Multistate Markov Model to Predict the Prognosis of High-Risk Human Papillomavirus-Related Cervical Lesions

Abstract

Cervical intraepithelial neoplasia (CIN) has a natural history of bidirectional transition between different states. Therefore, conventional statistical models assuming a unidirectional disease progression may oversimplify CIN fate. We applied a continuous-time multistate Markov model to predict this CIN fate by addressing the probability of transitions between multiple states according to the genotypes of high-risk human papillomavirus (HPV). This retrospective cohort comprised 6022 observations in 737 patients (195 normal, 259 CIN1, and 283 CIN2 patients at the time of entry in the cohort). Patients were followed up or treated at the University of Tokyo Hospital between 2008 and 2015. Our model captured the prevalence trend satisfactory, particularly for up to two years. The estimated probabilities for 2-year transition to CIN3 or more were the highest in HPV 16-positive patients (13%, 30%, and 42% from normal, CIN1, and CIN2, respectively) compared with those in the other genotype-positive patients (3.1–9.6%, 7.6–16%, and 21–32% from normal, CIN1, and CIN2, respectively). Approximately 40% of HPV 52- or 58-related CINs remained at CIN1 and CIN2. The Markov model highlights the differences in transition and progression patterns between high-risk HPV-related CINs. HPV genotype-based management may be desirable for patients with cervical lesions.

Prognosis of high‐risk human papillomavirus‐related cervical lesions: A hidden Markov model analysis of a single‐center cohort in Japan

“…Moreover, the progression and regression rates were similar between patients with other hrHPVs and those with no hrHPVs. These results are consistent with those seen in the literature and corroborate the finding that patients with HPV 16 are more likely to develop more severe lesions than those with HPV 52, HPV 58, other hrHPVs, or no hrHPVs 6 . By applying the hidden Markov model to accommodate the diagnostic misclassification, our study confirmed the robustness of the current literature on CIN characteristics according to HPV genotype.…”

Nucleic acids and proteins carried by exosomes of different origins as potential biomarkers for gynecologic cancers

“… 111 Persistent high-risk human papillomavirus (HPV) infection is considered a leading cause of cervical cancer, and the HPV oncogenes E6 and E7 play an essential role in this process. 112 , 113 However, a few patients with cervical cancer do not show HPV infection; thus, preventing high-grade cervical intraepithelial neoplasia (CIN) from developing into invasive cervical cancer through early screening is crucial. 114 …”

Genotype-specific Distribution and Change of High-risk Human Papillomavirus Infection and the Association with Cervical Progression Risk in Women with Normal Pathology and Abnormal Cytology in a Population-based Cohort Study in China

“…HPV31/33 infections have also been reported to promote cervical carcinogenesis worldwide [7][8][9][10]. HPV52 and 58 are the genotypes with oncogenic potential and high prevalence in Asia regions [10,11]. The 5-year risk for cervical intraepithelial neoplasia grade 2 and above (CIN2+) was much higher (45.3%) in women with mild abnormal cervical cytology than that (12.9%) in women with normal cervical cytology [12], suggesting that women with normal pathology screened from abnormal cervical cytology were a special population with higher progression risk than women with normal cytology.…”

“…A PCR-based flow-through hybridization and gene chip system were used for HPV hybridization and color rendering. Purple 11,42,43,44,and CP8304). HR-HPV infection meant that at least one HR-HPV genotype was positive.…”