Abstract
BackgroundThe purpose of this study is to propose the Least Absolute Shrinkage and Selection Operators procedure (LASSO) as an alternative to conventional variable selection models, as it allows for easy interpretation and handles multicollinearities. We developed a model on the basis of LASSO-selected parameters in order to link associated demographical, socio-economical, clinical and immunological factors to performing tuberculosis screening in HIV-positive patients in Ghana.MethodsApplying the LASSO method and multivariate logistic regression analysis on a large public health data set, we selected relevant predictors related to tuberculosis screening.ResultsOne Thousand Ninety Five patients infected with HIV were enrolled into this study with 691 (63.2 %) of them having tuberculosis screening documented in their patient folders. Predictors found to be significantly associated with performance of tuberculosis screening can be classified into factors related to the clinician’s perception of the clinical state, as well as those related to PLHIV’s awareness. These factors include newly diagnosed HIV infections (n = 354 (32.42 %), aOR 1.84), current CD4+ T cell count (aOR 0.92), non-availability of HIV type (n = 787 (72.07 %), aOR 0.56), chronic cough (n = 32 (2.93 %), aOR 5.07), intake of co-trimoxazole (n = 271 (24.82 %), aOR 2.31), vitamin supplementation (n = 220 (20.15 %), aOR 2.64) as well as the use of mosquito bed nets (n = 613 (56.14 %), aOR 1.53).ConclusionsAccelerated TB screening among newly diagnosed HIV-patients indicates that application of the WHO screening form for intensifying tuberculosis case finding among HIV-positive individuals in resource-limited settings is increasingly adopted. However, screening for TB in PLHIV is still impacted by clinician’s perception of patient’s health state and PLHIV’s health awareness. Education of staff, counselling of PLHIV and sufficient financing are needed for further improvement in implementation of TB screening for all PLHIV. The LASSO approach proved a convenient method for automatic variable selection in a large public health data set that requires efficient and fast algorithms.Trials registrationClinicalTrials.gov NCT01897909 (July 5, 2013).
Highlights
The purpose of this study is to propose the Least Absolute Shrinkage and Selection Operators procedure (LASSO) as an alternative to conventional variable selection models, as it allows for easy interpretation and handles multicollinearities
Results show that a high CD4+ T cell count and high haemoglobin, which indicate a good control of the Human Immunodeficiency Virus (HIV)-infection, are negatively associated with TB screening, whereas chronic coughing during the past six months, which is a possible sign of active TB, is positively associated but does not trigger TB screening in every case
These findings demonstrate that TB screening is still related to current health status as it was practice before the World Health Organization (WHO) recommended TB screening as standard procedure regardless of the patient’s disease progress
Summary
The purpose of this study is to propose the Least Absolute Shrinkage and Selection Operators procedure (LASSO) as an alternative to conventional variable selection models, as it allows for easy interpretation and handles multicollinearities. Detecting relevant predictors for an outcome using conventional explorative data analysis frameworks, such as running univariate regression tests for each potential preventive or risk factor and thereafter including those parameters with p < 0.05 into a multivariate regression model using forward or backward variable selection is time-consuming for large data sets. Many risk or preventive factors are not convenient for translating evidence into public health practice because clinicians are usually short of time and unable to consider more than a handful parameters for decisionmaking during routine work [3] They rather rely on their individual clinical experience than on evidencebased interrelationships if these are too complex [4]
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