Abstract 1884P
Background
Older cancer patients are at a higher risk of treatment-related toxicities (TRT) due to various reasons. Existing chemotherapy toxicity calculators have limitations. This study aimed to develop and validate a prediction tool for severe TRT in older cancer patients on systemic treatment.
Methods
Consecutive cancer patients aged ≥65 undergoing systemic anti-cancer treatment were recruited from three large oncology centers in Hong Kong (Queen Mary Hospital, Queen Elizabeth Hospital and Gleneagles Hospital) from March 2019 to May 2022. Pre-treatment assessments captured clinical, tumour/treatment, laboratory, and geriatric assessment variables. Patients were followed throughout treatment or 6 months for grade 3-5 TRT based on CTCAE version 5. Univariate and multivariable logistic regression identified predictive factors, and a weighted scoring system was used to develop the prediction model. Model performance was evaluated using area under the ROC curve (AUC) and goodness-of-fit statistics, with internal and external validation.
Results
Among the 500 patients (400 in development cohort, 100 in validation cohort) with median age 71, 304 (60.8%) developed grade 3-5 TRT. Ten independent predictors associated with TRT were identified. The predictive model categorized patients into low (0-3 points: incidence of TRT in development cohort: 35.3%, validation cohort: 29.0%), intermediate (4-8 points: 59.7% and 61.7%), and high-risk (9-26 points: 82.8% vs. 77.3%) groups. The AUC was 0.718 (95% CI: 0.667-0.769) in the development cohort and 0.717 (95% CI:0.616-0.818) in the validation cohort. Table: 1884P
Treatment-related toxicity risk model (TR-TRM)
Category | Variable | Score | |
1 | Treatment factor | No chemotherapy/ monotherapy Doublet or more chemotherapies | 0 3 |
2 | Current no use of immune checkpoint inhibitor Current use of immune checkpoint inhibitor | 0 2 | |
3 | No history of chemotherapy use Previous use of chemotherapy | 0 1 | |
4 | Patient factor | Self rated health status: Better or similar to same age Worse than same age | 0 1 |
5 | Geriatric variable | Clinical frailty scale 1-5 6-9 | 0 3 |
6 | Charles comorbidity index 0-7 8-10 ≥11 | 0 1 3 | |
7 | Laboratory result | Hemoglobin (g/dl) ≥10.0 ConclusionsThis study developed and validated a prediction tool for severe TRT in older cancer patients receiving systemic treatment. The tool incorporates patient and treatment characteristics, geriatric assessment variables, and laboratory results. It helps clinicians assess TRT risk and guide treatment decisions in this population. Clinical trial identificationEditorial acknowledgementLegal entity responsible for the studyThe authors. FundingMadam Tsoi Foundation for Geriatric Oncology Research. DisclosureAll authors have declared no conflicts of interest. Resources from the same session1832P - Physical condition is associated with quality of life in colorectal cancer survivors: Results from a Portuguese and Spanish cohort of patientsPresenter: Luisa Soares Miranda Session: Poster session 12 1833P - JUMP_START: Optimization of multiprofessional care for young patients with colorectal cancerPresenter: Kaiyu Xu Session: Poster session 12 1834P - Accuracy of recommendations by a conversational Artificial Intelligence (AI) cancer mentor application (app): A multi-disciplinary, multi-institutional evaluation reportPresenter: Talia Golan Session: Poster session 12 1835P - Multi-centre, randomised controlled trial of digital health cancer solution for cancer patients receiving chemotherapyPresenter: Agnieszka Michael Session: Poster session 12 1836P - Patient-reported health behaviors (PRHB) among 1850 patients enrolled in a remote patient monitoring (RPM) pathwayPresenter: Maria Alice Franzoi Session: Poster session 12 1837P - Assessing care complexity in remote patient monitoring (RPM): A cohort study of 2434 cancer patients across 50 sites in France and BelgiumPresenter: Capucine Baldini Session: Poster session 12 1838P - AI-based smart oncology follow-up system: Prospective application testing and enhancement of clinical efficacyPresenter: Chunwei Xu Session: Poster session 12 1839P - Dynamic reporting of treatment related symptoms via ePROs can reversely identify the type of underlying cancerPresenter: Andreas Trojan Session: Poster session 12 1840P - Ready for digital health? A national mirror survey exploring the perspectives of both patients and healthcare professionalsPresenter: Florian Scotté Session: Poster session 12 1841P - Feasibility of wrist-worn health-tracker data to predict the need for therapy modifications in patients with metastatic cancerPresenter: Anna Sophie Berghoff Session: Poster session 12 This site uses cookies. Some of these cookies are essential, while others help us improve your experience by providing insights into how the site is being used. For more detailed information on the cookies we use, please check our Privacy Policy.
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