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Associations between diagnostic patterns and stages in ovarian cancer

Journal Article · · Model Assisted Statistics and Applications
DOI:https://doi.org/10.3233/mas-170402· OSTI ID:1399505
 [1];  [2];  [2];  [3];  [4];  [5];  [2]
  1. Case Western Reserve Univ., Cleveland, OH (United States). Dept. of Orthopedics
  2. Case Western Reserve Univ., Cleveland, OH (United States). Center for Statistical Research, Computing and Collaboration (SR2c), Dept. of Population and Quantitative Health Sciences
  3. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Case Western Reserve Univ., Cleveland, OH (United States). Dept. of Population and Quantitative Health Sciences
  4. State Univ. of New York (SUNY), Binghamton, NY (United States). Dept. of Biological Sciences
  5. Univ. Hospitals, Cleveland, OH (United States). Dept. of OB/GYN-Gynecological Oncology
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Ovarian cancer (OvCa) is the fifth leading cause of cancer deaths in women and remains the most deadly gynecological cancer. The disease places a debilitating burden on the US population, in terms of mortality, morbidity, individual suffering and loss of productivity for all women with OvCa. National expenditures for OvCa care were estimated at $5.12B in 2010. The high fatality of OvCa is attributed to the fact that most patients are diagnosed at a late stage, with 63% diagnosed at Stage III or later. Effective early-stage diagnosis is challenging because there are no approved screening procedures for the general population, which has led to OvCa being termed1 the “silent killer”. We have previously shown that public awareness and knowledge about OvCa is poor among the general population. It has also been reported that ovarian masses have often been misdiagnosed, although there was some association of pre-diagnostic symptoms with OvCa and with OvCa diagnostic stages. The motivation for the current study was to examine the association of diagnostic patterns (determined by the responses from ‘frontline’ clinicians, specifically primary care physicians (PCPs) and emergency room (ER) doctors, together with follow-up by specialists), with OvCa stages.

Research Organization:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
AC04-94AL85000
OSTI ID:
1399505
Report Number(s):
SAND-2017-6463J; 654620
Journal Information:
Model Assisted Statistics and Applications, Vol. 12, Issue 3; ISSN 1574-1699
Publisher:
IOS PressCopyright Statement
Country of Publication:
United States
Language:
English

References (12)

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Patient Education vs. Patient Experiences of Self-advocacy: Changing the Discourse to Support Cancer Survivors journal April 2015
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Crowdsourcing Awareness: Exploration of the Ovarian Cancer Knowledge Gap through Amazon Mechanical Turk journal January 2014
Misdiagnoses of Ovarian Masses in Children and Adolescents journal January 2004
Validation of a Medicare Claims-based Algorithm for Identifying Breast Cancers Detected at Screening Mammography journal January 2016

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