Modelling zero-inflated count data when exposure varies: with an application to tumor counts)

This paper is concerned with the analysis of zero-inflated count data when time of exposure varies. It proposes a modified zero-inflated count data model where the probability of an extra zero is derived from an underlying duration model with Weibull hazard rate. The new model is compared to the standard Poisson model with logit zero inflation in an application to the effect of treatment with thiotepa on the number of new bladder tumors.

Minimum count sums for charcoalconcentration estimates in pollen slides: accuracy and potential errors

Charcoal particles in pollen slides are often abundant, and thus analysts are faced with the problem of setting the minimum counting sum as small as possible in order to save time. We analysed the reliability of charcoal-concentration estimates based on different counting sums, using simulated low-to high-count samples. Bootstrap simulations indicate that the variability of inferred charcoal concentrations increases progressively with decreasing sums. Below 200 items (i.e., the sum of charcoal particles and exotic marker grains), reconstructed fire incidence is either too high or too low. Statistical comparisons show that the means of bootstrap simulations stabilize after 200 counts. Moreover, a count of 200-300 items is sufficient to produce a charcoal-concentration estimate with less than+5% error if compared with high-count samples of 1000 items for charcoal/marker grain ratios 0.1-0.91. If, however, this ratio is extremely high or low (> 0.91 or < 0.1) and if such samples are frequent, we suggest that marker grains are reduced or added prior to new sample processing.

Effect of low count sums on quantitative environmental reconstructions: an example using subfossil chironomids

The concentrations of chironomid remains in lake sediments are very variable and, therefore, chironomid stratigraphies often include samples with a low number of counts. Thus, the effect of low count sums on reconstructed temperatures is an important issue when applying chironomid‐temperature inference models. Using an existing data set, we simulated low count sums by randomly picking subsets of head capsules from surface‐sediment samples with a high number of specimens. Subsequently, a chironomid‐temperature inference model was used to assess how the inferred temperatures are affected by low counts. The simulations indicate that the variability of inferred temperatures increases progressively with decreasing count sums. At counts below 50 specimens, a further reduction in count sum can cause a disproportionate increase in the variation of inferred temperatures, whereas at higher count sums the inferences are more stable. Furthermore, low count samples may consistently infer too low or too high temperatures and, therefore, produce a systematic error in a reconstruction. Smoothing reconstructed temperatures downcore is proposed as a possible way to compensate for the high variability due to low count sums. By combining adjacent samples in a stratigraphy, to produce samples of a more reliable size, it is possible to assess if low counts cause a systematic error in inferred temperatures.

CD4 count at antiretroviral therapy initiation and the risk of loss to follow-up: results from a multicentre cohort study.

BACKGROUND Antiretroviral therapy (ART) initiation is now recommended irrespective of CD4 count. However data on the relationship between CD4 count at ART initiation and loss to follow-up (LTFU) are limited and conflicting. METHODS We conducted a cohort analysis including all adults initiating ART (2008-2012) at three public sector sites in South Africa. LTFU was defined as no visit in the 6 months before database closure. The Kaplan-Meier estimator and Cox's proportional hazards models examined the relationship between CD4 count at ART initiation and 24-month LTFU. Final models were adjusted for demographics, year of ART initiation, programme expansion and corrected for unascertained mortality. RESULTS Among 17 038 patients, the median CD4 at initiation increased from 119 (IQR 54-180) in 2008 to 257 (IQR 175-318) in 2012. In unadjusted models, observed LTFU was associated with both CD4 counts <100 cells/μL and CD4 counts ≥300 cells/μL. After adjustment, patients with CD4 counts ≥300 cells/μL were 1.35 (95% CI 1.12 to 1.63) times as likely to be LTFU after 24 months compared to those with a CD4 150-199 cells/μL. This increased risk for patients with CD4 counts ≥300 cells/μL was largest in the first 3 months on treatment. Correction for unascertained deaths attenuated the association between CD4 counts <100 cells/μL and LTFU while the association between CD4 counts ≥300 cells/μL and LTFU persisted. CONCLUSIONS Patients initiating ART at higher CD4 counts may be at increased risk for LTFU. With programmes initiating patients at higher CD4 counts, models of ART delivery need to be reoriented to support long-term retention.

When to Monitor CD4 Cell Count and HIV RNA to Reduce Mortality and AIDS-Defining Illness in Virologically Suppressed HIV-Positive Persons on Antiretroviral Therapy in High-Income Countries: A Prospective Observational Study.

OBJECTIVE To illustrate an approach to compare CD4 cell count and HIV-RNA monitoring strategies in HIV-positive individuals on antiretroviral therapy (ART). DESIGN Prospective studies of HIV-positive individuals in Europe and the USA in the HIV-CAUSAL Collaboration and The Center for AIDS Research Network of Integrated Clinical Systems. METHODS Antiretroviral-naive individuals who initiated ART and became virologically suppressed within 12 months were followed from the date of suppression. We compared 3 CD4 cell count and HIV-RNA monitoring strategies: once every (1) 3 ± 1 months, (2) 6 ± 1 months, and (3) 9-12 ± 1 months. We used inverse-probability weighted models to compare these strategies with respect to clinical, immunologic, and virologic outcomes. RESULTS In 39,029 eligible individuals, there were 265 deaths and 690 AIDS-defining illnesses or deaths. Compared with the 3-month strategy, the mortality hazard ratios (95% CIs) were 0.86 (0.42 to 1.78) for the 6 months and 0.82 (0.46 to 1.47) for the 9-12 month strategy. The respective 18-month risk ratios (95% CIs) of virologic failure (RNA >200) were 0.74 (0.46 to 1.19) and 2.35 (1.56 to 3.54) and 18-month mean CD4 differences (95% CIs) were -5.3 (-18.6 to 7.9) and -31.7 (-52.0 to -11.3). The estimates for the 2-year risk of AIDS-defining illness or death were similar across strategies. CONCLUSIONS Our findings suggest that monitoring frequency of virologically suppressed individuals can be decreased from every 3 months to every 6, 9, or 12 months with respect to clinical outcomes. Because effects of different monitoring strategies could take years to materialize, longer follow-up is needed to fully evaluate this question.

The normal range of the leukocyte count: Implications for surveillance of occupational and environmental exposure and the practice of preventive medicine

Leukopenia, the leukocyte count, and prognosis of disease are interrelated; a systematic search of the literature was undertaken to ascertain the strength of the evidence. One hundred seventy-one studies were found from 1953 onward pertaining to the predictive capabilities of the leukocyte count. Of those studies, 42 met inclusion criteria. An estimated range of 2,200cells/μL to 7,000cells/μL was determined as that which indicates good prognosis in disease and indicates the least amount of risk to an individual overall. Tables of the evidence are included indicating the disparate populations examined and the possible degree of association. ^

Determinants of CD4 cell count decline after treatment interruption

Patients who had started HAART (Highly Active Anti-Retroviral Treatment) under previous aggressive DHHS guidelines (1997) underwent a life-long continuous HAART that was associated with many short term as well as long term complications. Many interventions attempted to reduce those complications including intermittent treatment also called pulse therapy. Many studies were done to study the determinants of rate of fall in CD4 count after interruption as this data would help guide treatment interruptions. The data set used here was a part of a cohort study taking place at the Johns Hopkins AIDS service since January 1984, in which the data were collected both prospectively and retrospectively. The patients in this data set consisted of 47 patients receiving via pulse therapy with the aim of reducing the long-term complications. ^ The aim of this project was to study the impact of virologic and immunologic factors on the rate of CD4 loss after treatment interruption. The exposure variables under investigation included CD4 cell count and viral load at treatment initiation. The rates of change of CD4 cell count after treatment interruption was estimated from observed data using advanced longitudinal data analysis methods (i.e., linear mixed model). Using random effects accounted for repeated measures of CD4 per person after treatment interruption. The regression coefficient estimates from the model was then used to produce subject specific rates of CD4 change accounting for group trends in change. The exposure variables of interest were age, race, and gender, CD4 cell counts and HIV RNA levels at HAART initiation. ^ The rate of fall of CD4 count did not depend on CD4 cell count or viral load at initiation of treatment. Thus these factors may not be used to determine who can have a chance of successful treatment interruption. CD4 and viral load were again studied by t-tests and ANOVA test after grouping based on medians and quartiles to see any difference in means of rate of CD4 fall after interruption. There was no significant difference between the groups suggesting that there was no association between rate of fall of CD4 after treatment interruption and above mentioned exposure variables. ^

The association between CD4+ lymphocyte count and measures of body composition in HIV-infected men

Purpose. This project was designed to describe the association between wasting and CD4 cell counts in HIV-infected men in order to better understand the role of wasting in progression of HIV infection.^ Methods. Baseline and prevalence data were collected from a cross-sectional survey of 278 HIV-infected men seen at the Houston Veterans Affairs Medical Center Special Medicine Clinic, from June 1, 1991 to January 1, 1994. A follow-up study was conducted among those at risk, to investigate the incidence of wasting and the association between wasting and low CD4 cell counts. Wasting was described by four methods. Z-scores for age-, sex-, and height-adjusted weight; sex-, and age-adjusted mid-arm muscle circumference (MAMC); and fat-free mass; and the ratio of extra-cellular mass (ECM) to body-cell mass (BCM) $>$ 1.20. FFM, ECM, and BCM were estimated from bioelectrical impedance analysis. MAMC was calculated from triceps skinfold and mid-arm circumference. The relationship between wasting and covariates was examined with logistic regression in the cross-sectional study, and with Poisson regression in the follow-up study. The association between death and wasting was examined with Cox's regression.^ Results. The prevalence of wasting ranged from 5% (weight and ECM:BCM) to almost 14% (MAMC and FFM) among the 278 men examined. The odds of wasting, associated with baseline CD4 cell count $<$200, was significant for each method but weight, and ranged from 4.6 to 12.7. Use of antiviral therapy was significantly protective of MAMC, FFM and ECM:BCM (OR $\approx$ 0.2), whereas the need for antibacterial therapy was a risk (OR 3.1, 95% CI 1.1-8.7). The average incidence of wasting ranged from 4 to 16 per 100 person-years among the approximately 145 men followed for 160 person-years. Low CD4 cell count seemed to increase the risk of wasting, but statistical significance was not reached. The effect of the small sample size on the power to detect a significant association should be considered. Wasting, by MAMC and FFM, was significantly associated with death, after adjusting for baseline serum albumin concentration and CD4 cell count.^ Conclusions. Wasting by MAMC and FFM were strongly associated with baseline CD4 cell counts in both the prevalence and incidence study and strong predictors of death. Of the two methods, MAMC is convenient, has available reference population data, may be the most appropriate for assessing the nutritional status of HIV-infected men. ^

CHARACTERIZATION OF THE COUNT RATE PERFORMANCE AND EVALUATION OF THE EFFECTS OF HIGH COUNT RATES ON MODERN GAMMA CAMERAS

CHARACTERIZATION OF THE COUNT RATE PERFORMANCE AND EVALUATION OF THE EFFECTS OF HIGH COUNT RATES ON MODERN GAMMA CAMERAS Michael Stephen Silosky, B.S. Supervisory Professor: S. Cheenu Kappadath, Ph.D. Evaluation of count rate performance (CRP) is an integral component of gamma camera quality assurance and measurement of system dead time (τ) is important for quantitative SPECT. The CRP of three modern gamma cameras was characterized using established methods (Decay and Dual Source) under a variety of experimental conditions. For the Decay method, input count rate was plotted against observed count rate and fit to the paralyzable detector model (PDM) to estimate τ (Rates method). A novel expression for observed counts as a function of measurement time interval was derived and the observed counts were fit to this expression to estimate τ (Counts method). Correlation and Bland-Altman analysis were performed to assess agreement in estimates of τ between methods. The dependencies of τ on energy window definition and incident energy spectrum were characterized. The Dual Source method was also used to estimate τ and its agreement with the Decay method under identical conditions and the effects of total activity and the ratio of source activities were investigated. Additionally, the effects of count rate on several performance metrics were evaluated. The CRP curves for each system agreed with the PDM at low count rates but deviated substantially at high count rates. Estimates of τ for the paralyzable portion of the CRP curves using the Rates and Counts methods were highly correlated (r=0.999) but with a small (~6%) difference. No significant difference was observed between the highly correlated estimates of τ using the Decay or Dual Source methods under identical experimental conditions (r=0.996). Estimates of τ increased as a power-law function with decreasing ratio of counts in the photopeak to the total counts and linearly with decreasing spectral effective energy. Dual Source method estimates of τ varied as a quadratic with the ratio of the single source to combined source activities and linearly with total activity used across a large range. Image uniformity, spatial resolution, and energy resolution degraded linearly with count rate and image distorting effects were observed. Guidelines for CRP testing and a possible method for the correction of count rate losses for clinical images have been proposed.