Jennifer L Lund1, Paul R Duberstein2, Kah Poh Loh3, Nikesha Gilmore3, Sandy Plumb3, Lianlian Lei4, Alexander P Keil5, Jessica Y Islam5, Laura C Hanson6, Jeffrey K Giguere7, Victor G Vogel8, Brian L Burnette9, Supriya G Mohile3. 1. Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. Electronic address: jennifer.lund@unc.edu. 2. Department of Health Behavior, Society and Policy, Rutgers School of Public Health, Piscataway, NJ, USA. 3. James P. Wilmot Cancer Institute, Division of Hematology/Oncology, Department of Medicine, University of Rochester, Rochester, NY, USA. 4. Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA. 5. Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. 6. Division of Geriatric Medicine, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. 7. NCORP of the Carolinas (Greenville Health System NCORP), Greenville, SC, USA. 8. Geisinger Cancer Institute NCORP, Danville, PA, USA. 9. Cancer Research of Wisconsin and Northern Michigan (CROWN) NCORP, Grand Rapids, MI, USA.
Abstract
OBJECTIVES: Oncologists estimate patients' prognosis to guide care. Evidence suggests oncologists tend to overestimate life expectancy, which can lead to care with questionable benefits. Information obtained from geriatric assessment may improve prognostication for older adults. In this study, we created a geriatric assessment-based prognostic model for older adults with advanced cancer and compared its performance to alternative models. MATERIALS AND METHODS: We conducted a secondary analysis of a trial (URCC 13070; PI: Mohile) capturing geriatric assessment and vital status up to one year for adults age ≥ 70 years with advanced cancer. Oncologists estimated life expectancy as 0-6 months, 7-12 months, and > 1 year. Three statistical models were developed: (1) a model including age, sex, cancer type, and stage (basic model), (2) basic model + Karnofsky Performance Status (≤50, 60-70, and 80+) (KPS model), and (3) basic model +16 binary indicators of geriatric assessment impairments (GA model). Cox regression was used to model one-year survival; c-indices and time-dependent c-statistics assessed model discrimination and stratified survival curves assessed model calibration. RESULTS: We included 484 participants; mean age was 75; 48% had gastrointestinal or lung cancer. Overall, 43% of patients died within one year. Oncologists classified prognosis accurately for 55% of patients, overestimated for 35%, and underestimated for 10%. C-indices were 0.61 (basic model), 0.62 (KPS model), and 0.63 (GA model). The GA model was well-calibrated. CONCLUSIONS: The GA model showed moderate discrimination for survival, similar to alternative models, but calibration was improved. Further research is needed to optimize geriatric assessment-based prognostic models for use in older adults with advanced cancer.
OBJECTIVES: Oncologists estimate patients' prognosis to guide care. Evidence suggests oncologists tend to overestimate life expectancy, which can lead to care with questionable benefits. Information obtained from geriatric assessment may improve prognostication for older adults. In this study, we created a geriatric assessment-based prognostic model for older adults with advanced cancer and compared its performance to alternative models. MATERIALS AND METHODS: We conducted a secondary analysis of a trial (URCC 13070; PI: Mohile) capturing geriatric assessment and vital status up to one year for adults age ≥ 70 years with advanced cancer. Oncologists estimated life expectancy as 0-6 months, 7-12 months, and > 1 year. Three statistical models were developed: (1) a model including age, sex, cancer type, and stage (basic model), (2) basic model + Karnofsky Performance Status (≤50, 60-70, and 80+) (KPS model), and (3) basic model +16 binary indicators of geriatric assessment impairments (GA model). Cox regression was used to model one-year survival; c-indices and time-dependent c-statistics assessed model discrimination and stratified survival curves assessed model calibration. RESULTS: We included 484 participants; mean age was 75; 48% had gastrointestinal or lung cancer. Overall, 43% of patients died within one year. Oncologists classified prognosis accurately for 55% of patients, overestimated for 35%, and underestimated for 10%. C-indices were 0.61 (basic model), 0.62 (KPS model), and 0.63 (GA model). The GA model was well-calibrated. CONCLUSIONS: The GA model showed moderate discrimination for survival, similar to alternative models, but calibration was improved. Further research is needed to optimize geriatric assessment-based prognostic models for use in older adults with advanced cancer.
Authors: Arti Hurria; Tanya Wildes; Sarah L Blair; Ilene S Browner; Harvey Jay Cohen; Mollie Deshazo; Efrat Dotan; Barish H Edil; Martine Extermann; Apar Kishor P Ganti; Holly M Holmes; Reshma Jagsi; Mohana B Karlekar; Nancy L Keating; Beatriz Korc-Grodzicki; June M McKoy; Bruno C Medeiros; Ewa Mrozek; Tracey O'Connor; Hope S Rugo; Randall W Rupper; Rebecca A Silliman; Derek L Stirewalt; William P Tew; Louise C Walter; Alva B Weir; Mary Anne Bergman; Hema Sundar Journal: J Natl Compr Canc Netw Date: 2014-01 Impact factor: 11.908
Authors: Arti Hurria; Supriya Gupta; Marjorie Zauderer; Enid L Zuckerman; Harvey J Cohen; Hyman Muss; Miriam Rodin; Katherine S Panageas; Jimmie C Holland; Leonard Saltz; Mark G Kris; Ariela Noy; Jorge Gomez; Ann Jakubowski; Clifford Hudis; Alice B Kornblith Journal: Cancer Date: 2005-11-01 Impact factor: 6.860
Authors: Cheryl P Bruijnen; Diny G van Harten-Krouwel; José J Koldenhof; Mariëlle H Emmelot-Vonk; Petronella O Witteveen Journal: J Geriatr Oncol Date: 2019-03-27 Impact factor: 3.599
Authors: Rachael K Ross; Tzy-Mey Kuo; Michael Webster-Clark; Carmen L Lewis; Christine E Kistler; Michele Jonsson Funk; Jennifer L Lund Journal: J Am Geriatr Soc Date: 2020-09-05 Impact factor: 5.562
Authors: Arti Hurria; Constance T Cirrincione; Hyman B Muss; Alice B Kornblith; William Barry; Andrew S Artz; Linda Schmieder; Rafat Ansari; William P Tew; Douglas Weckstein; Jeffrey Kirshner; Kayo Togawa; Kurt Hansen; Vani Katheria; Richard Stone; Ilene Galinsky; John Postiglione; Harvey Jay Cohen Journal: J Clin Oncol Date: 2011-02-28 Impact factor: 44.544
Authors: Hung-Jui Tan; Xi Zhou; Brooke N Spratte; Stephen McMahon; Matthew E Nielsen; Jennifer Lund; Alex H S Harris; Angela B Smith; Ethan Basch Journal: J Urol Date: 2020-09-10 Impact factor: 7.450
Authors: B E Kiely; G McCaughan; S Christodoulou; P J Beale; P Grimison; J Trotman; M H N Tattersall; M R Stockler Journal: Support Care Cancer Date: 2012-06-21 Impact factor: 3.603
Authors: Grant R Williams; Chen Dai; Smith Giri; Mustafa Al-Obaidi; Christian Harmon; Kelly M Kenzik; Andrew McDonald; Olumide Gbolahan; Darryl Outlaw; Moh'd Khushman; Joshua Richman; Smita Bhatia Journal: JCO Clin Cancer Inform Date: 2022-09