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Biological Age Predicts 90-Day Mortality in Advanced Cancer

NCT07035470 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 1615

Last updated 2025-06-29

No results posted yet for this study

Summary

This retrospective study evaluates whether biological age, calculated using the PhenoAge model, predicts short-term outcomes in patients with advanced cancer who were hospitalized. The main goal is to investigate associations between biological age and short-term mortality, functional status (ECOG), comorbidity burden (mCCI), and length of hospital stay. All data were collected from medical records without any patient intervention.

Conditions

  • Advanced Solid Tumors Cancer
  • Hospitalizations

Interventions

OTHER

PhenoAge-Based Biological Age Assessment

Biological age was retrospectively calculated using the PhenoAge algorithm, based on nine routine laboratory parameters and chronological age. This model estimates phenotypic aging and was used to predict short-term outcomes including mortality, functional status, comorbidity burden, and hospital length of stay. No new intervention was administered; all data were collected from existing medical records.

Sponsors & Collaborators

  • Ankara Etlik City Hospital

    lead OTHER_GOV

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-11-05
Primary Completion
2024-12-31
Completion
2024-12-31

Countries

  • Turkey (Türkiye)

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 NCT07035470 on ClinicalTrials.gov