• Medientyp: E-Artikel
  • Titel: A risk prediction model to allow personalized screening for cervical cancer
  • Beteiligte: Rothberg, Michael B.; Hu, Bo; Lipold, Laura; Schramm, Sarah; Jin, Xian Wen; Sikon, Andrea; Taksler, Glen B.
  • Erschienen: Springer Science + Business Media, 2018
  • Erschienen in: Cancer Causes & Control
  • Umfang: 297-304
  • Sprache: Englisch
  • ISSN: 0957-5243; 1573-7225
  • Schlagwörter: ORIGINAL PAPER
  • Zusammenfassung: <sec> <label>Importance</label> <p>Cervical cancer screening guidelines are in evolution. Current guidelines do not differentiate recommendations based on individual patient risk.</p> </sec> <sec> <label>Objective</label> <p>To derive and validate a tool for predicting individualized probability of cervical intraepithelial neoplasia grade 2 or higher (CIN2+) at a single time point, based on demographic factors and medical history.</p> </sec> <sec> <label>Design</label> <p>The study design consisted of an observational cohort with hierarchical generalized linear regression modeling.</p> </sec> <sec> <label>Setting</label> <p>The study was conducted in a setting of 33 primary care practices from 2004 to 2010.</p> </sec> <sec> <label>Participants</label> <p>The participants of the study were women aged ≥ 30 years.</p> </sec> <sec> <label>Main outcome and measures</label> <p>CIN2+ was the main outcome on biopsy, and the following predictors were included: age, race, marital status, insurance type, smoking history, median income based on zip code, prior human papilloma virus (HPV) results.</p> </sec> <sec> <label>Results</label> <p>The final dataset included 99,319 women. Of these, 745 (0.75%) had CIN2+. The multivariable model had a C-statistic of 0.81. All factors but race were independently associated with CIN2+. The model categorized women as having below-average CIN2+ risk (0.15% predicted vs. 0.12% observed risk), average CIN2+ risk (0.42% predicted vs. 0.36% observed), and above-average CIN2+ risk (1.76% predicted vs. 1.85% observed). Before screening, women at below-average risk had a risk of CIN2+ well below that of women with ASCUS and HPV negative (0.12 vs. 0.20%).</p> </sec> <sec> <label>Conclusions and relevance</label> <p>A multivariable model using data from the electronic health record was able to stratify women across a 50-fold gradient of risk for CIN2+. After further validation, use of a similar model could enable more targeted cervical cancer screening.</p> </sec>
  • Beschreibung: <sec>
    <label>Importance</label>
    <p>Cervical cancer screening guidelines are in evolution. Current guidelines do not differentiate recommendations based on individual patient risk.</p>
    </sec>
    <sec>
    <label>Objective</label>
    <p>To derive and validate a tool for predicting individualized probability of cervical intraepithelial neoplasia grade 2 or higher (CIN2+) at a single time point, based on demographic factors and medical history.</p>
    </sec>
    <sec>
    <label>Design</label>
    <p>The study design consisted of an observational cohort with hierarchical generalized linear regression modeling.</p>
    </sec>
    <sec>
    <label>Setting</label>
    <p>The study was conducted in a setting of 33 primary care practices from 2004 to 2010.</p>
    </sec>
    <sec>
    <label>Participants</label>
    <p>The participants of the study were women aged ≥ 30 years.</p>
    </sec>
    <sec>
    <label>Main outcome and measures</label>
    <p>CIN2+ was the main outcome on biopsy, and the following predictors were included: age, race, marital status, insurance type, smoking history, median income based on zip code, prior human papilloma virus (HPV) results.</p>
    </sec>
    <sec>
    <label>Results</label>
    <p>The final dataset included 99,319 women. Of these, 745 (0.75%) had CIN2+. The multivariable model had a C-statistic of 0.81. All factors but race were independently associated with CIN2+. The model categorized women as having below-average CIN2+ risk (0.15% predicted vs. 0.12% observed risk), average CIN2+ risk (0.42% predicted vs. 0.36% observed), and above-average CIN2+ risk (1.76% predicted vs. 1.85% observed). Before screening, women at below-average risk had a risk of CIN2+ well below that of women with ASCUS and HPV negative (0.12 vs. 0.20%).</p>
    </sec>
    <sec>
    <label>Conclusions and relevance</label>
    <p>A multivariable model using data from the electronic health record was able to stratify women across a 50-fold gradient of risk for CIN2+. After further validation, use of a similar model could enable more targeted cervical cancer screening.</p>
    </sec>
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