Assessing factors associated with clusters of DNA index distribution in patients with cervical neoplasia
Cervical cancer is the fourth most common cancer affecting women worldwide, with a high incidence and mortality rate especially in underdeveloped regions. One prevention strategy for cervical cancer includes screening and risk factor reduction. Regular screening with the Papanicolaou test has contributed to a decline in the incidence rate but is difficult to apply in low-resource settings due to the high cost. A new screening method known as quantitative cytology has shown promise for a more cost-effective screening modality. Quantitative cytology measures multiple cell features that assist in detecting pre-cancerous anomalies. DNA index, a measure of the amount of chromatin in the cell nucleus, is the cell feature most widely used and the distribution of the DNA index has recently been shown to be correlated with pre-cancer status. However, within each pre-cancer status (“Positive”: cervical intraepithelial neoplasia (CIN) grade 2/3, carcinoma in situ (CIS) and cancer; “Negative”: atypia, HPV associated changes (HPVAC) and CIN1), heterogeneity exists in the distribution of the DNA index of cells within a patient, and the factors associated with this heterogeneity are still unknown. Thus, in this study we aimed at finding factors associated with the heterogeneity. The data set was obtained from a large cohort previously conducted at the University of Texas MD Anderson Cancer Center, British Columbia Cancer Agency, and Lyndon Baines Johnson General Hospital. We used K-means and hierarchical clustering to group individuals into clusters based on similar DNA index distributions, and then used standard statistical tests and multinomial logistic regressions to examine the association between factors and cluster membership. The results showed that histology and race/ethnicity were significantly different in their distributions across clusters. The severity of histologic grade was positively associated with the proportion of aneuploid cells. Blacks were associated with a more aberrant DNA index distribution, after controlling for all other factors in the regression model, indicating a higher risk of cancer progression. Thus race should be considered in algorithms using quantitative cytology data. Further studies of the association between differences in the proportion of aneuploidy cells in Blacks versus non-Blacks and clinical progression are warranted.
Pan, Meiling, "Assessing factors associated with clusters of DNA index distribution in patients with cervical neoplasia" (2016). Texas Medical Center Dissertations (via ProQuest). AAI10126715.