Causal Inference in Observational Studies with Outcome-Dependent Sampling

In this paper, we consider estimation of the causal effect of a treatment on an outcome from observational data collected in two phases. In the first phase, a simple random sample of individuals are drawn from a population. On these individuals, information is obtained on treatment, outcome, and a few low-dimensional confounders. These individuals are then stratified according to these factors. In the second phase, a random sub-sample of individuals are drawn from each stratum, with known, stratum-specific selection probabilities. On these individuals, a rich set of confounding factors are collected. In this setting, we introduce four estimators: (1) simple inverse weighted, (2) locally efficient, (3) doubly robust and (4)enriched inverse weighted. We evaluate the finite-sample performance of these estimators in a simulation study. We also use our methodology to estimate the causal effect of trauma care on in-hospital mortality using data from the National Study of Cost and Outcomes of Trauma.

Improved effectiveness of partner notification for patients with sexually transmitted infections: systematic review

OBJECTIVE: To examine the effectiveness of methods to improve partner notification by patient referral (index patient has responsibility for informing sex partners of their exposure to a sexually transmitted infection). DESIGN: Systematic review of randomised trials of any intervention to supplement simple patient referral. DATA SOURCES: Seven electronic databases searched (January 1990 to December 2005) without language restriction, and reference lists of retrieved articles. REVIEW METHODS: Selection of trials, data extraction, and quality assessment were done by two independent reviewers. The primary outcome was a reduction of incidence or prevalence of sexually transmitted infections in index patients. If this was not reported data were extracted according to a hierarchy of secondary outcomes: number of partners treated; number of partners tested or testing positive; and number of partners notified, located, or elicited. Random effects meta-analysis was carried out when appropriate. RESULTS: 14 trials were included with 12 389 women and men diagnosed as having gonorrhoea, chlamydia, non-gonococcal urethritis, trichomoniasis, or a sexually transmitted infection syndrome. All studies had methodological weaknesses that could have biased their results. Three strategies were used. Six trials examined patient delivered partner therapy. Meta-analysis of five of these showed a reduced risk of persistent or recurrent infection in patients with chlamydia or gonorrhoea (summary risk ratio 0.73, 95% confidence interval 0.57 to 0.93). Supplementing patient referral with information for partners was as effective as patient delivered partner therapy. Neither strategy was effective in women with trichomoniasis. Two trials found that providing index patients with chlamydia with sampling kits for their partners increased the number of partners who got treated. CONCLUSIONS: Involving index patients in shared responsibility for the management of sexual partners improves outcomes. Health professionals should consider the following strategies for the management of individual patients: patient delivered partner therapy, home sampling for partners, and providing additional information for partners.

Delays in childhood immunization in a conflict area: a study from Sierra Leone during civil war

ABSTRACT: BACKGROUND: Sierra Leone has undergone a decade of civil war from 1991 to 2001. From this period few data on immunization coverage are available, and conflict-related delays in immunization according to the Expanded Programme on Immunization (EPI) schedule have not been investigated. We aimed to study delays in childhood immunization in the context of civil war in a Sierra Leonean community. METHODS: We conducted an immunization survey in Kissy Mess-Mess in the Greater Freetown area in 1998/99 using a two-stage sampling method. Based on immunization cards and verbal history we collected data on immunization for tuberculosis, diphtheria, tetanus, pertussis, polio, and measles by age group (0-8/9-11/12-23/24-35 months). We studied differences between age groups and explored temporal associations with war-related hostilities taking place in the community. RESULTS: We included 286 children who received 1690 vaccine doses; card retention was 87%. In 243 children (85%, 95% confidence interval (CI): 80-89%) immunization was up-to-date. In 161 of these children (56%, 95%CI: 50-62%) full age-appropriate immunization was achieved; in 82 (29%, 95%CI: 24-34%) immunization was not appropriate for age. In the remaining 43 children immunization was partial in 37 (13%, 95%CI: 9-17) and absent in 6 (2%, 95%CI: 1-5). Immunization status varied across age groups. In children aged 9-11 months the proportion with age-inappropriate (delayed) immunization was higher than in other age groups suggesting an association with war-related hostilities in the community. CONCLUSION: Only about half of children under three years received full age-appropriate immunization. In children born during a period of increased hostilities, immunization was mostly inappropriate for age, but recommended immunizations were not completely abandoned. Missing or delayed immunization represents an additional threat to the health of children living in conflict areas.

Measurement of the 1s-2s energy interval in muonium

The 1s-2s interval has been measured in the muonium (;mgr;(+)e(-)) atom by Doppler-free two-photon pulsed laser spectroscopy. The frequency separation of the states was determined to be 2 455 528 941.0(9.8) MHz, in good agreement with quantum electrodynamics. The result may be interpreted as a measurement of the muon-electron charge ratio as -1-1.1(2.1)x10(-9). We expect significantly higher accuracy at future high flux muon sources and from cw laser technology.

HIV-1 coreceptor usage and CXCR4-specific viral load predict clinical disease progression during combination antiretroviral therapy

BACKGROUND: Although combination antiretroviral therapy (cART) dramatically reduces rates of AIDS and death, a minority of patients experience clinical disease progression during treatment. OBJECTIVE: To investigate whether detection of CXCR4(X4)-specific strains or quantification of X4-specific HIV-1 load predict clinical outcome. METHODS: From the Swiss HIV Cohort Study, 96 participants who initiated cART yet subsequently progressed to AIDS or death were compared with 84 contemporaneous, treated nonprogressors. A sensitive heteroduplex tracking assay was developed to quantify plasma X4 and CCR5 variants and resolve HIV-1 load into coreceptor-specific components. Measurements were analyzed as cofactors of progression in multivariable Cox models adjusted for concurrent CD4 cell count and total viral load, applying inverse probability weights to adjust for sampling bias. RESULTS: Patients with X4 variants at baseline displayed reduced CD4 cell responses compared with those without X4 strains (40 versus 82 cells/microl; P = 0.012). The adjusted multivariable hazard ratio (HR) for clinical progression was 4.8 [95% confidence interval (CI) 2.3-10.0] for those demonstrating X4 strains at baseline. The X4-specific HIV-1 load was a similarly independent predictor, with HR values of 3.7 (95% CI, 1.2-11.3) and 5.9 (95% CI, 2.2-15.0) for baseline loads of 2.2-4.3 and > 4.3 log10 copies/ml, respectively, compared with < 2.2 log10 copies/ml. CONCLUSIONS: HIV-1 coreceptor usage and X4-specific viral loads strongly predicted disease progression during cART, independent of and in addition to CD4 cell count or total viral load. Detection and quantification of X4 strains promise to be clinically useful biomarkers to guide patient management and study HIV-1 pathogenesis.

The performance of computer-aided detection when analyzing prior mammograms of newly detected breast cancers with special focus on the time interval from initial imaging to detection

PURPOSE: The clinical role of CAD systems to detect breast cancer, which have not been on cancer containing mammograms not detected by the radiologist was proven retrospectively. METHODS: All patients from 1992 to 2005 with a histologically verified malignant breast lesion and a mammogram at our department, were analyzed in retrospect focussing on the time of detection of the malignant lesion. All prior mammograms were analyzed by CAD (CADx, USA). The resulting CAD printout was matched with the cancer containing images yielding to the radiological diagnosis of breast cancer. CAD performance, sensitivity as well as the association of CAD and radiological features were analyzed. RESULTS: 278 mammograms fulfilled the inclusion criteria. 111 cases showed a retrospectively visible lesion (71 masses, 23 single microcalcification clusters, 16 masses with microcalcifications, in one case two microcalcification clusters). 54/87 masses and 34/41 microcalcifications were detected by CAD. Detection rates varied from 9/20 (ACR 1) to 5/7 (ACR 4) (45% vs. 71%). The detection of microcalcifications was not influenced by breast tissue density. CONCLUSION: CAD might be useful in an earlier detection of subtle breast cancer cases, which might remain otherwise undetected.

Influence of antibiotic dose, dosing interval, and duration of therapy on outcome in experimental pneumococcal meningitis in rabbits

We examined the influence of several pharmacokinetic parameters on cure rates in rabbits with experimental pneumococcal meningitis. When the duration of treatment was kept constant, cure rates improved as the individual dose of ampicillin was increased. On the other hand, when four doses of ampicillin at 60 mg/kg of body weight, producing peak concentrations in cerebrospinal fluid (CSF) of approximately 40 times the MBC, were administered at intervals of 24 instead of 4 h and the duration of therapy was thus prolonged from 12 to 72 h, cure rates also increased (85 versus 25%; P less than 0.01). These high cure rates were achieved even though bacterial titers in CSF 24 h after the first dose had reached levels similar to those present at the beginning of therapy. Cure in these animals was explained by the fact that the second ampicillin dose reduced bacterial titers in CSF significantly more than did the first dose (5.2 versus 2.5 log10 CFU/ml; P less than 0.02). The clinical relevance of these observations remains to be determined.

Similarities in the Subgingival Microbiota Assessed by a Curet Sampling Method at Sites With Chronic Periodontitis

Background: The goal of this study was to determine whether site-specific differences in the subgingival microbiota could be detected by the checkerboard method in subjects with periodontitis. Methods: Subjects with at least six periodontal pockets with a probing depth (PD) between 5 and 7 mm were enrolled in the study. Subgingival plaque samples were collected with sterile curets by a single-stroke procedure at six selected periodontal sites from 161 subjects (966 subgingival sites). Subgingival bacterial samples were assayed with the checkerboard DNA-DNA hybridization method identifying 37 species. Results: Probing depths of 5, 6, and 7 mm were found at 50% (n = 483), 34% (n = 328), and 16% (n = 155) of sites, respectively. Statistical analysis failed to demonstrate differences in the sum of bacterial counts by tooth type (P = 0.18) or specific location of the sample (P = 0.78). With the exceptions of Campylobacter gracilis (P <0.001) and Actinomyces naeslundii (P <0.001), analysis by general linear model multivariate regression failed to identify subject or sample location factors as explanatory to microbiologic results. A trend of difference in bacterial load by tooth type was found for Prevotella nigrescens (P <0.01). At a cutoff level of >/=1.0 x 10(5), Porphyromonas gingivalis and Tannerella forsythia (previously T. forsythensis) were present at 48.0% to 56.3% and 46.0% to 51.2% of sampled sites, respectively. Conclusions: Given the similarities in the clinical evidence of periodontitis, the presence and levels of 37 species commonly studied in periodontitis are similar, with no differences between molar, premolar, and incisor/cuspid subgingival sites. This may facilitate microbiologic sampling strategies in subjects during periodontal therapy.

Hermitian curve interpolation for CT-data re-sampling

Purpose: Development of an interpolation algorithm for re‐sampling spatially distributed CT‐data with the following features: global and local integral conservation, avoidance of negative interpolation values for positively defined datasets and the ability to control re‐sampling artifacts. Method and Materials: The interpolation can be separated into two steps: first, the discrete CT‐data has to be continuously distributed by an analytic function considering the boundary conditions. Generally, this function is determined by piecewise interpolation. Instead of using linear or high order polynomialinterpolations, which do not fulfill all the above mentioned features, a special form of Hermitian curve interpolation is used to solve the interpolation problem with respect to the required boundary conditions. A single parameter is determined, by which the behavior of the interpolation function is controlled. Second, the interpolated data have to be re‐distributed with respect to the requested grid. Results: The new algorithm was compared with commonly used interpolation functions based on linear and second order polynomial. It is demonstrated that these interpolation functions may over‐ or underestimate the source data by about 10%–20% while the parameter of the new algorithm can be adjusted in order to significantly reduce these interpolation errors. Finally, the performance and accuracy of the algorithm was tested by re‐gridding a series of X‐ray CT‐images. Conclusion: Inaccurate sampling values may occur due to the lack of integral conservation. Re‐sampling algorithms using high order polynomialinterpolation functions may result in significant artifacts of the re‐sampled data. Such artifacts can be avoided by using the new algorithm based on Hermitian curve interpolation

Proteins in silico-modeling and sampling

Proteins are linear chain molecules made out of amino acids. Only when they fold to their native states, they become functional. This dissertation aims to model the solvent (environment) effect and to develop & implement enhanced sampling methods that enable a reliable study of the protein folding problem in silico. We have developed an enhanced solvation model based on the solution to the Poisson-Boltzmann equation in order to describe the solvent effect. Following the quantum mechanical Polarizable Continuum Model (PCM), we decomposed net solvation free energy into three physical terms– Polarization, Dispersion and Cavitation. All the terms were implemented, analyzed and parametrized individually to obtain a high level of accuracy. In order to describe the thermodynamics of proteins, their conformational space needs to be sampled thoroughly. Simulations of proteins are hampered by slow relaxation due to their rugged free-energy landscape, with the barriers between minima being higher than the thermal energy at physiological temperatures. In order to overcome this problem a number of approaches have been proposed of which replica exchange method (REM) is the most popular. In this dissertation we describe a new variant of canonical replica exchange method in the context of molecular dynamic simulation. The advantage of this new method is the easily tunable high acceptance rate for the replica exchange. We call our method Microcanonical Replica Exchange Molecular Dynamic (MREMD). We have described the theoretical frame work, comment on its actual implementation, and its application to Trp-cage mini-protein in implicit solvent. We have been able to correctly predict the folding thermodynamics of this protein using our approach.

Sampling-Design Effects on Properties of Species-Area Relationships - A Case Study from Estonian Dry Grassland Communities

Despite widespread use of species-area relationships (SARs), dispute remains over the most representative SAR model. Using data of small-scale SARs of Estonian dry grassland communities, we address three questions: (1) Which model describes these SARs best when known artifacts are excluded? (2) How do deviating sampling procedures (marginal instead of central position of the smaller plots in relation to the largest plot; single values instead of average values; randomly located subplots instead of nested subplots) influence the properties of the SARs? (3) Are those effects likely to bias the selection of the best model? Our general dataset consisted of 16 series of nested-plots (1 cm(2)-100 m(2), any-part system), each of which comprised five series of subplots located in the four corners and the centre of the 100-m(2) plot. Data for the three pairs of compared sampling designs were generated from this dataset by subsampling. Five function types (power, quadratic power, logarithmic, Michaelis-Menten, Lomolino) were fitted with non-linear regression. In some of the communities, we found extremely high species densities (including bryophytes and lichens), namely up to eight species in 1 cm(2) and up to 140 species in 100 m(2), which appear to be the highest documented values on these scales. For SARs constructed from nested-plot average-value data, the regular power function generally was the best model, closely followed by the quadratic power function, while the logarithmic and Michaelis-Menten functions performed poorly throughout. However, the relative fit of the latter two models increased significantly relative to the respective best model when the single-value or random-sampling method was applied, however, the power function normally remained far superior. These results confirm the hypothesis that both single-value and random-sampling approaches cause artifacts by increasing stochasticity in the data, which can lead to the selection of inappropriate models.