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Updated: Mar 29, 2026

Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence

Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence

Published on: November 2, 2014

Diagnostic Timing and Ovarian Cancer Survival.

Sarah E Soppe¹, Tzy-Mey Kuo², Victoria L Bae-Jump^2,3

¹Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill.

JAMA Network Open

|March 27, 2026

Summary

Earlier ovarian cancer (OC) diagnosis does not improve survival due to the wait time paradox. Both very short and long diagnostic intervals are linked to worse outcomes, highlighting the need for nonlinear analysis in OC research.

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Area of Science:

Oncology
Epidemiology
Biostatistics

Background:

Earlier cancer diagnosis generally improves patient outcomes.
However, studies indicate earlier diagnosis does not improve ovarian cancer (OC) survival, potentially discouraging diagnostic research.
The 'wait time paradox' may explain this, where severe cases are diagnosed faster but have poorer prognoses, masking benefits of timely diagnosis.

Purpose of the Study:

To investigate how nonlinear modeling of diagnostic time influences the association with OC survival.
To specifically address the confounding effect of the wait time paradox in OC diagnosis and survival.

Main Methods:

A cohort study utilizing North Carolina Central Cancer Registry data linked with multipayer claims (Medicare, Medicaid, private insurance).
Included female patients diagnosed with OC between January 1, 2009, and December 31, 2019.
Time to diagnosis was defined as the interval from the first symptom-related healthcare encounter to diagnosis; all-cause 5-year mortality was the primary outcome.

Main Results:

Analysis of 2359 women revealed a U-shaped association between time to diagnosis and mortality when using nonlinear modeling (restricted cubic splines).
The shortest diagnostic intervals (e.g., 10 days) and longer intervals (e.g., 360 days) were associated with increased mortality compared to a reference of 80 days.
Patients in the second-shortest quartile of diagnostic intervals had better survival outcomes and were more likely to be diagnosed at earlier stages.

Conclusions:

Very short diagnostic intervals in OC are linked to poorer survival, likely due to confounding by disease severity (wait time paradox).
Longer diagnostic intervals are also associated with worse outcomes.
Conventional linear analyses may obscure these complex relationships, contributing to previous null findings and hindering efforts to improve OC diagnosis.