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A Machine Learning-based Estimated Survival Model

NCT06432283 · Status: ACTIVE_NOT_RECRUITING · Type: OBSERVATIONAL · Enrollment: 1000

Last updated 2024-05-29

No results posted yet for this 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.

Conditions

  • Advanced Solid Tumor

Sponsors & Collaborators

  • Zhao Siyao

    lead OTHER

Principal Investigators

  • Siyao Zhao, postgraduate · West China Hospital

Eligibility

Min Age
60 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-05-01
Primary Completion
2025-12-31
Completion
2026-12-31

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06432283 on ClinicalTrials.gov