Clinical trial · Observational
Machine Learning Model to Predict HOLS and Mortality After Discharge in Hospitalized Oncologic Patients
Machine Learning Model to Predict Hospital Length of Stay (HOLS) and Mortality After Discharge in Hospitalized Oncologic Patients [Plantology Database]: a Multicenter Cross-validation Study
- 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)
The study aims to understand which are the most relevant parameters at admission which may allow to predict the hospital length of stay (HOLS) and mortality after discharge of oncologic hospitalized patients. This is the first multicentric prospective observational study that tries to understand the complexity of the hospitalized oncologic patients. A comprehensive analysis will be performed with the help of the nutrition, nursery, internal medicine and oncology teams.
Conditions
Conditions (8)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Artificial Intelligence | — | UNRESOLVED | — |
| Comorbidities and Coexisting Conditions | — | UNRESOLVED | — |
| Mental Status Change | — | UNRESOLVED | — |
| Nutrition Related Neoplasm/Cancer | — | UNRESOLVED | — |
| Oncology | — | UNRESOLVED | — |
| Quality of Life | — | UNRESOLVED | — |
| Solid Tumor | Solid Neoplasm | CURATED_BROADER | 0.80 |
| Tumor | Neoplasm | ALIAS | 0.90 |
Interventions
Interventions (0)
Data not yet available
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (2)
- measure
- Predict Mortality
- timeFrame
- 30 days after discharge
- description
- Mortality at 30-day after discharge
- measure
- Predict hospital length of stay
- timeFrame
- Through study completion, an average of 3 years
- description
- Number of days hospitalized
Secondary outcomes (8)
- measure
- Measure the impact of Anxiety and Depression
- timeFrame
- Within 24 hours of admission
- description
- Hospital Anxiety and Depression Scale (HADS). Minimum: 0 Maximum: 21. More than 12 points is clinical significant for depression or anxiety \[0-7 = Normal; 8-10 = Borderline; abnormal (borderline case)\] 11-21 = Abnormal (case)
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * ≥18 years-old. * Histological cancer confirmation. * Hospitalization in oncology ward. Exclusion Criteria: * \<18 years-old. * Not histological malignancy confirmed. * Less than 24 hours in the hospital.
References
Publications (5)
- RESULTSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021 May;71(3):209-249. doi: 10.3322/caac.21660. Epub 2021 Feb 4. PMID 33538338
- RESULTBrooks GA, Cronin AM, Uno H, Schrag D, Keating NL, Mack JW. Intensity of Medical Interventions between Diagnosis and Death in Patients with Advanced Lung and Colorectal Cancer: A CanCORS Analysis. J Palliat Med. 2016 Jan;19(1):42-50. doi: 10.1089/jpm.2015.0190. Epub 2015 Nov 24. PMID 26600474
- RESULTManzano JG, Luo R, Elting LS, George M, Suarez-Almazor ME. Patterns and predictors of unplanned hospitalization in a population-based cohort of elderly patients with GI cancer. J Clin Oncol. 2014 Nov 1;32(31):3527-33. doi: 10.1200/JCO.2014.55.3131. Epub 2014 Oct 6. PMID 25287830
- RESULTEarle CC, Park ER, Lai B, Weeks JC, Ayanian JZ, Block S. Identifying potential indicators of the quality of end-of-life cancer care from administrative data. J Clin Oncol. 2003 Mar 15;21(6):1133-8. doi: 10.1200/JCO.2003.03.059. PMID 12637481
- RESULTWhitney RL, Bell JF, Tancredi DJ, Romano PS, Bold RJ, Joseph JG. Hospitalization Rates and Predictors of Rehospitalization Among Individuals With Advanced Cancer in the Year After Diagnosis. J Clin Oncol. 2017 Nov 1;35(31):3610-3617. doi: 10.1200/JCO.2017.72.4963. Epub 2017 Aug 29. PMID 28850290