Time-dependent association between mean platelet volume and gynecological cancer risk in a large healthcare-based cohort
Year: 2026
Type: article
Abstract: Background Gynecological cancers remain a major public health concern worldwide, highlighting the need for accessible biomarkers for early risk assessment. This study aimed to investigate the association between routine clinical laboratory parameters and the risk of incident gynecological cancers in a large healthcare-based cohort. Methods We conducted a retrospective cohort study including 187, 861 women from the Clinical Center of the University of Debrecen between 2007 and 2023. Baseline laboratory parameters were defined as the median of measurements recorded in the entry year. Incident gynecological cancers were identified using International Classification of Diseases (ICD) codes. Time-to-event analyses were performed using Kaplan-Meier methods and Cox proportional hazards models, incorporating time-varying coefficients to address violations of proportionality. Results During a median follow-up of approximately 10 years (IQR 6–14 years; maximum follow-up 16 years), 1, 036 incident gynecological cancer cases were identified, corresponding to a crude proportion of 0.55%. Higher baseline mean platelet volume (MPV) was significantly associated with increased cancer risk; however, this relationship was strongly time-dependent. MPV showed little or inverse association in early follow-up but demonstrated progressively increasing hazard ratios over time. This pattern remained robust after adjustment for age, red cell distribution width (RDW), and C-reactive protein (CRP). RDW exhibited a time-dependent association with stronger effects early in follow-up that attenuated over time, while age showed a consistent positive association with cancer risk. Conclusion In this large healthcare-based cohort, higher baseline MPV was associated with an increased long-term risk of incident gynecological cancer, and the association strengthened with longer follow-up. These findings represent adjusted epidemiological associations that may be affected by residual confounding and should not be interpreted as causal.
Source: Frontiers in Oncology
Institution: University of Debrecen
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W7225821670