Page 171 - Haematologica May 2022
P. 171

 RCT of geriatric consultation in blood cancers
   studies should determine not only which models may be effective, but also whether certain components of GA-dri- ven interventions are more effective than others. The ben- efits of different models must be balanced against their scal- ability, especially considering the current limitations in oncology practices’ access to geriatricians.46,47 Such informa- tion will help oncology practices with varying resources adapt models of geriatric care that are feasible, effective, and sustainable in improving the care of older patients with blood cancers.
Disclosures
RJS serves on the Board of Directors for Kiadis and Be The Match/National Marrow Donor Program; has provided consulting for Gilead, Rheos Therapeutics, VOR Biopharma, and Takeda; and served on a Data Safety Monitoring Board for Juno/Celgene.
Contributions
GAA, JAD, RMS, and RJS designed the trial and oversaw execution of the protocol, contributed to data analysis and inter- pretation, and to preparing the manuscript; CD contributed to data acquisition, analysis, and interpretation, and wrote manu- script; HU contributed to the trial design, data analysis and interpretation, and to preparing the manuscript; GZ analyzed data and contributed to interpretation and manuscript prepara- tion; TH oversaw execution of the protocol, contributed to data acquisition and interpretation, and to preparing the manuscript;
RC and EM contributed to data acquisition and interpretation, and to preparing the manuscript; LM and HJ oversaw execution of the protocol, and contributed to data interpretation and preparing the manuscript.
Funding
This work was supported by the Harvard Translational Research in Aging Training Program (National Institute on Aging of the National Institutes of Health: T32AG023480) (CD); the Dana-Farber/Harvard Cancer Center SPORE in Multiple Myeloma (National Cancer Institute of the National Institutes of Health: P50 CA100707) (CD); the Harvard Catalyst (GZ); the Harvard Clinical and Translational Science Center (National Center for Advancing Translational Sciences, National Institutes of Health Award UL 1TR002541) and financial contributions from Harvard University and its affiliated academic healthcare centers. The content is solely the responsibility of the authors and does not necessarily represent the official views of Harvard Catalyst, Harvard University and its affiliated academic healthcare centers, or the National Institutes of Health; the Older Adult Hematologic Malignancy Program is supported by the Murphy Family Fund from the Dana-Farber Cancer Institute (GAA)
Data-sharing statement
Data and protocol requests will be considered on a case by case basis and in accordance with the regulations of the Dana-Farber Harvard Cancer Center Office for Human Research Studies.
References
1. Surveillance, Epidemiology, and End Results (SEER) (2013-2017). Cancer Stat Facts: Myeloma. National Cancer Institute. Accessed June, 2020. https://seer.cancer.gov/statfacts/html/mul my.html
2. Surveillance, Epidemiology, and End Results (SEER) (2013-2017). Cancer Stat Facts: Leukemia. National Cancer Institute. Accessed June, 2020. https://seer.cancer.gov/statfacts/html/mul my.html
3. Surveillance, Epidemiology, and End Results (SEER) (2013-2017). Cancer Stat Facts: Non-Hodgkin Lymphoma. National Cancer Institute. Accessed June, 2020. https://seer.cancer.gov/statfacts/html/mul my.html
4. Abel GA, Klepin HD. Frailty and the man- agement of hematologic malignancies. Blood. 2018;131(5):515-524.
5.Hshieh TT, Jung WF, Grande LJ, et al. Prevalence of cognitive impairment and association with survival among older patients with hematologic cancers. JAMA Oncol. 2018;4(5):686-693.
6. DuMontier C, Liu MA, Murillo A, et al. Function, survival, and care utilization among older adults with hematologic malignancies. J Am Geriatr Soc. 2019;67 (5):889-897.
7. Liu MA, DuMontier C, Murillo A, et al. Gait speed, grip strength, and clinical out- comes in older patients with hematologic malignancies. Blood. 2019;134(4):374-382.
8. Mohile SG, Dale W, Somerfield MR, et al. Practical assessment and management of vulnerabilities in older patients receiving chemotherapy: ASCO guideline for geri- atric oncology. J Clin Oncol. 2018;36(22):2326-2347.
9. Repetto L, Fratino L, Audisio RA, et al.
Comprehensive geriatric assessment adds information to Eastern Cooperative Oncology Group performance status in eld- erly cancer patients: an Italian Group for Geriatric Oncology Study. J Clin Oncol. 2002;20(2):494-502.
10. Hurria A, Mohile S, Gajra A, et al. Validation of a prediction tool for chemotherapy toxicity in older adults with cancer. J Clin Oncol. 2016;34(20):2366- 2371.
11.Extermann M, Boler I, Reich RR, et al. Predicting the risk of chemotherapy toxici- ty in older patients: the Chemotherapy Risk Assessment Scale for High-Age Patients (CRASH) score. Cancer. 2012;118(13):3377-3386.
GECP 08-02 study. J Clin Oncol. 2016;34
(13):1476-1483.
17. Nipp RD, Temel B, Fuh C-X, et al. Pilot ran-
domized trial of a transdisciplinary geriatric and palliative care intervention for older adults with cancer. J Natl Compr Canc Netw. 2020;18(5):591.
18.Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: evidence for a phe- notype. J Gerontol A Biol Sci Med Sci. 2001;56(3):M146-156.
19.Rockwood K, Mitnitski A. Frailty in rela- tion to the accumulation of deficits. J Gerontol A Biol Sci Med Sci. 2007;62(7): 722-727.
20.Temel JS, Greer JA, Muzikansky A, et al. Early palliative care for patients with metastatic non-small-cell lung cancer. N Engl J Med. 2010;363(8):733-742.
12.
13.
14.
Palumbo A, Bringhen S, Mateos MV, et al. Geriatric assessment predicts survival and toxicities in elderly myeloma patients: an International Myeloma Working Group report. Blood. 2015;125(13):2068-2074. Mohile SG, Velarde C, Hurria A, et al. Geriatric assessment-guided care processes for older adults: a Delphi consensus of geri- atric oncology experts. J Natl Compr Canc Netw. 2015;13(9):1120-1130.
Mohile SG, Magnuson A, Pandya C, et al. Community oncologists' decision-making for treatment of older patients with cancer. J Natl Compr Canc Netw. 2018;16(3):301- 309.
21.
22.
23.
Abel GA, Neufeld EJ, Sorel M, Weeks JC. Direct-to-consumer advertising for bleed- ing disorders: a content analysis and expert evaluation of advertising claims. J Thromb Haemost. 2008;6(10):1680-1684. El-Jawahri AR, Abel GA, Steensma DP, et al. Health care utilization and end-of-life care for older patients with acute myeloid leukemia. Cancer. 2015;121(16):2840-2848. Mack JW, Cronin A, Taback N, et al. End- of-life care discussions among patients with advanced cancer: a cohort study. Ann Int Med. 2012;156(3):204-210.
15.Mohile SG, Epstein RM, Hurria A, et al. Communication with older patients with cancer using geriatric assessment: a cluster- randomized clinical trial from the National Cancer Institute community oncology research program. JAMA Oncol. 2019;6(2): 196-204.
16. Corre R, Greillier L, Caër HL, et al. Use of a comprehensive geriatric assessment for the management of elderly patients with advanced non-small-cell lung cancer: the phase III randomized ESOGIA-GFPC-
24.Uno H, Claggett B, Tian L, et al. Moving beyond the hazard ratio in quantifying the between-group difference in survival analy- sis. J Clin Oncol. 2014;32(22):2380-2385.
25. surv2sampleComp: Inference for Model- Free Between-Group Parameters for Censored Survival Data. R package version 1.0-5. 2017. https://CRAN.R- project.org/package=surv2sampleComp
26.Uno H, Cai T, Tian L, Wei LJ. Evaluating prediction rules for t-year survivors with censored regression models. J Am Stat Ass.
haematologica | 2022; 107(5)
  1179
  



















































   169   170   171   172   173