Cancer Causes & Control

, Volume 23, Issue 12, pp 2013–2021 | Cite as

A modified Latent Class Model assessment of human papillomavirus-based screening tests for cervical lesions in women with atypical glandular cells: a Gynecologic Oncology Group study

  • Randy L. Carter
  • Le Kang
  • Kathleen M. Darcy
  • James Kauderer
  • Shu-Yuan Liao
  • William H. Rodgers
  • Joan L. Walker
  • Heather A. Lankes
  • S. Terence Dunn
  • Eric J. Stanbridge
Original paper



In the absence of gold standard diagnoses, we estimate age-specific false-positive and false-negative prediction rates of HPV-, cytology-, and histology-based tests for significant cervical lesions (SCL) in US women with AGC-NOS Pap smear diagnoses.


Modified Latent Class Model (LCM) analyses, with prevalence of SCL modeled as a function of age, were applied to GOG-0171 study data (n = 122). The accuracies of several HPV-based tests, including Hybrid Capture II high-risk HPV (HC2 H-HPV); carbonic anhydrase IX (CA-IX); and invasive histological diagnosis, were compared. 1-PPV and 1-NPV were written as functions of sensitivity, specificity, and prevalence to obtain age-specific false-positive and false-negative rates.


The histology-based test was nearly perfect (sensitivity = 1.00, CI = 0.98–1.00; specificity = 0.99, CI = 0.96–1.00). Otherwise, HC2 H-HPV performed best (sensitivity = 1.00, CI = 1.00–1.00; specificity = 0.87, CI = 0.79–0.94). The false-positive detection rates (1-PPV) for HC2 H-HPV were high (>17 %) at each age, while those of the histological diagnoses were low (<5 % at ages ≤60 and <17 % overall ages). False-negative prediction rates (1-NPV) for HC2 H-HPV were <0.11 % at each age and were uniformly lower than those of other tests, including the histology-based test (<0.25 %). CA-IX together with HC2 H-HPV did not improve performance.


Women with negative HC2 H-HPV can safely forego invasive treatment (i.e., cone or LEEP biopsy, hysterectomy) in favor of observational follow-up. Additional biomarkers must be found for use in combination with HC2 H-HPV to reduce false-positive rates. This novel application of a modified LCM exemplifies methods for potential use in future cancer screening studies when gold standard diagnoses are not available.


Human papillomavirus Carbonic anhydrase IX Atypical glandular cells GOG HPV 



The following member institutions participated in this study: Abington Memorial Hospital, Walter Reed Army Medical Center, University of Mississippi Medical Center, University of California at Los Angeles, University of Pennsylvania Cancer Center, University of Cincinnati, University of Texas Southwestern Medical Center at Dallas, Wake Forest University School of Medicine, University of California Medical Center at Irvine, Tufts-New England Medical Center, The Cleveland Clinic Foundation, SUNY at Stony Brook, Washington University School of Medicine, Cooper Hospital/University Medical Center, Columbus Cancer Council, Fox Chase Cancer Center, Women’s Cancer Center—University of Nevada, University of Oklahoma, Tacoma General Hospital, Tampa Bay Cancer Consortium, Gynecologic Oncology Network/Brody School of Medicine, Ellis Fischel Cancer Center, Fletcher Allen Health Care, University of Wisconsin Hospital, University of Texas-Galveston. This study was supported by National Cancer Institute grants to the Gynecologic Oncology Group Administrative Office (CA 27469) and the Gynecologic Oncology Group Statistical and Data Center (CA 37517).

Conflict of interest

The authors wish to report that there are no conflicts of interest.

Supplementary material

10552_2012_81_MOESM1_ESM.doc (40 kb)
Supplementary material 1 (DOC 39 kb)


  1. 1.
    Kennedy AW, Salmieri SS, Wirth SL, Biscotti CV, Tuason LJ, Travarca MJ (1996) Results of the clinical evaluation of atypical glandular cells of undetermined significance (AGCUS) detected on cervical cytology screening. Gynecol Oncol 3:14–18CrossRefGoogle Scholar
  2. 2.
    Wilbur DC (1995) Endocervical glandular atypia: a “new” problem for the cytologist. Diagn Cytopathol 13:463–469PubMedCrossRefGoogle Scholar
  3. 3.
    Lee KR, Manna EA, St John T (1995) Atypical endocervical glandular cells: accuracy of cytologic diagnosis. Diagn Cytopathol 13:202–208PubMedCrossRefGoogle Scholar
  4. 4.
    Nasu I, Meurer W, Fu YS (1993) Endocervical glandular atypia and adenocarcinoma: a correlation of cytology and histology. Int J Gynecol Pathol 12:208–211PubMedCrossRefGoogle Scholar
  5. 5.
    Liao SY, Rodgers WH, Kauderer J et al (2009) Carbonic anhydrase IX and human papillomavirus as diagnostic biomarkers of cervical dysplasia/neoplasia in women with a cytologic diagnosis of atypical glandular cells: a Gynecologic Oncology Group study in United States. Int J Cancer 125:2434–2440PubMedCrossRefGoogle Scholar
  6. 6.
    Schnatz PF, Guile M, O’Sullivan DM, Sorosky JL (2006) Clinical significance of atypical glandular cells on cervical cytology. Obstet Gynecol 107:701–708PubMedCrossRefGoogle Scholar
  7. 7.
    Sieber AG, Massuger LFAG, Bulten J (2007) Referral compliance, outcome and predictors of CIN after repeated borderline cervical smears in the Netherlands. Cytopathology 18:96–104CrossRefGoogle Scholar
  8. 8.
    Valenstein P (1990) Evaluating diagnostic tests with imperfect standards. Am J Clin Pathol 93:252–258PubMedGoogle Scholar
  9. 9.
    Gaffikin L, McGrath JA, Arbyn M, Blumenthal PD (2007) Visual inspection with acetic acid as a cervical cancer test: accuracy validated using latent class analysis. BMC Med Res Methodol 7:36PubMedCrossRefGoogle Scholar
  10. 10.
    Myers ER, McCrory DC, Nanda K, Bastian L, Matchar DB (2000) Mathematical model for the natural history of human papillomavirus infection and cervical carcinogenesis. Am J Epidemiol 156:1158–1171CrossRefGoogle Scholar
  11. 11.
    Liao SY, Brewer C, Závada J et al (1994) Identification of the MN antigen as a diagnostic biomarker of cervical intraepithelial squamous and glandular neoplasia and cervical carcinoma. Am J Pathol 145:598–609PubMedGoogle Scholar
  12. 12.
    Liao SY, Stanbridge EJ (1994) Expression of the MN antigen in cervical Papanicolaou smears is an early diagnostic biomarker of cervical dysplasia. Cancer Epidemiol Biomarkers Prev 5:549–557Google Scholar
  13. 13.
    Gravitt PE, Schiffman M, Solomon D, Wheeler CM, Castle PE (2008) A comparison of linear array and hybrid capture 2 for detection of carcinogenic human papillomavirus and cervical precancer in ASCUS-LSIL triage study. Cancer Epidemiol Biomarkers Prev 17:1248–1254PubMedCrossRefGoogle Scholar
  14. 14.
    Castle PE, Sadorra M, Garcia F, Holladay EB, Kornegay J (2008) Pilot study of a commercialized human papillomavirus (HPV) genotyping assay: comparison of HPV risk group to cytology and histology. J Clin Microbiol 44:3915–3917CrossRefGoogle Scholar
  15. 15.
    Lazarsfeld P, Henry N (1968) Latent structure analysis. Houghton Mifflin Co., BostonGoogle Scholar
  16. 16.
    Walter SD, Irwig LM (1988) Estimation of error rates, disease prevalence and relative risk from misclassified data: a review. J Clin Epidemiol 41:923–938PubMedCrossRefGoogle Scholar
  17. 17.
    Uebersax JS, Grove WM (1990) Latent class analysis of diagnostic agreement. Stat Med 9:559–572PubMedCrossRefGoogle Scholar
  18. 18.
    Dempster AP, Laird NM, Rubin DB (1977) Maximum likelihood estimation from incomplete data via the EM algorithm. J Royal Stat Soc Ser B 39:1–38Google Scholar
  19. 19.
    Wei GCG, Tanner MA (1990) A Monte Carlo implementation of the EM algorithm and the poor man’s data augmentation algorithms. J Am Stat Assoc 85:699–704CrossRefGoogle Scholar
  20. 20.
    Bland M (2000) An introduction to medical statistics, 3rd edn. Oxford University Press, OxfordGoogle Scholar
  21. 21.
    Efron B, Tibshirani RJ (1993) An introduction to the bootstrap. Chapman and Hall/CRC, Boca RatonGoogle Scholar
  22. 22.
    Pretorius RG, Bao YP, Belinson JL, Burchette RJ, Smith JS, Qiao YL (2007) Inappropriate gold standard bias in cervical cancer screening studies. Int J Cancer 121(10):2218–2224PubMedCrossRefGoogle Scholar
  23. 23.
    Poljak M, Marin IJ, Seme K, Vince A (2002) Hybrid Capture II HPV test detects at least 15 human papillomavirus genotypes not included in its current high risk cocktail. J Clin Virol 25(Suppl. 3):S89–S97PubMedCrossRefGoogle Scholar
  24. 24.
    Castle PE, Gravitt PE, Solomon D, Wheeler CM, Schiffman M (2008) Comparison of linear array and line blot assay for detection of human papillomavirus and diagnosis of cervical precancer and cancer in the atypical squamous cell of undetermined significance and low-grade squamous intraepithelial lesion triage study. J Clin Microbiol 46:109–117PubMedCrossRefGoogle Scholar
  25. 25.
    Castle PE, Schiffman M, Burk RD et al (2002) Restricted cross-reactivity of hybrid capture 2 with non-oncogenic human papillomavirus types. Cancer Epidemiol Biomarkers Prev 11:1394–1399PubMedGoogle Scholar
  26. 26.
    Castle PE, Solomon D, Wheeler CM, Gravitt PE, Wacholder S, Schiffman M (2008) Human papillomavirus genotype specificity of Hybrid Capture 2. J Clin Microbiol 46:2595–2604PubMedCrossRefGoogle Scholar
  27. 27.
    Liao SY, Rodgers WH, Kauderer J et al (2010) Carbonic anhydrase IX (CA-IX) and high-risk human papillomavirus (H-HPV) as diagnostic biomarkers of cervical dysplasia/neoplasia in Japanese women with a cytologic diagnosis of atypical glandular cells (AGC): a Gynecologic Oncology Group (GOG) Study. Br J Cancer 104:353–360PubMedCrossRefGoogle Scholar
  28. 28.
    Schiffman M, Castle PE, Jeronimo J, Rodriguez AC, Wacholder S (2007) Human papilloma virus and cervical cancer. Lancet 370:890–907PubMedCrossRefGoogle Scholar
  29. 29.
    Kinney W, Stoler MH, Castle PE (2010) Patient safety and the next generation of HPV DNA tests. Am J Clin Pathol 134:193–199PubMedCrossRefGoogle Scholar
  30. 30.
    Castle PE, Katki HA (2010) Benefits and risks of HPV testing in cervical cancer screening. Lancet Oncol 11:214–215PubMedCrossRefGoogle Scholar
  31. 31.
    Arbyn M, Kyrgiou M, Simoens C et al (2008) Perinatal mortality and other severe adverse pregnancy outcomes associated with treatment of cervical intraepithelial neoplasia: meta-analysis. BMJ 337:a1284PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  • Randy L. Carter
    • 1
    • 2
  • Le Kang
    • 2
  • Kathleen M. Darcy
    • 1
    • 8
  • James Kauderer
    • 1
  • Shu-Yuan Liao
    • 3
  • William H. Rodgers
    • 4
  • Joan L. Walker
    • 5
  • Heather A. Lankes
    • 1
  • S. Terence Dunn
    • 6
  • Eric J. Stanbridge
    • 7
  1. 1.GOG Statistical and Data CenterRoswell Park Cancer InstituteBuffaloUSA
  2. 2.Department of BiostatisticsUniversity at BuffaloBuffaloUSA
  3. 3.Department of Epidemiology, School of MedicineUniversity of California at IrvineIrvineUSA
  4. 4.Department of PathologyNSLIJ/Lenox Hill HospitalNew YorkUSA
  5. 5.Department of Obstetrics and GynecologyUniversity of Oklahoma Health Sciences CenterOklahoma CityUSA
  6. 6.Department of PathologyUniversity of Oklahoma Health Sciences CenterOklahoma CityUSA
  7. 7.Department of Microbiology and Molecular Genetics, School of MedicineUniversity of California at IrvineIrvineUSA
  8. 8.The Henry M. Jackson Foundation for the Advancement of Military Medicine, Department of Defense Gynecologic Cancer Center of ExcellenceAnnandaleUSA

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