Regression of ranked responses when raw responses are censored

We discuss semiparametric regression when only the ranks of responses are observed. The model is $Y_i = F (\mathbf{x}_i'{\boldsymbol\beta}_0 + \varepsilon_i)$, where $Y_i$ is the unobserved response, $F$ is a monotone increasing function, $\mathbf{x}_i$ is a known $p-$vector of covariates, ${\boldsymbol\beta}_0$ is an unknown $p$-vector of interest, and $\varepsilon_i$ is an error term independent of $\mathbf{x}_i$. We observe $\{(\mathbf{x}_i,R_n(Y_i)) : i = 1,\ldots ,n\}$, where $R_n$ is the ordinal rank function. We explore a novel estimator under Gaussian assumptions. We discuss the literature, apply the method to an Alzheimer's disease biomarker, conduct simulation studies, and prove consistency and asymptotic normality.Comment: 33 pages, 6 figure

A multicenter assessment of interreader reliability of LI-RADS version 2018 for MRI and CT

Background: Various limitations have impacted research evaluating reader agreement for Liver Imaging-Reporting and Data System (LI-RADS). Purpose: To assess reader agreement of LI-RADS in an international multi-center, multireader setting using scrollable images. Materials and Methods: This retrospective study used de-identified clinical multiphase CT and MRI examinations and reports with at least one untreated observation from six institutions and three countries; only qualifying examinations were submitted. Examination dates were October 2017 – August 2018 at the coordinating center. One untreated observation per examination was randomly selected using observation identifiers, and its clinically assigned features were extracted from the report. The corresponding LI-RADS v2018 category was computed as a re-scored clinical read. Each examination was randomly assigned to two of 43 research readers who independently scored the observation. Agreement for an ordinal modified four-category LI-RADS scale (LR-1/2, LR-3, LR-4, LR-5/M/tumor in vein) was computed using intra-class correlation coefficients (ICC). Agreement was also computed for dichotomized malignancy (LR-4/LR5/LR-M/LR-tumor in vein), LR-5, and LR-M. Agreement was compared between researchversus-research reads and research-versus-clinical reads. Results: 484 patients (mean age, 62 years ±10 [SD]; 156 women; 93 CT, 391 MRI) were included. ICCs for ordinal LI-RADS, dichotomized malignancy, LR-5, and LR-M were 0.68 (95% CI: 0.62, 0.74), 0.63 (95% CI: 0.56, 0.71), 0.58 (95% CI: 0.50, 0.66), and 0.46 (95% CI: 0.31, 0.61) respectively. Research-versus-research reader agreement was higher than research-versus-clinical agreement for modified four-category LI-RADS (ICC, 0.68 vs. 0.62, P = .03) and for dichotomized malignancy (ICC, 0.63 vs. 0.53, P = .005), but not for LR-5 (P = .14) or LR-M (P = .94). Conclusion: There was moderate agreement for Liver Imaging-Reporting and Data System v2018 overall. For some comparisons, research-versus-research reader agreement was higher than research-versus-clinical reader agreement, indicating differences between the clinical and research environments that warrant further study

HIV-associated neurocognitive disorders before and during the era of combination antiretroviral therapy: differences in rates, nature, and predictors

Combination antiretroviral therapy (CART) has greatly reduced medical morbidity and mortality with HIV infection, but high rates of HIV-associated neurocognitive disorders (HAND) continue to be reported. Because large HIV-infected (HIV+) and uninfected (HIV−) groups have not been studied with similar methods in the pre-CART and CART eras, it is unclear whether CART has changed the prevalence, nature, and clinical correlates of HAND. We used comparable methods of subject screening and assessments to classify neurocognitive impairment (NCI) in large groups of HIV + and HIV − participants from the pre-CART era (1988–1995; N = 857) and CART era (2000–2007; N = 937). Impairment rate increased with successive disease stages (CDC stages A, B, and C) in both eras: 25%, 42%, and 52% in pre-CART era and 36%, 40%, and 45% in CART era. In the medically asymptomatic stage (CDC-A), NCI was significantly more common in the CART era. Low nadir CD4 predicted NCI in both eras, whereas degree of current immunosuppression, estimated duration of infection, and viral suppression in CSF (on treatment) were related to impairment only pre-CART. Pattern of NCI also differed: pre-CART had more impairment in motor skills, cognitive speed, and verbal fluency, whereas CART era involved more memory (learning) and executive function impairment. High rates of mild NCI persist at all stages of HIV infection, despite improved viral suppression and immune reconstitution with CART. The consistent association of NCI with nadir CD4 across eras suggests that earlier treatment to prevent severe immunosuppression may also help prevent HAND. Clinical trials targeting HAND prevention should specifically examine timing of ART initiation

Regression of ranked responses when raw responses are censored

We discuss semiparametric regression when only the ranks of responses are observed. The model is $Y_i = F (\mathbf{x}_i'{\boldsymbol\beta}_0 + \varepsilon_i)$, where $Y_i$ is the unobserved response, $F$ is a monotone increasing function, $\mathbf{x}_i$ is a known $p-$vector of covariates, ${\boldsymbol\beta}_0$ is an unknown $p$-vector of interest, and $\varepsilon_i$ is an error term independent of $\mathbf{x}_i$. We observe $\{(\mathbf{x}_i,R_n(Y_i)) : i = 1,\ldots ,n\}$, where $R_n$ is the ordinal rank function. We explore a novel estimator under Gaussian assumptions. We discuss the literature, apply the method to an Alzheimer's disease biomarker, conduct simulation studies, and prove consistency and asymptotic normality

More "mapping" in brain mapping: statistical comparison of effects.

The term "mapping" in the context of brain imaging conveys to most the concept of localization; that is, a brain map is meant to reveal a relationship between some condition or parameter and specific sites within the brain. However, in reality, conventional voxel-based maps of brain function, or for that matter of brain structure, are generally constructed using analyses that yield no basis for inferences regarding the spatial nonuniformity of the effects. In the normal analysis path for functional images, for example, there is nowhere a statistical comparison of the observed effect in any voxel relative to that in any other voxel. Under these circumstances, strictly speaking, the presence of significant activation serves as a legitimate basis only for inferences about the brain as a unit. In their discussion of results, investigators rarely are content to confirm the brain's role, and instead generally prefer to interpret the spatial patterns they have observed. Since "pattern" implies nonuniform effects over the map, this is equivalent to interpreting results without bothering to test their significance, a practice most of the experimentally-trained would eschew in other contexts. In this review, we appeal to investigators to adopt a new standard of data presentation that facilitates comparison of effects across the map. Evidence for sufficient effect size difference between the effects in structures of interest should be a prerequisite to the interpretation of spatial patterns of activation

A Comparison of E-Cigarette Use Patterns and Smoking Cessation Behavior among Vapers by Primary Place of Purchase

Background: E-cigarettes are purchased through multiple channels, including general retail, online, and specialty smoke and vape shops. We examine how e-cigarette users’ primary purchase place relates to e-cigarette use and smoking cessation behaviors. Methods: Probability-based samples of the U.S. population who were current e-cigarette users were surveyed in 2014 (N = 879) and 2016 (N = 743), with responses combined for most analyses. E-cigarette use and smoking cessation behaviors were compared across users’ primary purchase place. Results: Higher percentages of vape shop (59.1%) and internet (42.9%) customers were current daily users of e-cigarettes compared to retail (19.7%) and smoke shop (23.2%) customers (p-values < 0.001). Higher percentages of vape shop (40.2%) and internet (35.1%) customers were also former smokers, compared to 17.7% of retail and 19.3% of smoke shop customers (p’s < 0.001). Among those smoking 12 months prior to survey, smoking cessation rates were higher for vape shop (22.2%) and internet customers (22.5%) than for retail customers (10.7%, p = 0.010 and p = 0.022, respectively), even though retail customers were more likely to use FDA-approved smoking cessation aids. The percentage of customers purchasing from vape shops increased from 20.4% in 2014 to 37.6% in 2016, surpassing general retail (27.7%) as the most likely channel in 2016. Conclusions: E-cigarette customers differed in significant ways by channels of purchase, most notably in their smoking cessation behaviors. Previous population studies have relied mostly on retail channel data, which accounted for less than 30% of all products sold by 2016. Future studies of e-cigarette use should consider a broader set of channels