In this work we propose a method for optimal treatment assignment based on individual covariate information for a patient. For the K treatment ([Formula: see text]) scenario, we compare quantities that are suitable surrogates to true conditional probabilities of outcome variable of each treatment dominating outcome variables for all other treatments conditional on patient specific scores constructed from patient-specific covariates. As opposed to methods based on conditional means, our method can be applied for a broad set of models and error structures. Furthermore, the proposed method has very desirable large sample properties. We suggest Single Index Models as appropriate models connecting outcome variables to covariates and our empirical investigations show that correct treatment assignments are highly accurate. The proposed method is also rather robust against departures from a Single Index Model structure. Furthermore, selection of a treatment using the proposed metric appears to incur no losses in terms of the average reward for cases when two treatments are close in terms of this metric. We also conduct a real data analysis to show the applicability of the proposed procedure. This analysis highlights possible gains both in terms of average response and survival time if one were to use the proposed method.

BackgroundDiabetes mellitus, ischemic heart disease, and chronic kidney disease are three major chronic conditions that develop with increasing risks among adults as they get older. The interconnectedness of these three chronic conditions is well known, while each condition acts as a prognostic risk factor for the other two. It is important to understand the progressive relationships of these three conditions over time in terms of transitioning between clinical states and the impact on patients’ survival.MethodsWe investigate the survival characteristics of a Medicare population aged 65 years and above in a multistate system that contained clinical states specified by death and diagnosis combinations of three chronic conditions. The study was conducted using Hawaii Medicare claims data from 2009 to 2013. To evaluate the progression of a subject with one of the newly diagnosed chronic conditions, we analyzed quantities such as state occupation probabilities in eight states and hazards of sixteen transition types. We quantified effects and significances of potential covariates such as age, gender, race/ethnicity, comorbidity burden and financial status on these temporal functions. Nonparametric method of estimating state occupation probabilities and pseudo-value based method for estimating covariate effects of a survival system were utilized.ResultsWe found a range of age, gender, race/ethnicity and financial status based interesting covariate influences on transitions and state occupation probabilities of the system.ConclusionSurvival characteristics of the disease system are influenced by subject-specific effects. Subgroup-specific interventions/screenings should be considered for the optimal prevention and care.Electronic supplementary materialThe online version of this article (10.1186/s12889-018-5688-y) contains supplementary material, which is available to authorized users.

Background Cellular immunometabolism among people living with HIV (PLWH) on antiretroviral therapy (ART) remains under investigated. We assessed the relationships between mitochondrial oxidative phosphorylation (OXPHOS) in peripheral blood mononuclear cells (PBMCs) and blood parameters associated with HIV immune dysregulation. Methods PLWH �40 years old and on stable ART �3 months were enrolled (N = 149). OXPHOS complex I (CI, NADH dehydrogenase) and complex IV (CIV, cytochrome c oxidase) protein levels in PBMCs were quantified using immunoassays. Monocyte subsets and markers of T-cell activation, senescence, and exhaustion were measured on PBMC by flow cytometry. Plasma inflammatory mediators were quantified using a multiplex assay. HIV-uninfected group (N = 44) of similar age, gender, and ethnicity had available OXPHOS levels. Results PLWH had a median age of 51 years. Majority were male (88.6%), Caucasian (57.7%), and with undetectable plasma HIV RNA <50 copies/mL (84.6%). Median CI level was lower in PLWH compared with the HIV-seronegative group (65.5 vs 155.0 optical density/μg protein x 10 3 , p <0.0001). There was no significant difference in median CIV levels. Lower OXPHOS levels correlated with lower CD4% and CD4/CD8 ratio. On multivariable linear regression adjusted for age, current use of zidovudine/didanosine, and HIV RNA (detectable versus undetectable), lower OXPHOS levels were significantly associated with higher MPO, SAA, SAP, and sVCAM, and higher frequencies of intermediate (CD14 ++ CD16 +) monocytes and TIGIT+TIM3+ CD4 T-cell (p<0.01).