A Machine Learning-based Estimated Survival Model

NCT06432283 · tracked via the Priya Life Science China tracker

Sponsor

Zhao Siyao

Phase

Observational

Started

2024-05-01

Last updated

2024-05-29

Condition(s) studied

Advanced Solid Tumor

Study summary

Malignant tumors are the leading cause of death in elderly patients, and palliative care can improve the quality of life for elderly advanced cancer patients. One of the main reasons why these patients are not included in palliative care is the lack of accurate estimation of their survival period by patients, family members, and doctors. Both doctors and patients tend to be overly optimistic about the survival period of elderly advanced cancer patients, leading to overtreatment. Therefore, assessing the risk of death for these patients and further establishing a survival period estimation model can improve the accuracy of doctors' clinical predictions of patient survival, facilitate early referral to palliative care, and promote rationalization of medical decision-making.

Eligibility

Sex

ALL

Min age

60 Years

Max age

—

Healthy volunteers

Inclusion Criteria:Inclusion criteria for late-stage malignant tumor patients: Must meet Condition 1) and also meet either Condition 2), 3), or 4): 1. Clinical diagnosis of advanced malignant tumor: TNM stage III or IV 2. "Surprise question": If this patient were to die within the next 6 months, it would not be surprising to you. 3. Karnofsky performance status (KPS) score ≤ 50 4. Palliative Performance Scale (PPS) ≤ 50% Exclusion Criteria: 1. Patients who refuse to participate in the study; 2. Patients who, for various reasons, are unable to cooperate and complete the questionnaire survey; 3. Patients who, for various reasons, are unable to cooperate and complete the follow-up.

Primary outcome measure(s)

A model — 2026-12-31
Build a survival estimation model for elderly late-stage cancer patients.

Trial sites (1)

Facility	City	Region	Status
Siyao Zhao	Chengdu	Sichuan

Other trials for the same condition

A Study of CHS-114 (Tagmokitug) in Combination With Toripalimab and/or Other Treatments in Participants With Advanced Solid Tumors Recruiting

Study of SHR-A1921 in Combination With Other Anti-cancer Agents in Patients With Advanced Solid Tumors Active, not recruiting

A First-in-human Study of PARP1 Selective Inhibitor, IMP1734, in Participants With Advanced Solid Tumors Recruiting

Study SC-101 in Subjects With Advanced Malignancies Recruiting

Phase I/II FIH Study of 9MW2921 in Patients With Advanced Solid Tumors Active, not recruiting

Official registry record

This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.

View NCT06432283 on ClinicalTrials.gov ↗ ← All trials in China