Endometrial Cancer Clinical Trial
Official title:
Preliminary Study of Endometrial Hyperplasia: Groundwork for a Study to Define an Optimal Classification of Endometrial Carcinoma Precursors
This study, conducted jointly by the National Cancer Institute and the Kaiser Permanente
Center for Health Research Northwest (KPCHRN) in Portland, Oregon, will lay the groundwork
for a future study to identify precursors of endometrial cancer; that is, conditions that
precede development of cancer of the lining of the uterus. The diagnosis of endometrial
hyperplasia (a condition of abnormal proliferation of endometrial tissue) includes most
precursors of endometrial cancer, as well as many benign conditions. Currently, three methods
of classifying endometrial cancer precursors have been suggested based on endometrial
hyperplasia findings, but it is not known which classification best predicts cancer risk.
This study will examine surgical specimens of hyperplasia and cancer from women diagnosed
with endometrial cancer at least 2 years after a diagnosis of endometrial hyperplasia.
Investigators will estimate the percentage of cases with different degrees of hyperplasia,
and assess the subsequent cancers that developed. This will allow them to rank hyperplasia
lesions according to cancer risk and identify lesions that represent the most immediate
cancer precursors. They will also review patients medical charts for information related to
cancer risk and treatment.
Study participants will include women enrolled in the KPCHRN who are 40 years of age or older
and who were diagnosed with endometrial cancer at least 2 years after being diagnosed with
endometrial hyperplasia.
Three systems have been proposed to classify endometrial carcinoma precursors, but it is
currently unclear which system best predicts cancer risk and is most reproducible. The
optimal surrogate endpoint for endometrial carcinoma is therefore unknown. The pathologic
diagnosis of endometrial hyperplasia (EH) includes most suspected immediate precursors and
many mild, highly reversible proliferations. We propose an exploratory study to assess the
feasibility of investigating EH as a source of an endometrial carcinoma surrogate endpoint.
We are conducting a nested case-control study within a large, population-based health care
plan. We will identify cases, defined as women who were diagnosed with EH at least one year
before being diagnosed with endometrial carcinoma or severe atypical hyperplasia at
hysterectomy, through a computerized search of plan databases. We will retrieve the slides
from the matching biopsy and hysterectomy on which carcinoma was diagnosed. Women ages 40 or
older who were plan members and received a biopsy or curettage diagnosis of EH between 1970
and 2002 will be eligible to be a case.
We will perform an initial histologic review of cases index biopsy slides to assess two types
of misclassification known to affect the diagnosis of EH: a) false-negative endometrial
carcinoma (i.e., prevalent carcinoma t the time of EH diagnosis) and b) false-positive EH
(i.e., a benign, non-hyperplastic lesion). From cases physical records and linked computer
records, we will collect data on histopathologic classification of EH lesions and subsequent
carcinomas; descriptive data (e.g., patient weight, parity, and menopausal status); and a
summary of relevant treatments and follow-up procedures (e.g., hormone therapy or additional
clinical procedures).
We will select controls, defined as women who were diagnosed with EH but then did not develop
endometrial carcinoma or undergo hysterectomy for a follow-up interval that is equivalent to
the follow-up interval of the cases. Controls will be individually matched to cases on age at
EH diagnosis, date of EH diagnosis, and duration of follow-up, and also counter-matched based
on the original EH diagnosis. After selecting 3 controls per case, we will assemble the same
data from controls: histologic review of original slides, descriptive data from medical
records databases, and treatment and follow-up procedure data from linked databases.
These data will then be used to estimate the cancer risk associated with specific EH
classifications, identify other patient or clinical factors that might modify those risks,
explore predictors of EH, and explore molecular factors that might influence the probability
of developing carcinoma after a diagnosis of EH.
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