Modified CARG score using data from the electronic health record to predict chemotherapy toxicity in older adults.

Authors

null

Jasmine L Martin

Geisinger Health Systems, Danville, PA

Jasmine L Martin , Kathie Wu , Mudit Gupta , Alicia M Johns , Christian S. Adonizio

Organizations

Geisinger Health Systems, Danville, PA, Geisinger Medical Center, Danville, PA, Geisinger Health System, Danville, PA, Geisinger Cancer Institute, Danville, PA

Research Funding

Other

Background: Older adults starting chemotherapy are at greater risk of toxicity compared with younger patients. Additional tools are needed to aid in management decisions for this population. The Cancer and Aging Research Group (CARG) chemotherapy toxicity calculator is one such tool, which stratifies older adults into high, intermediate, or low risk for chemotherapy toxicity (Hurria, A., Mohile, S., Tew, W. P., & et al. (2016). Validation of a prediction tool for chemotherapy toxicity in older adults with cancer. Journal of Clinical Oncology, 34(20), 2366–2371. https://doi.org/10.1200/jco.2015.65.4327). This tool relies on a face-to-face encounter to ask questions, e.g. “How is your hearing?” or “Can you take your own medicines?” in addition to lab values such as hemoglobin and creatinine clearance. We modified the CARG chemo toxicity calculator to include data points which could be pulled from the electronic health record (EHR) without the need for a face-to-face encounter to assess for an association with emergency department (ED) visits and hospital admissions. Methods: Retrospective data analysis was conducted using the EHR of patients over age 65 diagnosed with a solid tumor from 1/1/2019 to 12/31/2020 who started chemotherapy. A modified CARG score was calculated using age, cancer type, number of drugs, hemoglobin, creatinine clearance, and falls within the past 6 months. The remaining items needed to calculate the complete CARG score were excluded since they were not accessible in the EHR. We assessed ED visits leading to admission, ED visits leading to discharge, direct admissions, and the total of all 3 visit types for all patients. Results: A modified CARG score was calculated for 763 patients. Multiple models were evaluated and negative binomial distribution was found to be the best fitted for our data. For every one unit increase in our calculated score the number of ED visits which lead to hospital admission increased by 6% (p-value = 0.0156). Additionally, there was a 5% increase in combined ED visits, ED visits leading to admission, and direct admissions for every one unit increase in risk score (p-value = 0.0063). ED visits that did not lead to admission were found not to have an association with the risk score (p-value= 0.1263). (Table) Conclusions: A modified CARG score using data obtained from patients’ EHR had a statistically significant association with increased ER visits that resulted in hospital admission and with the total of ED visits leading to admission, ED visits leading to discharge, direct admissions. Using these outcomes as a surrogate for toxicity, we deduce that a simple tool could be used to predict chemotherapy toxicity in older adults.

Outcomes
Incidence Rate Ratio for Risk Score (95% CI)
p value
ER Visits
1.04 (0.99, 1.10)
0.1263
ER Visits that Lead to Admission
1.06 (1.01, 1.11)
0.0156
Direct Admissions
1.05 (0.99, 1.12)
0.0899
Total Visits
1.05 (1.01, 1.09)
0.0063

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Abstract Details

Meeting

2022 ASCO Annual Meeting

Session Type

Poster Session

Session Title

Symptoms and Survivorship

Track

Symptom Science and Palliative Care

Sub Track

Geriatric Models of Care

Citation

J Clin Oncol 40, 2022 (suppl 16; abstr 12038)

DOI

10.1200/JCO.2022.40.16_suppl.12038

Abstract #

12038

Poster Bd #

284

Abstract Disclosures

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