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Multicenter Study
. 2025 Oct 30;54(11):afaf324.
doi: 10.1093/ageing/afaf324.

Development and validation of ACTTOP: a prediction model for severe anticancer treatment toxicities in older patients with solid malignancy

Wing Lok Chan  1 , Holly Li-Yu Hou  1 , Horace Chuek-Wai Choi  2 , Siu-Long Thomas Yik  3 , Ho-Fai Matthew Cheng  4 , Wai-Lam Tsoi  5 , Ka-Man Cheung  6 , Roger Ngan  7 , Ping-Chit Naomi Tse  3 , Sally Ka-Wing Lau  3 , Wai-Kwan Steven Siu  4 , A-On Lam  1 , Chi-Leung Chiang  1 , Aya El-Helali  1 , Rachel Yuk-Ki Chu  2 , Victor Ho-Fun Lee  1 , Thomas Yau  8 , Kwok-Keung Yuen  4 , Dora Kwong  1
Affiliations
Multicenter Study

Development and validation of ACTTOP: a prediction model for severe anticancer treatment toxicities in older patients with solid malignancy

Wing Lok Chan et al. Age Ageing. .

Abstract

Background: Older adults with cancer are at increased risk of severe treatment-related toxicity (TRT). Existing chemotherapy toxicity prediction models have limitations. This study aimed to develop and validate a tool for predicting severe TRT in older patients receiving systemic anticancer therapy.

Methods: Patients aged ≥65 scheduled for systemic therapy, including chemotherapy, targeted therapy and/or immunotherapy, were recruited from three oncology centres in Hong Kong between March 2019 and June 2023. Pretreatment assessments captured clinical, tumour/treatment, laboratory and geriatric variables. Patients were monitored during treatment or for six months for grade 3-5 TRT (NCI CTCAE v5.0). Predictive factors were identified using multivariable logistic regression, and a weighted scoring system, Anti-Cancer Treatment Toxicity in Older Patients (ACTTOP), was developed. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and goodness-of-fit statistics, and compared with the CARG model.

Results: Among 700 patients (first 400 for development; last 300 for validation; median age 71), 413 (59.0%) developed grade 3-5 TRT. Ten predictors were identified. ACTTOP stratified patients into low (0-3 points: 36.0% development, 40.5% validation), intermediate (4-8 points: 63.9%, 52.5%) and high-risk (9-26 points: 86.3%, 76.6%) groups. The AUC was 0.72 (95% CI: 0.67-0.77) in development and 0.77 (95% CI: 0.72-0.82) in validation. Risk groups were significantly associated with premature termination, emergency room visits, toxicity-related hospitalisations and early mortality (P < .001). ACTTOP demonstrated superior predictive capability over the CARG score (AUC 0.61).

Conclusion: ACTTOP is a validated prediction model that enables individualised risk assessment for severe toxicity in older cancer patients receiving systemic therapy.

Keywords: chemotherapy; geriatric oncology; immunotherapy; older people; prediction model; toxicities.

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