Target parameters and bias in non-causal change-score analyses with measurement errors.

In studies where the outcome is a change-score, it is often debated whether or not the analysis should adjust for the baseline score. When the aim is to make causal inference, it has been argued that the two analyses (adjusted vs. unadjusted) target different causal parameters, which may both be relevant. However, these arguments are not applicable when the aim is to make predictions rather than to estimate causal effects. When the scores are measured with error, there have been attempts to quantify the bias resulting from adjustment for the (mis-)measured baseline score or lack thereof. However, these bias results have been derived under an unrealistically simple model, and assuming that the target parameter is the unadjusted (for the true baseline score) association, thus dismissing the adjusted association as a possibly relevant target parameter. In this paper we address these limitations. We argue that, even if the aim is to make predictions, there are two possibly relevant target parameters; one adjusted for the baseline score and one unadjusted. We consider both the simple case when there are no measurement errors, and the more complex case when the scores are measured with error. For the latter case, we consider a more realistic model than previous authors. Under this model we derive analytic expressions for the biases that arise when adjusting or not adjusting for the (mis-)measured baseline score, with respect to the two possible target parameters. Finally, we use these expressions to discuss when adjustment is warranted in change-score analyses.

Causal inference in survival analysis under deterministic missingness of confounders in register data.

Long-term register data offer unique opportunities to explore causal effects of treatments on time-to-event outcomes, in well-characterized populations with minimum loss of follow-up. However, the structure of the data may pose methodological challenges. Motivated by the Swedish Renal Registry and estimation of survival differences for renal replacement therapies, we focus on the particular case when an important confounder is not recorded in the early period of the register, so that the entry date to the register deterministically predicts confounder missingness. In addition, an evolving composition of the treatment arms populations, and suspected improved survival outcomes in later periods lead to informative administrative censoring, unless the entry date is appropriately accounted for. We investigate different consequences of these issues on causal effect estimation following multiple imputation of the missing covariate data. We analyse the performance of different combinations of imputation models and estimation methods for the population average survival. We further evaluate the sensitivity of our results to the nature of censoring and misspecification of fitted models. We find that an imputation model including the cumulative baseline hazard, event indicator, covariates and interactions between the cumulative baseline hazard and covariates, followed by regression standardization, leads to the best estimation results overall, in simulations. Standardization has two advantages over inverse probability of treatment weighting here: it can directly account for the informative censoring by including the entry date as a covariate in the outcome model, and allows for straightforward variance computation using readily available software.

Adjustment for Disease Severity in the Test-Negative Study Design.

The test-negative study design is often used to estimate vaccine effectiveness in influenza studies, but it has also been proposed in the context of other infectious diseases, such as cholera, dengue, or Ebola. It was introduced as a variation of the case-control design, in an attempt to reduce confounding bias due to health-care-seeking behavior, and has quickly gained popularity because of its logistic advantages. However, examination of the directed acyclic graphs that describe the test-negative design reveals that without strong assumptions, the estimated odds ratio derived under this sampling mechanism is not collapsible over the selection variable, such that the results obtained for the sampled individuals cannot be generalized to the whole population. In this paper, we show that adjustment for severity of disease can reduce this bias and, under certain assumptions, makes it possible to unbiasedly estimate a causal odds ratio. We support our findings with extensive simulations and discuss them in the context of recently published cholera test-negative studies of the effectiveness of cholera vaccines.

Cancer Risk Stratification of Anal Intraepithelial Neoplasia in Human Immunodeficiency Virus-Positive Men by Validated Methylation Markers Associated With Progression to Cancer.

BACKGROUND: High-grade anal intraepithelial neoplasia (HGAIN; AIN2-3) is highly prevalent in HIV+ men, but only a minority of these lesions progress towards cancer. Currently, cancer progression risk cannot be established; therefore, no consensus exists on whether HGAIN should be treated. This study aimed to validate previously identified host cell DNA methylation markers for detection and cancer risk stratification of HGAIN. METHODS: A large independent cross-sectional series of 345 anal cancer, AIN3, AIN2, AIN1, and normal control biopsies of HIV+ men was tested for DNA methylation of 6 genes using quantitative methylation-specific PCR. We determined accuracy for detection of AIN3 and cancer (AIN3+) by univariable and multivariable logistic regression analysis, followed by leave-one-out cross-validation. Methylation levels were assessed in a series of 10 anal cancer cases with preceding HGAIN at similar anatomic locations, and compared with the cross-sectional series. RESULTS: Methylation levels of all genes increased with increasing severity of disease (P < .05). HGAIN revealed a heterogeneous methylation pattern, with a subset resembling cancer. ZNF582 showed highest accuracy (AUC = 0.88) for AIN3+ detection, slightly improved by addition of ASCL1 and SST (AUC = 0.89), forming a marker panel. In the longitudinal series, HGAIN preceding cancer displayed high methylation levels similar to cancers. CONCLUSIONS: We validated the accuracy of 5 methylation markers for the detection of anal (pre-) cancer. High methylation levels in HGAIN were associated with progression to cancer. These markers provide a promising tool to identify HGAIN in need of treatment, preventing overtreatment of HGAIN with a low cancer progression risk.

Evaluation of six methylation markers derived from genome-wide screens for detection of cervical precancer and cancer.

Aim: To evaluate the triage performance of six host-cell DNA methylation markers derived from two genome-wide discovery screens for detection of cervical precancer (cervical intraepithelial neoplasia 3 [CIN]) and cancer. Materials & methods: Human papillomavirus-positive cervical scrapes of controls (≤CIN1; n = 352) and women diagnosed with CIN3 (n = 175) or cervical cancer (n = 50) were analyzed for methylation of ASCL1, LHX8, ST6GALNAC5, GHSR, SST and ZIC1. Results: Methylation levels increased significantly with disease severity (all markers p < 0.001). Three markers (ASCL1, LHX8, ZIC1) showed receiver operating characteristic curves with area under the curve >0.800 after leave-one-out cross-validation. Bi-marker panel ASCL1/LHX8 had highest area under the curve (0.882), and detected 83.4% of CIN3 and all cervical cancers at specificity of 82.4%. Conclusion: All six methylation markers showed an equivalent, high performance for the triage of human papillomavirus-positive women using cervical scrapes with complementarity between markers.

Host Cell Deoxyribonucleic Acid Methylation Markers for the Detection of High-grade Anal Intraepithelial Neoplasia and Anal Cancer.

BACKGROUND: High-grade anal intraepithelial neoplasia (AIN2/3; HGAIN) is highly prevalent in human immunodeficiency virus positive (HIV+) men who have sex with men (MSM), but only a minority will eventually progress to cancer. Currently, the cancer risk cannot be established, and therefore all HGAIN is treated, resulting in overtreatment. We assessed host cell deoxyribonucleic acid (DNA) methylation markers for detecting HGAIN and anal cancer. METHODS: Tissue samples of HIV+ men with anal cancer (n = 26), AIN3 (n = 24), AIN2 (n = 42), AIN1 (n = 22) and HIV+ male controls (n = 34) were analyzed for methylation of 9 genes using quantitative methylation-specific polymerase chain reaction. Univariable and least absolute shrinkage and selection operator logistic regression, followed by leave-one-out cross-validation, were used to determine the performance for AIN3 and cancer detection. RESULTS: Methylation of all genes increased significantly with increasing severity of disease (P < 2 × 10-6). HGAIN samples revealed heterogeneous methylation patterns, with a subset resembling cancer. Four genes (ASCL1, SST, ZIC1,ZNF582) showed remarkable performance for AIN3 and anal cancer detection (area under the curve [AUC] > 0.85). ZNF582 (AUC = 0.89), detected all cancers and 54% of AIN3 at 93% specificity. Slightly better performance (AUC = 0.90) was obtained using a 5-marker panel. CONCLUSIONS: DNA methylation is associated with anal carcinogenesis. A marker panel that includes ZNF582 identifies anal cancer and HGAIN with a cancer-like methylation pattern, warrantingvalidation studies to verify its potential for screening and management of HIV+ MSM at risk for anal cancer.

Balancing reward and work: anticipatory brain activation in NAcc and VTA predict effort differentially.

Complex decision-making involves anticipation of future rewards to bias effort for obtaining it. Using fMRI, we investigated 50 participants employing an instrumental-motivation task that cued reinforcement levels before the onset of the motor-response phase. We extracted timecourses from regions of interest (ROI) in the mesocorticolimbic system and used a three-level hierarchical model to separate anticipatory brain responses predicting value and subsequent effort on a trial-by-trial basis. Whereas all ROIs scaled positively with value, higher effort was predicted by higher anticipatory activation in nucleus accumbens (NAcc) but lower activation in ventral tegmental area/substantia nigra (VTA/SN). Moreover, anticipatory activation in the dorsal striatum predicted average effort whereas higher activation in the amygdala predicted above-average effort. Thus, anticipatory activation entails the appetitive drive towards reinforcement that requires effort in order to be obtained. Our results support the role of NAcc as the main hub supported by the salience network operating on a trial-by-trial basis, while the dorsal striatum incorporates habitual responding.