamin E Greer; Matthew Boente; Michael J Birrer; Sharon X Liang
Journal:  N Engl J Med       Date:  2011-12-29       Impact factor: 91.245

7.  ESMO-ESGO consensus conference recommendations on ovarian cancer: pathology and molecular biology, early and advanced stages, borderline tumours and recurrent disease†.

Authors:  N Colombo; C Sessa; A du Bois; J Ledermann; W G McCluggage; I McNeish; P Morice; S Pignata; I Ray-Coquard; I Vergote; T Baert; I Belaroussi; A Dashora; S Olbrecht; F Planchamp; D Querleu
Journal:  Ann Oncol       Date:  2019-05-01       Impact factor: 32.976

8.  Evaluating the risk of ovarian cancer before surgery using the ADNEX model to differentiate between benign, borderline, early and advanced stage invasive, and secondary metastatic tumours: prospective multicentre diagnostic study.

Authors:  Ben Van Calster; Kirsten Van Hoorde; Lil Valentin; Antonia C Testa; Daniela Fischerova; Caroline Van Holsbeke; Luca Savelli; Dorella Franchi; Elisabeth Epstein; Jeroen Kaijser; Vanya Van Belle; Artur Czekierdowski; Stefano Guerriero; Robert Fruscio; Chiara Lanzani; Felice Scala; Tom Bourne; Dirk Timmerman
Journal:  BMJ       Date:  2014-10-15

Review 9.  Tumor evolution and chemoresistance in ovarian cancer.

Authors:  Soochi Kim; Youngjin Han; Se Ik Kim; Hee-Seung Kim; Seong Jin Kim; Yong Sang Song
Journal:  NPJ Precis Oncol       Date:  2018-09-17

10.  Distinct evolutionary trajectories of primary high-grade serous ovarian cancers revealed through spatial mutational profiling.

Authors:  Ali Bashashati; Gavin Ha; Alicia Tone; Jiarui Ding; Leah M Prentice; Andrew Roth; Jamie Rosner; Karey Shumansky; Steve Kalloger; Janine Senz; Winnie Yang; Melissa McConechy; Nataliya Melnyk; Michael Anglesio; Margaret T Y Luk; Kane Tse; Thomas Zeng; Richard Moore; Yongjun Zhao; Marco A Marra; Blake Gilks; Stephen Yip; David G Huntsman; Jessica N McAlpine; Sohrab P Shah
Journal:  J Pathol       Date:  2013-09       Impact factor: 7.996

View more
  2 in total

Review 1.  Platinum-resistant ovarian cancer: From drug resistance mechanisms to liquid biopsy-based biomarkers for disease management.

Authors:  Mohammad Aslam Khan; Kunwar Somesh Vikramdeo; Sarabjeet Kour Sudan; Seema Singh; Annelise Wilhite; Santanu Dasgupta; Rodney Paul Rocconi; Ajay Pratap Singh
Journal:  Semin Cancer Biol       Date:  2021-08-18       Impact factor: 15.707

2.  Single-cell isogrowth profiling: Uniform inhibition uncovers non-uniform drug responses.

Authors:  Martin Lukačišin; Adriana Espinosa-Cantú; Tobias Bollenbach
Journal:  Clin Transl Med       Date:  2022-08
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.