Biological Age Predicts 90-Day Mortality in Advanced Cancer

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

1615 participants

Study Classification

OBSERVATIONAL

Study Start Date

2022-11-05

Study Completion Date

2024-12-31

Brief Summary

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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.

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Detailed Description

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This is a retrospective observational study including hospitalized adult patients with stage III or IV solid tumors admitted to Etlik City Hospital between November 5, 2022 and December 31, 2024. Patients were included if they stayed for ≥48 hours and had all required laboratory values for calculating biological age using the Levine PhenoAge model. The study aimed to evaluate the association between biological age and (1) 30- and 90-day mortality, (2) ECOG performance score, (3) modified Charlson Comorbidity Index (mCCI), and (4) hospital length of stay. Regression and survival analyses were used to identify prognostic factors. All data were anonymized and collected retrospectively from hospital records.

Conditions

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Advanced Solid Tumors Cancer Hospitalizations

Study Design

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Observational Model Type

COHORT

Study Time Perspective

RETROSPECTIVE

Study Groups

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Hospitalized Advanced Cancer Patients

Patients hospitalized with advanced solid tumors (Stage III or IV) in the oncology clinic were retrospectively analyzed. Biological age was calculated using the PhenoAge model. Clinical outcomes such as mortality, ECOG score, mCCI, and length of stay were assessed.

PhenoAge-Based Biological Age Assessment

Intervention Type OTHER

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.

Interventions

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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.

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* Hospitalized in the Medical Oncology Department between November 5, 2022, and December 31, 2024

Histologically confirmed advanced-stage (stage III-IV) solid tumors

Age ≥18 years

Hospital stay of at least 48 hours

Actively receiving chemotherapy or received it within the last 6 months

Availability of all 9 required laboratory tests (albumin, creatinine, glucose, CRP, lymphocyte %, MCV, RDW, ALP, WBC) for PhenoAge calculation during the first admission

Exclusion Criteria

* Elective hospitalizations (e.g., planned chemotherapy, biopsy)

Patients who died during the first admission

Missing required laboratory parameters

ICU patients and unconscious patients

Eligible Sex

ALL

Accepts Healthy Volunteers

No