Clinical trial NCT06432283: A Machine Learning-based Estimated Survival Model
Official title: Construction and Validation of a Machine Learning-based Estimated Survival Model for Elderly Patients With Advanced Malignancy
Study type: OBSERVATIONAL
Overall status: ACTIVE_NOT_RECRUITING
Conditions: Advanced Solid Tumor
Lead sponsor: West China Hospital
Sponsor class: OTHER
First posted: 2024-05-29
Enrollment: 1000
Sex: ALL
Minimum age (years): 60
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: Advanced cancer （stage III and IV） malignant tumor patients aged 60 years and above.

Brief 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.

Detailed description: 1. By searching the literature, conducting systematic reviews, and meta-analyses, we aim to uncover the prognostic factors related to death in elderly advanced cancer patients.
2. Based on evidence-based data and considering the clinical conditions of elderly advanced cancer patients in China, we will establish relevant entries for a risk assessment scale for death in elderly advanced cancer patients. By using the Delphi expert consultation evaluation method, we will finalize the assessment scale framework, laying the theoretical foundation for the establishment and validation of a death risk prediction model for elderly advanced cancer patients in China.
3. Develop a survival estimation model for elderly advanced cancer patients; through metabolomics studies and other research methods, we will investigate metabolic biomarkers related to predicting the survival period of elderly advanced cancer patients.

Eligibility criteria: 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 outcomes:
measure: A model
timeFrame: 2026-12-31
Secondary outcomes:
Other outcomes:
Locations:
city: Chengdu
country: China
facility: Siyao Zhao
state: Sichuan
Study officials:
affiliation: West China Hospital
name: Siyao Zhao, postgraduate
role: PRINCIPAL_INVESTIGATOR
References: