Epidemiological Characteristics and the Development of Prognostic Nomograms of Patients With HIV-Associated Cutaneous T-Cell Lymphoma

Development and Evaluation of a Nomogram for Predicting the Outcome of Immune Reconstitution Among HIV/AIDS Patients Receiving Antiretroviral Therapy in China

This study aims to develop and evaluate a model to predict the immune reconstitution among HIV/AIDS patients after antiretroviral therapy (ART). A total of 502 HIV/AIDS patients are randomized to the training cohort and evaluation cohort. Least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression analysis are performed to identify the indicators and establish the nomogram for predicting the immune reconstitution. Decision curve analysis (DCA) and clinical impact curve (CIC) are used to evaluate the clinical effectiveness of the nomogram. Predictive factors included white blood cells (WBC), baseline CD4+ T-cell counts (baseline CD4), ratio of effector regulatory T cells to resting regulatory T cells (eTreg/rTreg) and low-density lipoprotein cholesterol (LDL-C) and are incorporated into the nomogram. The area under the curve (AUC) is 0.812 (95% CI, 0.767∼0.851) and 0.794 (95%CI, 0.719∼0.857) in the training cohort and evaluation cohort, respectively. The calibration curve shows a high consistency between the predicted and actual observations. Moreover, DCA and CIC indicate that the nomogram has a superior net benefit in predicting poor immune reconstitution. A simple-to-use nomogram containing four routinely collected variables is developed and internally evaluated and can be used to predict the poor immune reconstitution in HIV/AIDS patients after ART.

Clinical Characteristics and Outcomes of AIDS-Related Burkitt Lymphoma in China: A Retrospective Single-Center Study

Objectives: Studies on the prognosis and risk stratification of patients with acquired immune deficiency syndrome (AIDS) - related Burkitt lymphoma (AR-BL) are rare. We aim to construct a novel model to improve the risk assessment of these patients. Methods: We retrospectively analyzed the clinical data of 34 patients over the past 10 years and the factors associated with progression-free survival (PFS) and overall survival (OS) were evaluated in univariate and multivariate Cox models. Then, the novel model consisting of screened factors was compared with the existing models. Results: With a 37-month median follow-up, the overall 2-year PFS and OS rates were 40.50% and 36.18%, respectively. The OS of patients who received chemotherapy was better compared with those without chemotherapy (P = .0012). Treatment with an etoposide, prednisone, oncovin, cyclophosphamide, and hydroxydaunorubicin-based regimen was associated with longer OS and PFS compared with a cyclophosphamide, doxorubicin, vincristine, and prednisone-based regimen (OS, P = .0002; PFS, P = .0158). Chemotherapy (hazard ratio [HR] = 0.075; 95% confidence interval [CI], 0.009-0.614) and Eastern Cooperative Oncology Group Performance Status (ECOG PS) 2 to 4 (HR = 4.738; 95% CI, 1.178-19.061) were independent prognostic factors of OS in multivariate analysis and we established a novel prognostic risk stratification model named GZ8H model with chemotherapy and ECOG PS. Conclusion: GZ8H showed better stratification ability than the international prognostic index (IPI) or Burkitt lymphoma IPI (BL-IPI). Furthermore, the C-index of the nomogram used to predict OS was 0.884 in the entire cohort and the calibration curve showed excellent agreement between the predicted and actual results of OS. No human immunodeficiency virus-related factors were found to be associated with OS and PFS of AR-BL patients in our study. Overall, the clinical characteristics and outcomes in AR-BL were shown and prognostic factors for OS and PFS were identified in this study.

Nomograms for predicting overall survival and cancer-specific survival in patients with head and neck non-Hodgkin lymphoma: A population-based study

This study aimed to develop comprehensive nomograms for patients with head and neck non-Hodgkin lymphoma (H&NNHL) to determine their overall survival (OS) and cancer-specific survival (CSS). In this study, 602 H&NNHL patients were analyzed from the Surveillance, Epidemiology, and End Results database. The R software was used to randomly divide the patients into the training cohort (n = 421) and the validation cohort (n = 181) in a 7-to-3 ratio. To develop nomograms for projecting OS and CSS, multivariable Cox regression was used to acquire independent predictive factors. We have constructed nomograms to predict the 3-, 5-, and 8-year OS and CSS probabilities of H&NNHL patients. The consistency index of the nomograms for OS (CSS) was 0.74 (0.778) and 0.734 (0.775), in the training and validation cohort respectively, and was higher than that of the Ann Arbor staging system. Calibration plotting showed that our models have good calibration ability. Moreover, assessments of the area under the time-dependent receiver operating characteristics curve, net reclassification improvement, integrated discrimination improvement and decision curve analysis demonstrated that our nomograms performed better and were more clinically useful than the Ann Arbor staging system. This is the first research to establish comprehensive nomograms for predicting OS and CSS in patients with H&NNHL at 3-, 5-, and 8-year. The validation of the models demonstrated good performance. It can provide clinicians with reference information for determining customized clinical treatment options and providing personalized prognoses. Indexes such as the concordance index, the area under the time-dependent receiver operating characteristics curve, calibration curves, the net reclassification improvement, the integrated discrimination improvement, and decision-curve analysis were used to compare new survival models to the classical Ann Arbor staging system.