A user-friendly nomogram for predicting radioiodine refractory differentiated thyroid cancer

Predicting the individualized risk of human immunodeficiency virus infection among sexually active women in Ethiopia using a nomogram: prediction model development and validation

Introduction

Women are more vulnerable to HIV infection due to biological and socioeconomic reasons. Developing a predictive model for these vulnerable populations to estimate individualized risk for HIV infection is relevant for targeted preventive interventions. The objective of the study was to develop and validate a risk prediction model that allows easy estimations of HIV infection risk among sexually active women in Ethiopia.

Methods

Data from the 2016 Ethiopian Demographic and Health Survey, which comprised 10,253 representative sexually active women, were used for model development. Variables were selected using the least absolute shrinkage and selection operator (LASSO). Variables selected by LASSO were incorporated into the multivariable mixed-effect logistic regression model. Based on the multivariable model, an easy-to-use nomogram was developed to facilitate its applicability. The performance of the nomogram was evaluated using discrimination and calibration abilities, Brier score, sensitivity, and specificity. Internal validation was carried out using the bootstrapping method.

Results

The model selected seven predictors of HIV infection, namely, age, education, marital status, sex of the household head, age at first sex, multiple sexual partners during their lifetime, and residence. The nomogram had a discriminatory power of 89.7% (95% CI: 88.0, 91.5) and a calibration p-value of 0.536. In addition, the sensitivity and specificity of the nomogram were 74.1% (95% CI: 68.4, 79.2) and 80.9% (95% CI: 80.2, 81.7), respectively. The internally validated model had a discriminatory ability of 89.4% (95% CI: 87.7, 91.1) and a calibration p-value of 0.195. Sensitivity and specificity after validation were 72.9% (95% CI: 67.2, 78.2) and 80.1% (95% CI: 79.3, 80.9), respectively.

Conclusion

A new prediction model that quantifies the individualized risk of HIV infection has been developed in the form of a nomogram and internally validated. It has very good discriminatory power and good calibration ability. This model can facilitate the identification of sexually active women at high risk of HIV infection for targeted preventive measures.

Radioactive iodine refractoriness in Middle Eastern differentiated thyroid cancer: clinical outcome and risk factor analysis

Background

Radioactive iodine refractory differentiated thyroid cancer (RAIR-DTC) has received increasing attention due to its poor prognosis. However, outcomes may vary among patients with RAIR-DTC. The role of clinico-pathological and molecular prognostic factors in survival remains controversial, resulting in difficulty in selecting patients for new targeted therapies. We assessed mortality rate and DTC-specific survival in Middle Eastern RAIR-DTC to identify prognostic factors associated with survival.

Methods

This single center, retrospective study enrolled 268 patients with RAIR-DTC. Mortality rate and DTC-specific survival were analyzed to identify prognostic factors related to survival. Univariate and multivariate analysis were performed using Cox proportional hazards model.

Results

Of the 268 cases of RAIR-DTC, 40.3% (108/268) had absent 131I uptake (either on diagnostic or post-therapy whole body scan), 15.3% (41/268) had progressive disease (PD) despite 131I, 7.5% (20/268) had persistent disease despite cumulative activity of I131 of >600 mCi and 36.9% (n=99/268) developed distant metastasis. On multivariate analysis, age (more than 45 years), presence of metastatic disease and tumors harboring telomerase reverse transcriptase (TERT) promoter mutations were independent prognostic factors for poor DTC-specific survival. Subjects were divided into 3 groups according to the number of risk factors; low risk (no risk factors); intermediate (≤ 2 risk factors); and high risk (all the 3 risk factors). Ten-year DTC-specific survival rates in low, intermediate and high-risk groups were 100.0%, 92.9% and 53.6%, respectively.

Conclusions

The contribution of age greater than 45 years to RAIR-DTC mortality is impactful. Older age, presence of distant metastasis and TERT mutations could be used as early predictors of RAIR-DTC cases. The identification of prognostic factors for poor survival in RAIR-DTC may improve the selection of patients for more personalized surveillance and therapeutic modalities.

Clinicopathological features of differentiated thyroid carcinoma as predictors of the effects of radioactive iodine therapy

BACKGROUND

Patients with differentiated thyroid cancer (DTC) usually have an excellent prognosis; however, 5 %-15 % develop radioactive iodine-refractory (RAIR) DTC (RAIR-DTC), which has a poor prognosis and limited treatment options. The aim of the present study was to investigate the clinicopathological characteristics of RAIR-DTC in order to provide clinical evidence for timely prediction of the effects of iodine therapy.

METHODS

Clinicopathological data for 44 patients with RAIR-DTC and 50 patients with radioiodine-avid DTC (RAIA-DTC) were retrospectively analyzed. The risk factors for RAIR-DTC were evaluated and a RAIR-DTC prediction model was established.

RESULTS

RAIR-DTC showed unique clinicopathological features that differed from those of RAIA-DTC; these included age >55 years, a high-risk histological subtype, a large tumor size, a late TNM stage, calcification, distant metastasis, and more than six metastatic lymph nodes. Patients with RAIR-DTC also developed earlier tumor progression. Binary logistic regression analysis showed that distant metastasis, a high-risk histological subtype, and a maximum tumor diameter of ≥12.5 mm were independent risk factors for RAIR-DTC, and the specificity and sensitivity of a combination of these three parameters for the prediction of RAIR-DTC were 98.0 % and 56.8 %, respectively. Decision curve analysis and the calibration curve revealed that the combined prediction of these three parameters had good repeatability and accuracy.

CONCLUSION

The clinicopathological features of DTC can effectively predict the effects of iodine therapy. A combination of distant metastasis, a high-risk histological subtype, and a maximum tumor diameter of ≥12.5 mm showed significantly higher prediction accuracy.