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Updated: Aug 16, 2025
An Orthotopic Murine Model of Human Prostate Cancer Metastasis
Published on: September 18, 2013
Choice of imputation method for missing metastatic status affected estimates of metastatic prostate cancer incidence
Marcus Westerberg1, Kerri Beckmann2, Rolf Gedeborg3
1Department of Surgical Sciences, Uppsala University, Uppsala, Sweden; Department of Mathematics, Uppsala University, Uppsala, Sweden.
Objectives:
To study how handling missing data on M stage in a clinical cancer register affects estimates of incidence of metastatic prostate cancer.
Study Design And Setting:
Estimates of age-standardized incidence of metastatic prostate cancer were obtained by the use of data in a population-based clinical cancer register in Sweden and using four methods for imputation of missing M stage. Adjusted survival was used to compare men with known and imputed M stage.
Results:
The proportion of men with missing M stage was high (66%) and varied according to the risk group and over calendar time. The estimated incidence of metastatic disease varied depending on imputation method, with all methods indicating a decreasing incidence over time. A combination of deterministic imputation (DI) and multiple imputation (MI) produced adjusted survival curves for men with imputed M stage that best resembled the survival for men with known M stage.
Conclusions:
Plausible estimates of incidence of metastatic prostate cancer in clinical cancer registers can be obtained by the use of a combination of DI of missing M stage and MI.
Insights
Handling missing M stage data in prostate cancer registers is crucial. A combination of deterministic imputation (DI) and multiple imputation (MI) provides accurate metastatic prostate cancer incidence estimates.
Area of Science:
- Oncology
- Epidemiology
- Biostatistics
Background:
- Clinical cancer registers are vital for epidemiological studies.
- Missing data, particularly on metastatic stage (M stage), can significantly bias cancer incidence estimates.
- Accurate staging is essential for understanding cancer progression and treatment outcomes.
Purpose of the Study:
- To evaluate the impact of different data imputation methods on the estimated incidence of metastatic prostate cancer.
- To identify the most reliable method for handling missing M stage data in population-based cancer registries.
- To improve the accuracy of prostate cancer incidence and survival analyses.
Main Methods:
- Utilized data from a population-based clinical cancer register in Sweden.
- Applied four distinct methods for imputing missing M stage information.
- Compared incidence estimates and survival curves between known and imputed M stage data.
Main Results:
- A high proportion (66%) of men had missing M stage data, varying by risk group and time.
- Imputation methods yielded varying incidence estimates, though all suggested a decreasing trend.
- A combined deterministic imputation (DI) and multiple imputation (MI) approach best aligned imputed survival with known survival data.
Conclusions:
- A combined DI and MI strategy offers a robust solution for addressing missing M stage data in cancer registries.
- This approach enables more plausible and reliable estimation of metastatic prostate cancer incidence.
- Improved data handling can enhance the validity of epidemiological research on prostate cancer.
