Currently submitted to: JMIR Formative Research
Date Submitted: Nov 20, 2025
Open Peer Review Period: Nov 20, 2025 - Jan 15, 2026
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Efficacy of the ChulaCancer LINE Chatbot for Supportive Management of Chemotherapy Adverse Events: A Pilot Randomized Controlled Trial
ABSTRACT
Background:
Chemotherapy-related side effects are common, yet most are mild and manageable at home with appropriate supportive care. However, many patients find standard education overwhelming or insufficiently tailored to their symptoms. Smartphone-based chatbots offer accessible, personalized medical guidance that may reduce unnecessary hospital visits and improve quality of life (QoL). The ChulaCancer LINE Chatbot was developed as a Thai-language digital assistant to support patients receiving chemotherapy.
Objective:
To evaluate the feasibility and preliminary efficacy of the ChulaCancer LINE Chatbot for managing chemotherapy-related adverse events compared with usual care.
Methods:
This single-center, open-label, randomized controlled pilot trial was conducted at King Chulalongkorn Memorial Hospital from December 2024 to May 2025. Adults aged ≥18 years with early-stage breast or colorectal cancer scheduled for adjuvant or neoadjuvant chemotherapy (AC, TC, or CAPOX) and an ECOG performance status of 0–2 were randomized 1:1 to the Chatbot or Usual Care groups, stratified by cancer type. The chatbot was developed using the BOTNOI platform and integrated into the LINE messaging application. Educational content was adapted from existing hospital materials, and a closed-loop system ensured medical accuracy. Usual care included standard counseling, printed materials, and educational videos. The Chatbot group received proactive video content and interactive symptom-specific guidance. The primary outcome was the rate of additional hospital visits due to chemotherapy-related side effects within 12 weeks. Secondary outcomes included QoL changes measured by EORTC QLQ-C30 at baseline, week 6, and week 12, and incidence of grade ≥3 adverse events (CTCAE v5.0). Fisher’s exact test and linear mixed-effects models were used for analyses.
Results:
Forty patients were enrolled (20 per group). The median age was 54 years, 80% were female, and baseline characteristics were balanced. Across 12 weeks, 508 chatbot interactions were recorded; the most frequently accessed topics were cancer knowledge, nausea and vomiting, nutrition, chemotherapy information, and fever. Additional hospital visits occurred in 3 patients (15%) in the Chatbot group versus 7 (35%) with Usual Care (P=.24). Grade ≥3 adverse events occurred in 1 patient (5%) and 2 patients (10%), respectively (P=1.00). The Chatbot group showed a significant improvement in fatigue scores at week 12 (P=.016), with nonsignificant trends favoring the chatbot across other QoL domains.
Conclusions:
Use of a LINE-based chatbot is feasible and shows promising signals of benefit in supporting patients undergoing chemotherapy. Improvements in fatigue suggest that timely, personalized communication may enhance symptom management. Although limited by small sample size and short follow-up, this pilot study supports further evaluation of conversational agents in oncology, particularly in resource-limited settings.
Citation
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