Performance characteristics of Pap test, VIA, VILI, HR-HPV testing, cervicography, and colposcopy in diagnosis of significant cervical pathology

We sought to evaluate the performance of diagnostic tools to establish an affordable setting for early detection of cervical cancer in developing countries. We compared the performance of different screening tests and their feasibility in a cohort of over 12,000 women: conventional Pap smear, liquid-based cytology, visual inspection with acetic acid (VIA), visual inspection with Iodine solution (VILI), cervicography, screening colposcopy, and high-risk human papillomavirus (HPV) testing (HR-HPV) collected by physician and by self-sampling. HR-HPV assay collected by the physician has the highest sensitivity (80 %), but high unnecessary referrals to colposcopy (15.1 %). HR-HPV test in self-sampling had a markedly lower (57.1 %) sensitivity. VIA, VILI, and cervicography had a poor sensitivity (47.4, 55, and 28.6 %, respectively). Colposcopy presented with sensitivity of 100 % in detecting CIN2+, but the lowest specificity (66.9 %). Co-testing with VIA and VILI Pap test increased the sensitivity of stand-alone Pap test from 71.6 to 87.1 % and 71.6 to 95 %, respectively, but with high number of unnecessary colposcopies. Co-testing with HR-HPV importantly increased the sensitivity of Pap test (to 86 %), but with high number of unnecessary colposcopies (17.5 %). Molecular tests adjunct to Pap test seems a realistic option to improve the detection of high-grade lesions in population-based screening programs.

Covariates of high-risk human papillomavirus (HPV) infections are distinct for incident CIN1, CIN2 and CIN3 as disclosed by competing-risks regression models

Background: In addition to the oncogenic human papillomavirus (HPV), several cofactors are needed in cervical carcinogenesis, but whether the HPV covariates associated with incident i) CIN1 are different from those of incident ii) CIN2 and iii) CIN3 needs further assessment. Objectives: To gain further insights into the true biological differences between CIN1, CIN2 and CIN3, we assessed HPV covariates associated with incident CIN1, CIN2, and CIN3. Study Design and Methods: HPV covariates associated with progression to CIN1, CIN2 and CIN3 were analysed in the combined cohort of the NIS (n = 3,187) and LAMS study (n = 12,114), using competing-risks regression models (in panel data) for baseline HR-HPV-positive women (n = 1,105), who represent a sub-cohort of all 1,865 women prospectively followed-up in these two studies. Results: Altogether, 90 (4.8%), 39 (2.1%) and 14 (1.4%) cases progressed to CIN1, CIN2, and CIN3, respectively. Among these baseline HR-HPV-positive women, the risk profiles of incident GIN I, CIN2 and CIN3 were unique in that completely different HPV covariates were associated with progression to CIN1, CIN2 and CIN3, irrespective which categories (non-progression, CIN1, CIN2, CIN3 or all) were used as competing-risks events in univariate and multivariate models. Conclusions: These data confirm our previous analysis based on multinomial regression models implicating that distinct covariates of HR-HPV are associated with progression to CIN1, CIN2 and CIN3. This emphasises true biological differences between the three grades of GIN, which revisits the concept of combining CIN2 with CIN3 or with CIN1 in histological classification or used as a common end-point, e.g., in HPV vaccine trials.

Predicting smear negative pulmonary tuberculosis with classification trees and logistic regression: a cross-sectional study

Abstract Background Smear negative pulmonary tuberculosis (SNPT) accounts for 30% of pulmonary tuberculosis cases reported yearly in Brazil. This study aimed to develop a prediction model for SNPT for outpatients in areas with scarce resources. Methods The study enrolled 551 patients with clinical-radiological suspicion of SNPT, in Rio de Janeiro, Brazil. The original data was divided into two equivalent samples for generation and validation of the prediction models. Symptoms, physical signs and chest X-rays were used for constructing logistic regression and classification and regression tree models. From the logistic regression, we generated a clinical and radiological prediction score. The area under the receiver operator characteristic curve, sensitivity, and specificity were used to evaluate the model's performance in both generation and validation samples. Results It was possible to generate predictive models for SNPT with sensitivity ranging from 64% to 71% and specificity ranging from 58% to 76%. Conclusion The results suggest that those models might be useful as screening tools for estimating the risk of SNPT, optimizing the utilization of more expensive tests, and avoiding costs of unnecessary anti-tuberculosis treatment. Those models might be cost-effective tools in a health care network with hierarchical distribution of scarce resources.

Desenvolvimento e avaliação de instrumentos de triagem nutricional

Esse estudo tem por objetivo descrever o desenvolvimento e a avaliação de instrumentos de triagem nutricional para identificação de risco de desnutrição em pacientes hospitalizados. A partir da identificação de variáveis preditivas, o paciente deve ser encaminhado à equipe multidisciplinar de terapia nutricional para intervenção. Foram estudados 300 pacientes de um hospital de São Paulo-SP, aplicada uma avaliação nutricional com levantamento de variáveis de risco e conduzida uma regressão logística múltipla para a seleção dos fatores preditivos. As variáveis associadas à desnutrição foram: perda de peso involuntária, ossatura aparente, redução de apetite, diarreia, ingestão energética inadequada e gênero masculino. Um instrumento de triagem nutricional foi desenvolvido e apresentou adequada concordância com instrumentos validados.