Skip to main content

Advertisement

Log in

All-Cause Mortality Risk Prediction in Older Adults with Cancer: Practical Approaches and Limitations

  • Geriatric Oncology (L Balducci, Section Editor)
  • Published:
Current Oncology Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

The prediction of all-cause mortality is an important component of shared decision-making across the cancer care continuum, particularly in older adults with limited life expectancy, for whom there is an increased risk of over-diagnosis and treatment.

Recent Findings

Currently, several international societies recommend the use of all-cause mortality risk prediction tools when making decisions regarding screening and treatment in geriatric oncology.

Summary

Here, we review some practical aspects of the utilization of those tools and dissect the characteristics of those most employed in geriatric oncology, highlighting both their advantages and their limitations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. Lee SJ, Lindquist K, Segal MR, Covinsky KE. Development and validation of a prognostic index for 4-year mortality in older adults. JAMA. 2006;295(7):801–8. https://doi.org/10.1001/jama.295.7.801.

    Article  CAS  PubMed  Google Scholar 

  2. Mariotto AB, Noone A-M, Howlader N, Cho H, Keel GE, Garshell J, et al. Cancer survival: an overview of measures, uses, and interpretation. J Natl Cancer Inst Monogr. 2014;2014(49):145–86. https://doi.org/10.1093/jncimonographs/lgu024.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Berry SD, Ngo L, Samelson EJ, Kiel DP. Competing risk of death: an important consideration in studies of older adults. J Am Geriatr Soc. 2010;58(4):783–7. https://doi.org/10.1111/j.1532-5415.2010.02767.x.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Gómez-Moreno C, Pilleron S, Neuendorff NR, Soto-Perez-de-Celis E. How we use noncancer-specific survival prediction in geriatric oncology: a Young International Society of Geriatric Oncology and Nursing & Allied Health Interest Group initiative. J Geriatr Oncol. 2021. https://doi.org/10.1016/j.jgo.2021.10.005.

    PubMed  Google Scholar 

  5. Lambden J, Zhang B, Friedlander R, Prigerson HG. Accuracy of oncologists’ life-expectancy estimates recalled by their advanced cancer patients: correlates and outcomes. J Palliat Med. 2016;19(12):1296–303. https://doi.org/10.1089/jpm.2016.0121.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Soto-Perez-de-Celis E, Li DN, Yuan Y, Lau YM, Hurria A. Functional versus chronological age: geriatric assessments to guide decision making in older patients with cancer. Lancet Oncology. 2018;19(6):E305–16. https://doi.org/10.1016/s1470-2045(18)30348-6. Comprehensive review of the use of the geriatric assessment for decision-making in older adults with cancer.

    Article  PubMed  Google Scholar 

  7. Mohile SG, Dale W, Somerfield MR, Hurria A. Practical assessment and management of vulnerabilities in older patients receiving chemotherapy: ASCO Guideline for Geriatric Oncology Summary. J Oncol Pract. 2018;14(7):442-+. https://doi.org/10.1200/jop.18.00180.

    Article  PubMed  Google Scholar 

  8. Loh KP, Soto-Perez-de-Celis E, Hsu T, de Glas NA, Battisti NML, Baldini C, et al. What every oncologist should know about geriatric assessment for older patients with ancer: Young International Society of Geriatric Oncology Position Paper. J Oncol Pract. 2018;14(2):85–94. https://doi.org/10.1200/JOP.2017.026435.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Verduzco-Aguirre HC, Gomez-Moreno C, Chavarri-Guerra Y, Soto-Perez-de-Celis E. Predicting life expectancy for older adults with cancer in clinical practice: implications for shared decision-making. Curr Oncol Rep. 2019;21(8):68. https://doi.org/10.1007/s11912-019-0821-3.

    Article  PubMed  Google Scholar 

  10. DuMontier C, Loh KP, Soto-Perez-de-Celis E, Dale W. Decision making in older adults with cancer. J Clin Oncol. 2021;39(19):2164–74. https://doi.org/10.1200/jco.21.00165. Recent narrative review on the relevance of shared decision-making in older adults with cancer includes strategies for the incorporation of all-cause mortality risk prediction in decision-making.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Ferlay J, Ervik M, Lam F, Colombet M, Mery L, Piñeros M, Znaor A, Soerjomataram I, Bray F (2018). Global cancer observatory: cancer today. Lyon, France: International Agency for Research on Cancer. Available from: https://gco.iarc.fr/today, accessed April 4 2019.

  12. Verduzco-Aguirre HC, Navarrete-Reyes AP, Chavarri-Guerra Y, Soto-Perez-de-Celis E. Cancer screening. In: Gu D, Dupre ME, editors. Encyclopedia of Gerontology and Population Aging. Cham: Springer International Publishing; 2020. p. 1–8.

    Google Scholar 

  13. Breslau ES, Gorin SS, Edwards HM, Schonberg MA, Saiontz N, Walter LC. An individualized approach to cancer screening decisions in older adults: a multilevel framework. J Gen Intern Med. 2016;31(5):539–47. https://doi.org/10.1007/s11606-016-3629-y.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Lee SJ, Boscardin WJ, Stijacic-Cenzer I, Conell-Price J, O’Brien S, Walter LC. Time lag to benefit after screening for breast and colorectal cancer: meta-analysis of survival data from the United States, Sweden, United Kingdom, and Denmark. BMJ. 2013;346:e8441. https://doi.org/10.1136/bmj.e8441.

    Article  PubMed  PubMed Central  Google Scholar 

  15. American Cancer Society Guidelines for the Early Detection of Cancer. https://www.cancer.org/healthy/find-cancer-early/american-cancer-society-guidelines-for-the-early-detection-of-cancer.html Accessed April 14 2022.

  16. Schonberg MA, Breslau ES, Hamel MB, Bellizzi KM, McCarthy EP. Colon cancer screening in U.S. adults aged 65 and older according to life expectancy and age. J Am Geriat Soc. 2015;63(4):750–6. https://doi.org/10.1111/jgs.13335.

    Article  PubMed  Google Scholar 

  17. Screening for colorectal cancer: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med. 2008;149(9):627–37. https://doi.org/10.7326/0003-4819-149-9-200811040-00243.

    Article  Google Scholar 

  18. Siu AL, Screening for Breast Cancer: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med. 2016;164(4):279–96. https://doi.org/10.7326/m15-2886.

    Article  PubMed  Google Scholar 

  19. Breast Cancer Screening in Older Women. J Am Geriatr Soc. 2000;48(7):842–3. https://doi.org/10.1111/j.1532-5415.2000.tb04763.x.

    Article  Google Scholar 

  20. Walter LC, Schonberg MA. Screening mammography in older women: a review. JAMA. 2014;311(13):1336–47. https://doi.org/10.1001/jama.2014.2834.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Arora A, Chadi SA, Chesney T. What should we recommend for colorectal cancer screening in adults aged 75 and older? Curr Oncol. 2021;28(4):2540–7. https://doi.org/10.3390/curroncol28040231.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Tranvåg EJ, Norheim OF, Ottersen T. Clinical decision making in cancer care: a review of current and future roles of patient age. BMC Cancer. 2018;18(1):546. https://doi.org/10.1186/s12885-018-4456-9.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Hurria A, Togawa K, Mohile SG, Owusu C, Klepin HD, Gross CP, et al. Predicting chemotherapy toxicity in older adults with cancer: a prospective multicenter study. J Clin Oncol. 2011;29(25):3457–65. https://doi.org/10.1200/JCO.2011.34.7625.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Hurria A, Mohile S, Gajra A, Klepin H, Muss H, Chapman A, et al. Validation of a prediction tool for chemotherapy toxicity in older adults with cancer. J Clin Oncol. 2016;34(20):2366–71. https://doi.org/10.1200/JCO.2015.65.4327.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Hurria A, Levit LA, Dale W, Mohile SG, Muss HB, Fehrenbacher L, et al. Improving the evidence base for treating older adults with cancer: American Society of Clinical Oncology Statement. J Clin Oncol. 2015;33(32):3826–33. https://doi.org/10.1200/JCO.2015.63.0319.

    Article  PubMed  Google Scholar 

  26. Soto-Perez-De-Celis E, Lichtman SM. Considerations for clinical trial design in older adults with cancer. Expert Opin Investig Drugs. 2017;26(10):1099–102. https://doi.org/10.1080/13543784.2017.1369043.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Mohile SG, Dale W, Somerfield MR, Schonberg MA, Boyd CM, Burhenn PS, et al. Practical assessment and management of vulnerabilities in older patients receiving chemotherapy: ASCO Guideline for Geriatric Oncology. J Clin Oncol. 2018;36(22):2326-+. https://doi.org/10.1200/jco.2018.78.8687.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Soto Perez De Celis E, Li D, Sun CL, Kim H, Twardowski P, Fakih M, et al. Patient-defined goals and preferences among older adults with cancer starting chemotherapy (CT). J Clin Oncol. 2018;36(15_suppl):10009-. https://doi.org/10.1200/JCO.2018.36.15_suppl.10009.

    Article  Google Scholar 

  29. Jang RW, Caraiscos VB, Swami N, Banerjee S, Mak E, Kaya E, et al. Simple prognostic model for patients with advanced cancer based on performance status. J Oncol Pract. 2014;10(5):e335–41. https://doi.org/10.1200/jop.2014.001457.

    Article  PubMed  Google Scholar 

  30. Chow E, Abdolell M, Panzarella T, Harris K, Bezjak A, Warde P, et al. Predictive model for survival in patients with advanced cancer. J Clin Oncol. 2008;26(36):5863–9. https://doi.org/10.1200/jco.2008.17.1363.

    Article  PubMed  Google Scholar 

  31. Widera EW, Block SD. Managing grief and depression at the end of life. Am Fam Physician. 2012;86(3):259–64.

    PubMed  Google Scholar 

  32. Morita T, Tsunoda J, Inoue S, Chihara S. The Palliative Prognostic Index: a scoring system for survival prediction of terminally ill cancer patients. Support Care Cancer. 1999;7(3):128–33. https://doi.org/10.1007/s005200050242.

    Article  CAS  PubMed  Google Scholar 

  33. Dotan E, Walter LC, Browner IS, Clifton K, Cohen HJ, Extermann M, et al. NCCN Guidelines® insights: older adult oncology, Version 1.2021. J Natl Compr Canc Netw. 2021;19(9):1006–19. https://doi.org/10.6004/jnccn.2021.0043.

    Article  PubMed  Google Scholar 

  34. Cowley LE, Farewell DM, Maguire S, Kemp AM. Methodological standards for the development and evaluation of clinical prediction rules: a review of the literature. Diagn Progn Research. 2019;3(1):16. https://doi.org/10.1186/s41512-019-0060-y.

    Article  Google Scholar 

  35. Wolff RF, Moons KGM, Riley RD, Whiting PF, Westwood M, Collins GS, et al. PROBAST: a tool to assess the risk of bias and applicability of prediction model studies. Ann Intern Med. 2019;170(1):51–8. https://doi.org/10.7326/m18-1376. Development of a tool to assess the risk of bias and applicability of prediction models. This tool was used to analyze the indices included in this manuscript (see Supplementary files).

    Article  PubMed  Google Scholar 

  36. Dahabreh IJ, Chan JA, Earley A. Modeling and simulation in the context of health technology assessment: review of existing guidance, future research needs, and validity assessment [Internet]. Rockville (MD): Agency for Healthcare Research and Quality (US); 2017 Jan. Chapter 4, A review of validation and calibration methods for health care modeling and simulation. Available from: https://www.ncbi.nlm.nih.gov/books/NBK424022/. Accessed May 17, 2022.

  37. Gagne JJ, Glynn RJ, Avorn J, Levin R, Schneeweiss S. A combined comorbidity score predicted mortality in elderly patients better than existing scores. J Clin Epidemiol. 2011;64(7):749–59. https://doi.org/10.1016/j.jclinepi.2010.10.004.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Sun JW, Rogers JR, Her Q, Welch EC, Panozzo CA, Toh S, et al. Adaptation and validation of the combined comorbidity score for ICD-10-CM. Med Care. 2017;55(12):1046–51. https://doi.org/10.1097/mlr.0000000000000824.

    Article  PubMed  Google Scholar 

  39. Cruz M, Covinsky K, Widera EW, Stijacic-Cenzer I, Lee SJ. Predicting 10-year mortality for older adults. JAMA. 2013;309(9):874–6. https://doi.org/10.1001/jama.2013.1184.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Kotwal AA, Lee SJ, Dale W, Boscardin WJ, Waite LJ, Smith AK. Integration of an objective cognitive assessment into a prognostic index for 5-year mortality prediction. J Am Geriatr Soc. 2020;68(8):1796–802. https://doi.org/10.1111/jgs.16451.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Suemoto CK, Ueda P, Beltrán-Sánchez H, Lebrão ML, Duarte YA, Wong R, et al. Development and validation of a 10-year mortality prediction model: meta-analysis of individual participant data from five cohorts of older adults in developed and developing countries. J Gerontol A Biol Sci Med Sci. 2017;72(3):410–6. https://doi.org/10.1093/gerona/glw166.

    Article  PubMed  Google Scholar 

  42. Schonberg MA, Davis RB, McCarthy EP, Marcantonio ER. Index to predict 5-year mortality of community-dwelling adults aged 65 and older using data from the National Health Interview Survey. J Gen Intern Med. 2009;24(10):1115–22. https://doi.org/10.1007/s11606-009-1073-y.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Schonberg MA, Davis RB, McCarthy EP, Marcantonio ER. External validation of an index to predict up to 9-year mortality of community-dwelling adults aged 65 and older. J Am Geriatr Soc. 2011;59(8):1444–51. https://doi.org/10.1111/j.1532-5415.2011.03523.x.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Schonberg MA, Li V, Marcantonio ER, Davis RB, McCarthy EP. Predicting mortality up to 14 years among community-dwelling adults aged 65 and older. J Am Geriatr Soc. 2017;65(6):1310–5. https://doi.org/10.1111/jgs.14805.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Anderson F, Downing GM, Hill J, Casorso L, Lerch N. Palliative performance scale (PPS): a new tool. J Palliat Care. 1996;12(1):5–11.

    Article  CAS  PubMed  Google Scholar 

  46. Prompantakorn P, Angkurawaranon C, Pinyopornpanish K, Chutarattanakul L, Aramrat C, Pateekhum C, et al. Palliative Performance Scale and survival in patients with cancer and non-cancer diagnoses needing a palliative care consultation: a retrospective cohort study. BMC Palliat Care. 2021;20(1):74. https://doi.org/10.1186/s12904-021-00773-8.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): explanation and elaboration. Ann Intern Med. 2015;162(1):W1-W73. https://doi.org/10.7326/m14-0698/m25560730.

  48. Carey EC, Walter LC, Lindquist K, Covinsky KE. Development and validation of a functional morbidity index to predict mortality in community-dwelling elders. J Gen Intern Med. 2004;19(10):1027–33. https://doi.org/10.1111/j.1525-1497.2004.40016.x.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Kimmick GG, Major B, Clapp J, Sloan J, Pitcher B, Ballman K, et al. Using ePrognosis to estimate 2-year all-cause mortality in older women with breast cancer: Cancer and Leukemia Group B (CALGB) 49907 and 369901 (Alliance A151503). Breast Cancer Res Treat. 2017;163(2):391–8. https://doi.org/10.1007/s10549-017-4188-6.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Dickerman BA, Hernán MA. Counterfactual prediction is not only for causal inference. Eur J Epidemiol. 2020;35(7):615–7. https://doi.org/10.1007/s10654-020-00659-8.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Royston P, Altman DG, Sauerbrei W. Dichotomizing continuous predictors in multiple regression: a bad idea. Stat Med. 2006;25(1):127–41. https://doi.org/10.1002/sim.2331.

    Article  PubMed  Google Scholar 

  52. Steyerberg EW, Vergouwe Y. Towards better clinical prediction models: seven steps for development and an ABCD for validation. Eur Heart J. 2014;35(29):1925–31. https://doi.org/10.1093/eurheartj/ehu207.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Pirracchio R, Ranzani OT. Recalibrating our prediction models in the ICU: time to move from the abacus to the computer. Intensive Care Med. 2014;40(3):438–41. https://doi.org/10.1007/s00134-014-3231-x.

    Article  PubMed  Google Scholar 

  54. D’Agostino RB Sr, Grundy S, Sullivan LM, Wilson P, Group ftCRP. Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation. JAMA. 2001;286(2):180–7. https://doi.org/10.1001/jama.286.2.180.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Enrique Soto-Perez-de-Celis.

Ethics declarations

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

Conflict of Interest

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is part of the Topical Collection on Geriatric Oncology

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (XLSX 26 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Perez-de-Acha, A., Pilleron, S. & Soto-Perez-de-Celis, E. All-Cause Mortality Risk Prediction in Older Adults with Cancer: Practical Approaches and Limitations. Curr Oncol Rep 24, 1377–1385 (2022). https://doi.org/10.1007/s11912-022-01303-2

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11912-022-01303-2

Keywords

Navigation