Effects of a Geriatric Assessment Intervention on Patient-Reported Symptomatic Toxicity in Older Adults With Advanced Cancer

Health-related quality of life with comprehensive geriatric assessment guided care versus usual care in older adults with cancer: A systematic review and meta-analysis of randomized trials

BACKGROUND

To evaluate if comprehensive geriatric assessment (CGA)-guided care improves health-related quality of life (HRQL) in older adults with cancer compared to usual care.

METHODS

Relevant randomized controlled trials (RCTs) were identified through biomedical databases. Meta-analyses using DerSimonian-Laird model summarized the difference in the mean change of HRQL scores from baseline across various time points, with evidence certainty assessed by the GRADE tool. Logistic regression via generalized estimating equations analyzed predictors of HRQL improvement.

RESULTS

Potential improvement in the global HRQL score by CGA-guided care at 3 months (Cohen's d 0.27, 95 % CI -0.03-0.58, moderate certainty), could not be excluded. Larger RCTs or those mandating CGA before initiating anti-cancer treatment were predictors of improved HRQL.

CONCLUSION

The effects of CGA-guided care on HRQL were variable. Larger RCTs and those mandating pre-treatment CGA tended to report improved HRQL.

Geriatric Oncology: A 5-Year Strategic Plan

The increasing rate of the older adult population across the world over the next 20 years along with significant developments in the treatment of oncology will require a more granular understanding of the older adult population with cancer. The ASCO Geriatric Oncology Community of Practice (COP) herein provides an outline for the field along three fundamental pillars: education, research, and implementation, inspired by ASCO's 5-Year Strategic Plan. Fundamental to improving the understanding of geriatric oncology is research that intentionally includes older adults with clinically meaningful data supported by grants across all career stages. The increased knowledge base that is developed should be conveyed among health care providers through core competencies for trainees and continuing education for practicing oncologists. ASCO's infrastructure can serve as a resource for fellowship programs interested in acquiring geriatric oncology content and provide recommendations on developing training pathways for fellows interested in pursuing formalized training in geriatrics. Incorporating geriatric oncology into everyday practice is challenging as each clinical setting has unique operational workflows with barriers that limit implementation of valuable geriatric tools such as Geriatric Assessment. Partnerships among experts in quality improvement from the ASCO Geriatric Oncology COP, the Cancer and Aging Research Group, and ASCO's Quality Training Program can provide one such venue for implementation of geriatric oncology through a structured support mechanism. The field of geriatric oncology must continue to find innovative strategies using existing resources and partnerships to address the pressing needs of the older adult population with cancer to improve patient outcomes.

Care Delivery Interventions for Individuals with Cancer: A Literature Review and Focus on Gastrointestinal Malignancies

BACKGROUND

Gastrointestinal malignancies represent a particularly challenging condition, often requiring a multidisciplinary approach to management in order to meet the unique needs of these individuals and their caregivers.

PURPOSE

In this literature review, we sought to describe care delivery interventions that strive to improve the quality of life and care for patients with a focus on gastrointestinal malignancies.

CONCLUSION

We highlight patient-centered care delivery interventions, including patient-reported outcomes, hospital-at-home interventions, and other models of care for individuals with cancer. By demonstrating the relevance and utility of these different care models for patients with gastrointestinal malignancies, we hope to highlight the importance of developing and testing new interventions to address the unique needs of this population.

Detailed Clinical Characteristics, Interventions, and Long-Term Outcomes of Patients With Gastric Cancer Who Received the Best Supportive Care Without Any Anticancer Treatment

Background

Due to the lack of studies, the long-term prognoses of unfit patients with gastric cancer (GC) who did not receive any aggressive cancer treatment (best supportive care [BSC] cases) remain unclear, especially for those with potentially curable GC. We conducted this observational study to capture the real-world data of characteristics and outcomes for BSC cases.

Method

Consecutive clinical records of patients with GC diagnosed at Steel Memorial Muroran Hospital from January 2017 to December 2021 were analyzed.

Result

Of 481 patients diagnosed with GC, 91 (18.9%) were BSC cases. The median overall survival (OS) was 12.4, 8.3, and 2.5 months for clinical stage (cStage) I, II-III, and IV, respectively. Patients with potentially curable GC (cStage I-III) had significantly longer OS than those with incurable disease (cStage IV), with a hazard ratio for death of 0.29 (95% confidence interval: 0.18-0.47).

Conclusion

Our report provides useful information for decision-making for unfit patients with GC in daily clinical practice.

Examining provider perceptions and practices for comprehensive geriatric assessment among cancer survivors: a qualitative study with an implementation science focus

Introduction: Cancer rates increase with age, and older cancer survivors have unique medical care needs, making assessment of health status and identification of appropriate supportive resources key to delivery of optimal cancer care. Comprehensive geriatric assessments (CGAs) help determine an older person's functional capabilities as cancer care providers plan treatment and follow-up care. Despite its proven utility, research on implementation of CGA is lacking. Methods: Guided by a qualitative description approach and through interviews with primary care providers and oncologists, our goal was to better understand barriers and facilitators of CGA use and identify training and support needs for implementation. Participants were identified through Cancer Prevention and Control Research Network partner listservs and a national cancer and aging organization. Potential interviewees, contacted via email, were provided with a description of the study purpose. Eight semi-structured interviews were conducted via Zoom, recorded, and transcribed verbatim by a professional transcription service. The interview guide explored providers' knowledge and use of CGAs. For codebook development, three representative transcripts were independently reviewed and coded by four team members. The interpretive process involved reflecting, transcribing, coding, and searching for and identifying themes. Results: Providers shared that, while it would be ideal to administer CGAs with all new patients, they were not always able to do this. Instead, they used brief screening tools or portions of CGAs, or both. There was variability in how CGA domains were assessed; however, all considered CGAs useful and they communicated with patients about their benefits. Identified facilitators of implementation included having clinic champions, an interdisciplinary care team to assist with implementation and referrals for intervention, and institutional resources and buy-in. Barriers noted included limited staff capacity and competing demands on time, provider inexperience, and misaligned institutional priorities. Discussion: Findings can guide solutions for improving the broader and more systematic use of CGAs in the care of older cancer patients. Uptake of processes like CGA to better identify those at risk of poor outcomes and intervening early to modify treatments are critical to maximize the health of the growing population of older cancer survivors living through and beyond their disease.

Practical Assessment and Management of Vulnerabilities in Older Patients Receiving Systemic Cancer Therapy: ASCO Guideline Update

PURPOSE

To update the ASCO guideline (2018) on the practical assessment and management of age-associated vulnerabilities in older patients undergoing systemic cancer therapy.

METHODS

An Expert Panel conducted a systematic review to identify relevant randomized clinical trials (RCTs), systematic reviews, and meta-analyses from January 2016 to December 2022.

RESULTS

A total of 26 publications met eligibility criteria and form the evidentiary basis for the update.

RECOMMENDATIONS

The Expert Panel reiterates its overarching recommendation from the prior guideline that geriatric assessment (GA), including all essential domains, should be used to identify vulnerabilities or impairments that are not routinely captured in oncology assessments for all patients over 65 years old with cancer. Based on recently published RCTs demonstrating significantly improved clinical outcomes, all older adults with cancer (65+ years old) receiving systemic therapy with GA-identified deficits should have GA-guided management (GAM) included in their care plan. GAM includes using GA findings to inform cancer treatment decision-making as well as to address impairments through appropriate interventions, counseling, and/or referrals. A GA should include high priority aging-related domains known to be associated with outcomes in older adults with cancer: physical and cognitive function, emotional health, comorbid conditions, polypharmacy, nutrition, and social support. Clinical adaptation of the GA based on patient population, resources, and time is appropriate.The Panel recommends the Practical Geriatric Assessment as one option for this purpose (https://old-prod.asco.org/sites/new-www.asco.org/files/content-files/practice-patients/documents/2023-PGA-Final.pdf; https://youtu.be/jnaQIjOz2Dw; https://youtu.be/nZXtwaGh0Z0).Additional information is available at www.asco.org/supportive-care-guidelines.

Predictors and effects of toxicity experienced by older adults with cancer receiving systemic therapy in a randomized clinical trial of geriatric assessment

INTRODUCTION

Older adults represent a large segment of the oncology population, however, they remain underrepresented in clinical research. Treatment of older adults is often extrapolated using data from younger and fitter patients, which may not be appropriate. Furthermore the implications of toxicity from treatment can be greater for this population. Predicting toxicity from treatment and its effect on quality of life and functional status for older adults therefore is important.

MATERIALS AND METHODS

We analyzed data from a clinical trial of geriatric assessment and management for Canadian elders with cancer (5C study). We assessed whether the baseline Cancer and Aging Research Group (CARG) toxicity score, G8 score, and Eastern Cooperative Oncology Group (ECOG) performance predicted grade 3-5 toxicity using logistic regression and pattern mixture models. We also assessed the impact of toxicity on quality of life and functional decline. Patients were followed for six months.

RESULTS

Three hundred sixteen patients were included. Mean age was 76 years old and 40% of patients were female. One hundred nineteen patients (38%) experienced at least one grade 3-5 toxicity. Neither the CARG toxicity score, G8, or ECOG were predictive of grade 3-5 toxicity. Patients who experienced grade 3-5 toxicity were more likely to have functional impairments over time (odds ratio 3.71, p = 0.03). However, they maintained their quality of life.

DISCUSSION

In this secondary analysis of a randomized controlled trial of geriatric assessment and management we did not find any predictors of grade 3-5 toxicity. Patients who did experience toxicity were more likely to report functional decline over time. Older adults who do experience treatment related toxicity may benefit from increased supports.

CLINICAL TRIAL INFORMATION

NCT0315467.

Systematic symptom screening in patients with advanced cancer treated in certified oncology centers: results of the prospective multicenter German KeSBa project

PURPOSE

Guidelines recommend a structured symptom screening (SC) for especially advanced cancer patients (CPs). The aim of this multicenter German prospective quality assurance project KeSBa (Kennzahl Symptom- und Belastungserfassung) was to gain knowledge on SC procedures in Oncology Centers (OCs) for advanced cancer patients and a first impression on the consequences of SC.

METHODS

The KeSBa project consisted of three phases: pilot, 3 months screening and feedback phase. Participating OCs decided to use either the Minimal Documentation System (MIDOS) or the Integrated Palliative care Outcome Scale (IPOS) and defined the cutoff values for positive screening results.

RESULTS

Out of 172 certified German OCs, 40 (23%) participated in the KeSBa pilot phase, 29 (16.8%) in the 3 months screening phase using MIDOS (n = 18, 58.6%) or IPOS (n = 11, 41.3%) and in the feedback round. 25/29 performed paper-based screening (86.2%). 2.963 CPs were screened. Results were documented for 1255 (42.2%, SC +) positive and 874 (29.5%, SC-) negative screenings depending on the center´s schedules: 452 SC + CPs (28.4%) and 42 SC- CPs (2.6%) had contact to specialized palliative care or other supportive specialist teams afterwards, 458 SC + CPs (28.8%) and 605 SC- CPs (38.1%) remained in standard oncology care. In the feedback round missing resources (personal and IT) and improved communication were mentioned most often.

CONCLUSION

Routine SC is feasible in advanced CPs treated in OCs but associated with considerable workload. In 42.2% of CPs SC was classified as positive, indicating the need of further diagnostics or professional judgment. SC requires staff and IT resources.

An Unsupervised Machine Learning Approach to Evaluating the Association of Symptom Clusters With Adverse Outcomes Among Older Adults With Advanced Cancer: A Secondary Analysis of a Randomized Clinical Trial

Importance

Older adults with advanced cancer who have high pretreatment symptom severity often experience adverse events during cancer treatments. Unsupervised machine learning may help stratify patients into different risk groups.

Objective

To evaluate whether clusters identified from baseline patient-reported symptom severity were associated with adverse outcomes.

Design, Setting, and Participants

This secondary analysis of the Geriatric Assessment Intervention for Reducing Toxicity in Older Patients With Advanced Cancer (GAP70+) Trial (2014-2019) included patients who completed the National Cancer Institute Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) before starting a new cancer treatment regimen and received care at community oncology sites across the United States. An unsupervised machine learning algorithm (k-means with Euclidean distance) clustered patients based on similarities of baseline symptom severities. Clustering variables included severity items of 24 PRO-CTCAE symptoms (range, 0-4; corresponding to none, mild, moderate, severe, and very severe). Total severity score was calculated as the sum of 24 items (range, 0-96). Whether the clusters were associated with unplanned hospitalization, death, and toxic effects was then examined. Analyses were conducted in January and February 2022.

Exposures

Symptom severity.

Main Outcomes and Measures

Unplanned hospitalization over 3 months (primary), all-cause mortality over 1 year, and any clinician-rated grade 3 to 5 toxic effect over 3 months.

Results

Of 718 enrolled patients, 706 completed baseline PRO-CTCAE and were included (mean [SD] age, 77.2 [5.5] years, 401 [56.8%] male patients; 51 [7.2%] Black and 619 [87.8%] non-Hispanic White patients; 245 [34.7%] with gastrointestinal cancer; 175 [24.8%] with lung cancer; mean [SD] impaired Geriatric Assessment domains, 4.5 [1.6]). The algorithm classified 310 (43.9%), 295 (41.8%), and 101 (14.3%) into low-, medium-, and high-severity clusters (within-cluster mean [SD] severity scores: low, 6.3 [3.4]; moderate, 16.6 [4.3]; high, 29.8 [7.8]; P < .001). Controlling for sociodemographic variables, clinical factors, study group, and practice site, compared with patients in the low-severity cluster, those in the moderate-severity cluster were more likely to experience hospitalization (risk ratio, 1.36; 95% CI, 1.01-1.84; P = .046). Moderate- and high-severity clusters were associated with a higher risk of death (moderate: hazard ratio, 1.31; 95% CI, 1.01-1.69; P = .04; high: hazard ratio, 2.00; 95% CI, 1.43-2.78; P < .001), but not toxic effects.

Conclusions and Relevance

In this study, unsupervised machine learning partitioned patients into distinct symptom severity clusters; patients with higher pretreatment severity were more likely to experience hospitalization and death.

Trial Registration

ClinicalTrials.gov Identifier: NCT02054741.