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An observational study to understand how digital twin-based artificial intelligence can help predict side effects of chemotherapy and radiotherapy in head and neck cancer patients.

An observational study on digital twin AI approaches for predicting chemotherapy & radiotherapy induced toxicities in head and neck malignancies. - NIL

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2026/02/103823
Enrollment
326
Registered
2026-02-13
Start date
Unknown
Completion date
Unknown
Last updated
2026-03-02

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Health Condition 1: C148- Malignant neoplasm of overlappingsites of lip, oral cavity and pharynx

Interventions

Intervention1: Nil: Nil

Sponsors

Dr Cyril Sajan
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: 1. Adult age greater than or equal to 18 years. 2. Histologically confirmed squamous cell carcinoma of the oral cavity, oropharynx, hypopharynx, or larynx. 3. Scheduled for definitive or adjuvant concurrent chemoradiotherapy (cisplatin or carboplatin-based) 4. Availability of baseline clinical, laboratory, and imaging data. 5. ECOG performance status 0-2 6. Ability to provide written informed consent.

Exclusion criteria

Exclusion criteria: 1. Prior head and neck radiotherapy 2. Distant Metastasis (M1) Stage 3. Contraindications to cisplatin or Carboplatin (e.g. severe renal dysfunction, hearing impairment) 4. Incomplete imaging or laboratory data 5. Severer comorbidities precluding treatment completion.

Design outcomes

Primary

MeasureTime frame
To determine how accurately the digital twin based AI model predicts chemotherapy- and radiotherapy-induced toxicities in head and neck cancer patients when compared with observed CTCAE v5.0 toxicity outcomes. Timepoint: 1. Baseline (Pre-CRT) collection of demographics, labs, imaging 2. Weekly during CRT (Weeks 1-7) weekly toxicity assessment (mucositis, hematologic, renal, ototoxicity, dermatitis, nausea/vomiting) 3. End of CRT - final acute toxicity documentation 4. Up to 90 days pos-CRT - follow-up for acute/subacute toxicities—

Secondary

MeasureTime frame
1. Prediction of Late ToxicitiesTimepoint: Baseline, weekly during treatment, and 90 days post-treatment.;Comparison with conventional assessment methodsTimepoint: 1. After data collection completion (after weekly and 90 day toxicity data) 2. During model validation phase (Months 30 to 36 of study timeline);Correlation with patient reported outcomes (PROs) using EORTC QLQ-C30 and EORTC QLQ-H&N35Timepoint: Baseline (Pre-CRT) End of CRT 90 days post-CRT;Impact on Treatment Delivery (interruptions, delays, hospitalizations)Timepoint: Continuously tracked during CRT (Weeks 1 7) Assessed again at End of CRT Final review at 90-day follow-up ;Clinical Utility & Feasibility of Digital Twin ModelTimepoint: Model development phase (Months 24 33) Model validation phase (Months 30 36) Clinical interpretation phase (Months 36 42)—

Countries

India

Contacts

Public ContactDr Prashant B Patel

Department of Pharmacy, Sumandeep Vidyapeeth Deemed to be University

hemrajs119@gmail.com919738375211

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Mar 14, 2026