The risk of low-grade adverse events in older patients could lead to cumulative toxicity that may impact their quality of life and independence.— Rawad Elias, MD
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Functional status impairment, limited mobility, comorbidities, polypharmacy, and other aging-related manifestations are common in older individuals. These conditions complicate the oncologic management of older adults, who are underrepresented in clinical trials, even though they form the majority of patients with cancer.1 Older patients are often either overtreated or undertreated due to the limited evidence that guides the management of cancer and its treatment-related complications in this patient population. The ASCO Annual Meeting constitutes an excellent opportunity to galvanize geriatric oncology research and present the latest data aiming to improve the care of older patients with cancer. In this column, we will review select research updates from the 2019 ASCO Annual Meeting and discuss their use in clinical care through a case discussion.
Mr. S, an 85-year-old man, presented with an early-stage, resectable, pancreatic cancer. He had a medical history of hypertension and benign prostatic hyperplasia. A geriatric assessment detected a slow gait and a history of falls. When asked about his goals of care, Mr. S said he wanted to live longer, even if that meant a decreased quality of life.
Multiagent Chemotherapy Regimens: Are Older Patients Appropriate Candidates?
Surgical resection is the first-line treatment of early-stage pancreatic cancer, but recent data are challenging this standard based on a total neoadjuvant treatment approach.2 However, it is not clear whether older patients will be appropriate candidates for this approach, as multiagent chemotherapy regimens are associated with increased toxicity.
At the ASCO meeting, the Spanish GESTA group presented a multicenter study that aimed to analyze predictive factors of grade 3 to 5 toxicity in patients aged 70 years or older treated with chemotherapy.3 All patients received a geriatric assessment at baseline, but none of the geriatric variables were found to be predictive of treatment-related high-grade adverse events. On multivariate analysis, just two factors were statistically significant for increased risk of grade 3 to 5 chemotherapy toxicity: chemotherapy dose (upfront standard vs reduced dosing) and creatinine clearance (below vs above 40 mL/min). It is important when interpreting these results to underline the high rate of patients who were started on a reduced chemotherapy dose (54%).
Guest Editor
Stuart M. Lichtman, MD, FASCO
Geriatrics for the Oncologist is guest edited by Stuart M. Lichtman, MD, FASCO, and developed in collaboration with the International Society of Geriatric Oncology (SIOG). Dr. -Lichtman is an Attending Physician at Memorial Sloan Kettering Cancer Center, Commack, New York, and Professor of Medicine at Weill Cornell Medical College, New York. He is also Past President of SIOG. For more information about geriatric oncology, visit www.siog.org and the ASCO Geriatric Oncology website (www.asco.org/practice-guidelines/cancer-care-initiatives/geriatric--oncology/geriatric-oncology-resources).
Although treating physicians were blinded to the results of the geriatric assessment, it is possible that many of them did consider geriatric variables when planning their treatment strategy. A reflection of this “geriatricized” approach to care in this patient population can be seen in the overall low rate of high-grade toxicity in this study (33.5%; 19% hematologic and 28% nonhematologic) compared with the rates reported in the Cancer and Aging Research Group (CARG) tool analysis (53%; 26% hematologic and 43% nonhematologic).4
The study authors found that the CARG chemotherapy toxicity risk prediction tool, a validated simple online calculator (http://www.mycarg.org/Chemo_Toxicity_Calculator), did not accurately predict high-grade toxicity for patients included in their study. This outcome might be explained by differences in methodology or patients’ baseline characteristics. For example, 55% of patients in the GESTA analysis had gastrointestinal cancer compared with 27% in the CARG study. In addition, an American patient population formed the basis of the CARG tool analysis, and therefore it might not apply to patients outside the United States. This nongeneralizability of the CARG tool was similarly suggested in a recent Australian analysis.5
The CARG chemotherapy toxicity risk prediction tool estimated Mr. S’s risk of grade 3 or 4 adverse events to be high at 78% if he were treated with standard-dose combination therapy.4 When evaluating an older patient, it is important also to consider the risk of low-grade adverse events, as they could lead to cumulative toxicity that may impact their quality of life and independence. In the case of Mr. S, this cumulative toxicity could hinder the plan to ultimately proceed with surgical resection and complicate his postoperative recovery.
Predicting Clinically Relevant Toxicity: Scope of CARG Tool
A multicenter observational cohort study data presented at the ASCO meeting aimed to evaluate the ability of the CARG tool to predict the risk of clinically relevant grade 2 as well as grade 3 to 5 toxicity in older patients with metastatic, castration-resistant prostate cancer treated with chemotherapy and androgen receptor–targeted agents.6 The study authors defined an adverse event as clinically relevant if it was associated with symptoms or led to a clinical action.
The CARG tool was predictive of clinically relevant grade 3 to 5 adverse events in patients treated with chemotherapy (29% in patients with a low CARG score, 57.7% in those with an intermediate score, and 90% in patients with a high score), but it did not predict clinically relevant grade 2 toxicity. Among patients treated with an androgen receptor–targeted agent, the CARG tool failed to predict either low- or high-grade clinically relevant toxicity.
These results emphasize the specific scope of the CARG tool: prediction of high-grade chemotherapy-related toxicity. The heterogeneity among patients, different treatment-specific toxicities, and various cancer-related morbidity indicate that a “cookie-cutter” approach to predict all toxicity related to any treatment in whatever patient population using a single tool will not be successful. Therefore, a comprehensive geriatric assessment remains the best tool to evaluate older patients with cancer.1,7
Comprehensive Geriatric Assessment: Moving Beyond CARG Tool
Information obtained from comprehensive geriatric assessment can help to predict morbidity and mortality associated with cancer or its treatment, and it can serve as the basis for interventions that aim to improve outcomes for older patients. For example, data from the Health ABC Study presented at the ASCO meeting showed that, among older adults with cancer, slow gait, a geriatric variable assessed during comprehensive geriatric assessment, was associated with increased mortality (hazard ratio [HR] = 1.44; 95% confidence interval [CI] = 1.05–1.98, P = .023) and major disability (HR = 1.70; 95% CI = 1.08–2.68, P = .021).8 Polypharmacy, another geriatric factor, was found to be associated with an increased risk of severe toxicity among older patients treated with a tyrosine kinase inhibitor in the PreToxE study.9 Geriatric variables were not included in this older adult multicohort analysis, but patients who were receiving at least three medications concomitantly with the tyrosine kinase inhibitor were found to be at increased risk for severe toxicity, defined as treatment-related death, persistent or significant disability, unexpected hospitalization, or discontinuation of treatment for more than 3 weeks.
Among hospitalized patients with advanced cancers, an activities of daily living (ADL) impairment was found to be associated with a higher symptom burden and worse health outcomes.10 Limited ADL were associated with longer hospital lengths of stay (P < .01), higher odds of death or readmission within 90 days (odds ratio = 2.26, P < .01), and higher mortality (HR = 1.73, P < .01).
Studies enrolling ‘physiologically’ older adults and designed with geriatric data will be essential to improve the care of older patients with cancer.— Rawad Elias, MD
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Abnormal cognitive status preceding treatment was shown to have prognostic impact in a prospective cohort of patients with advanced non–small cell lung cancer (NSCLC) aged ≥ 65 years.11 The study included 51 patients, with a median age of 73, who had various treatments for advanced NSCLC (37% immunotherapy, 29% targeted therapy, 18% chemoimmunotherapy, 16% chemotherapy). Among enrolled patients, 73% had an abnormal Montreal Cognitive Assessment score. In multivariable analysis, the Montreal Cognitive Assessment score was the only statistically significant prognostic factor associated with worse overall survival (HR = 1.15, 95% CI = 1.01–1.30).
Data from the ELCAPA-19 multicenter cohort study (n = 1,678 patients) showed that geriatric parameters are independently associated with cancer death.12 Geriatric factors associated with death at 6 months were dependency in ADL (adjusted subhazard ratio = 2.11, 95% CI = 1.68–2.64), impaired mobility based on a timed up and go test > 20 seconds (adjusted subhazard ratio = 1.40, 95% CI = 1.05–1.87) or inability to perform the timed up and go test (adjusted subhazard ratio = 2.41, 95% CI = 1.67–3.48), and comorbidities (total Cumulative Index Rating Scale-Geriatric score ≥ 13; adjusted subhazard ratio = 1.59, 95% CI = 1.23–2.06). At 3 years, geriatric parameters associated with death were limited ADL (adjusted subhazard ratio = 1.60, 95% CI = 1.34–1.91), timed up and go test > 20 seconds (adjusted subhazard ratio = 1.28, 95% CI = 1.04–1.59) or inability to perform the timed up and go test (adjusted subhazard ratio = 2.02,95% CI = 1.47–2.79), and cognitive impairment (adjusted subhazard ratio = 1.23, 95% CI = 1.01–1.50).
Factors predicting 1-year overall survival in older patients with cancer were evaluated in two large French cohorts.13 Patients in both cohorts had received a geriatric assessment; the ELCAPA study cohort (n = 2,012) was used for development, and the ONCODAGE study cohort (n = 1,397) served as a validation set. Using machine learning, the authors developed a decision tree that identified complex combinations between oncologic and geriatric features. The most discriminative variable was found to be a low score (< 10 vs ≥ 10) on the G8 geriatric frailty screening tool.
Although neoadjuvant chemotherapy might play a role in early pancreatic cancer, the plan for Mr. S was to proceed with upfront surgical resection. This decision was based on his high risk of grade 3 or 4 treatment-related toxicity (78% based on the CARG tool) and the potential effect of cumulative low-grade toxicity that could complicate the plan for surgical resection. However, it was essential to consider Mr. S’s risk of “surgical toxicity,” as older adults are at increased risk for functional decline and loss of independence in the postoperative setting.14 An evaluation of geriatric factors can help predict the surgical risk, facilitate the goals-of-care conversation, and establish interventions that can improve outcomes.
Assessing Quality of Life and Functional Recovery
An early analysis from the GOSAFE study was presented at the ASCO meeting.15 It aimed to evaluate quality of life and functional recovery in older adults undergoing cancer surgery. At 3 months after surgery, 15.6% of patients had an improvement in and 6.3% had a decline in quality of life. For 78.1% of the patients, there was no change in quality of life (67% with good quality of life at baseline, and 11.1% with poor quality of life). The most improvement in quality-of-life domains in the postoperative setting was seen in pain/discomfort (25.3% vs 40.1% prior to surgery) and anxiety/depression (26.1% vs 36.3% prior to surgery). At 90 days after surgery, 31% of patients experienced a functional decline, whereas while 69% had either a complete (29%) or partial (49%) functional recovery.
Older patients included in this analysis were mostly fit based on a composite measure of activities of ADL, the timed up and go test, and MiniCog (screening test for cognitive impairment in older adults); 8.2% were limited in their activities of daily living, 6.2% had a time up and go test score > 20 seconds, and 21.1% had an abnormal MiniCog. Therefore, although GOSAFE showed that cancer surgery is safe in fit older patients, it is still a concern for those who are frail or pre-frail. In fact, frail patients included in the GOSAFE study had higher rates of 90-day mortality (22.2% vs 4.2%) and morbidity (71% vs 46.3%), compared with those who were fit.
The higher mortality rate for frail patients undergoing cancer surgery was similarly reported in another presentation at the ASCO meeting. A fitness scale (FS4) that includes three geriatric variables (Karnofsky performance scale, ability to walk outside, ability to perform housekeeping) and preoperative albumin level was found to be predictive of 6-month postoperative mortality.16 These results were from a retrospective review of a prospective cohort of patients aged ≥ 75 years who had cancer surgery. Based on the FS4 score, the majority of the 1,270 patients included in this analysis were fit (61.4%), 25.7% were vulnerable, and 11.9% were frail. The 6-month mortality rate was 4.7%, 12.5%, and 21.2% for fit, vulnerable, and frail patients, respectively. Based on multivariate analysis, 6-month mortality odds were higher in frail (odds ratio = 4.58, P = .004) and vulnerable patients (odds ratio = 2.63, P = .004) vs fit patients.
Geriatric Co-management
Geriatric co-management may improve the outcomes of older adults with a surgical cancer, based on an analysis of 1,892 patients that was presented at the ASCO meeting.17 This retrospective analysis of a prospective cohort compared patients with standard surgical management (n = 872) vs those who had geriatric co-management during the perioperative period (n = 1,020). The 90-day postoperative mortality was 10.5% with surgery management and 3.5% with geriatric co-management. On multivariate analysis, geriatric co-management was associated with a 57% reduction in the risk of 90-day postoperative mortality following cancer surgery (odds ratio = 0.43; 95% CI = 0.28–0.67, P = .0002). Patients who received geriatric co-management were more likely to receive physical therapy (80% vs 64%) and occupational therapy (38% vs 25%) during the postoperative period compared with those managed by surgery.
A smaller analysis investigated the impact of a geriatric intervention in older adults with newly diagnosed incurable gastrointestinal or lung cancer.18 Patients were assigned to receive either usual care or two visits with a geriatrician. Among patients who received the geriatric intervention (n = 30), 62.5% found the geriatric clinician visits helpful, 12.5% did not think the visits helped, and 25% were not sure. The patients who received geriatric intervention had, in comparison to those who received usual care, less decrement in quality-of-life scores, greater reduction in the number of moderate/severe symptoms, and more improvement in -communication.
Mr. S’s treatment plan consisted of upfront surgical resection followed by adjuvant chemotherapy. This strategy was based on (1) increased risk of toxicity with neoadjuvant chemotherapy, which could jeopardize plans for surgery; (2) the fact that the patient was fit, which indicated he is a candidate for surgery; and (3) and his goals of care. Mr. S was referred to physical therapy prior to surgery, as the comprehensive geriatric assessment identified slow gait and a history of falls. He then proceeded with surgical resection, from which he recovered and then proceeded to receive adjuvant chemotherapy.
Older Patients in Clinical Trials
Unfortunately, despite multiple efforts, limited data are available to guide the management of older patients with cancer, who have been underrepresented in clinical trials. Data presented at the ASCO meeting showed that among 302 randomized therapeutic trials, the median age was 6.23 years younger than the population median age (95% CI = –5.55 to –6.91 years, P < .001).19 Moreover, trials with industry sponsorship had significantly younger trial patient populations compared with non–industry-sponsored trials (mean difference from the population –6.57 vs –4.48 years, P = .02). Studies enrolling “physiologically” older adults and designed with geriatric data will be essential to improve the care of older patients with cancer.
A great example from the ASCO meeting is the GO2 phase III trial, which showed that lower-dose chemotherapy can be safely used in frail and older patients with advanced gastroesophageal cancer without compromising efficacy.20 This study included 512 patients with a median age of 76 years; 58% were severely frail, and 31% had an Eastern Cooperative Oncology Group performance status of at least 2. All patients enrolled on this trial received a geriatric assessment at baseline, and investigators are working on identifying a personalized strategy for personalized dose selection based on comprehensive geriatric assessment.
The ASCO meeting was an opportunity for many investigators to showcase their geriatric oncology research. Data presented, as discussed in this article, is relevant to everyday clinical practice and can be used to improve the care of real-life older patients with cancer.
DISCLOSURE: Dr. Elias reported no conflicts of interest.
REFERENCES
1. Soto-Perez-de-Celis E, Li D, Yuan Y, et al: Functional vs chronological age: Geriatric assessments to guide decision making in older patients with cancer. Lancet Oncol 19:e305-e316, 2018.
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3. Batlle JF, Basterretxea L, Torregrosa MD, et al: Predictive factors of grade 3-5 toxicity in older patients with cancer treated with chemotherapy: A prospective multicenter study. 2019 ASCO Annual Meeting. Abstract 11509. Presented June 3, 2019.
4. Hurria A, Togawa K, Mohile SG, et al: Predicting chemotherapy toxicity in older adults with cancer: A prospective multicenter study. J Clin Oncol 29:3457-3465, 2011.
5. Moth EB, Kiely BE, Stefanic N, et al: Predicting chemotherapy toxicity in older adults: Comparing the predictive value of the CARG toxicity score with oncologists’ estimates of toxicity based on clinical judgement. J Geriatr Oncol 10:202-209, 2019.
6. Alibhai SMH, Breunis H, Gregg RW, et al: Validating the Cancer and Aging Research Group (CARG) toxicity prediction tool in older men receiving chemotherapy for metastatic castration-resistant prostate cancer (mCRPC) and extending it to androgen receptor targeted agents. 2019 ASCO Annual Meeting. Abstract 11510. Presented June 3, 2019.
7. Mohile SG, Dale W, Somerfield MR, et al: Practical assessment and management of vulnerabilities in older patients receiving chemotherapy: ASCO Guideline for Geriatric Oncology. J Clin Oncol 36:2326-2347, 2018.
8. Williams GR, Chen Y, Kenzik K, et al: Accelerated sarcopenia and outcomes in older adults with cancer: The Health ABC Study. 2019 ASCO Annual Meeting. Abstract 11526. Presented June 3, 2019.
9. Lebreton C, Cantarel C, Toulza E, et al: Predicting severe toxicity of targeted therapies in elderly patients with cancer (PreToxE): A multicenter, prospective, and retrospective study. 2019 ASCO Annual Meeting. Abstract 11550. Presented June 3, 2019.
10. Lage DE, El-Jawahri A, Fuh C-X, et al: Functional impairment on admission and associated symptom burden and health outcomes among hospitalized patients with advanced cancer. 2019 ASCO Annual Meeting. Abstract 11554. Presented June 3, 2019.
11. Wong ML, Miaskowski C, Smith AK, et al: Prognostic factors among older adults with advanced non-small cell lung cancer: A multisite cohort study. 2019 ASCO Annual Meeting. Abstract 11540. Presented June 3, 2019.
12. Assouan D, Paillaud E, Caillet P, et al: Cancer-specific mortality and competing causes of death in older adults: A prospective, multicenter cohort study (ELCAPA-19). 2019 ASCO Annual Meeting. Abstract 11547. Presented June 3, 2019.
13. Audureau E, Soubeyran P-L, Martinez-Tapia C, et al: Using machine learning to predict mortality in older patients with cancer: Decision tree and random forest analyses from the ELCAPA and ONCODAGE prospective cohorts. 2019 ASCO Annual Meeting. Abstract 11516. Presented June 1, 2019.
14. McDonald SR, Heflin MT, Whitson HE, et al: Association of integrated care coordination with postsurgical outcomes in high-risk older adults: The Perioperative Optimization of Senior Health (POSH) Initiative. JAMA Surg 153:454-462, 2018.
15. Montroni I, Ugolini G, Spinelli A, et al: Outcomes that matter to patients: The Geriatric Oncology Surgical Assessment and Functional Recovery After Surgery (GOSAFE) study—Analysis of 471 patients. 2019 ASCO Annual Meeting. Abstract 11511. Presented June 3, 2019.
16. Shahrokni A, Sarraf S, Downey RJ, et al: Fitness scale-4 item (FS4) to predict six-month postoperative mortality of cancer patients aged 75. 2019 ASCO Annual Meeting. Abstract 11542. Presented June 3, 2019.
17. Shahrokni A, Tin A, Sarraf S, et al: Reduced 90-day postoperative mortality through geriatric comanagement after cancer surgery. 2019 ASCO Annual Meeting. Abstract 11512. Presented June 3, 2019.
18. Kay P, El-Jawahri A, Fuh C-X, et al: Pilot randomized trial of a transdisciplinary geriatric intervention for older adults with cancer. 2019 ASCO Annual Meeting. Abstract 11549. Presented June 3, 2019.
19. Ludmir EB, Mainwaring W, Miller AB, et al: Age disparities among cancer clinical trial participants: The role of industry sponsorship. 2019 ASCO Annual Meeting. Abstract 11527. Presented June 3, 2019.
20. Hall PS, Swinson D, Waters JS, et al: Optimizing chemotherapy for frail and elderly patients with advanced gastroesophageal cancer: The GO2 phase III trial. 2019 ASCO Annual Meeting. Abstract 4006. Presented June 2, 2019.
