Clinical trial · Observational
A Machine Learning-based Estimated Survival Model
Construction and Validation of a Machine Learning-based Estimated Survival Model for Elderly Patients With Advanced Malignancy
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
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
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Advanced Solid Tumor | Solid Neoplasm | CURATED_BROADER | 0.80 |
Interventions
Interventions (0)
Data not yet available
Design
Arms and outcomes
Arms (1)
- label
- advanced cancer (stage III and IV) patients aged 60 years and above.
- description
- advanced cancer (stage III and IV) patients aged 60 years and above who are receiving treatment at the mentioned institution. The research subjects voluntarily participate and sign informed consent forms.
Primary outcomes (1)
- measure
- A model
- timeFrame
- 2026-12-31
- description
- Build a survival estimation model for elderly late-stage cancer patients.
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 60 Years
Show eligibility criteria text
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.
References
Publications (0)
Data not yet available