An information-theoretic approach for the assessment of a continuous outcome as a surrogate for a binary true endpoint based on causal inference: Application to vaccine evaluation.

Within the causal association paradigm, a method is proposed to assess the validity of a continuous outcome as a surrogate for a binary true endpoint. The methodology is based on a previously introduced information-theoretic definition of surrogacy and has two main steps. In the first step, a new model is proposed to describe the joint distribution of the potential outcomes associated with the putative surrogate and the true endpoint of interest. The identifiability issues inherent to this type of models are handled via sensitivity analysis. In the second step, a metric of surrogacy new to this setting, the so-called individual causal association is presented. The methodology is studied in detail using theoretical considerations, some simulations, and data from a randomized clinical trial evaluating an inactivated quadrivalent influenza vaccine. A user-friendly R package Surrogate is provided to carry out the evaluation exercise.

Anti-tau intrabodies: From anti-tau immunoglobulins to the development of functional scFv intrabodies.

Over the last decade, there has been a growing interest in intrabodies and their therapeutic potential. Intrabodies are antibody fragments that are expressed inside a cell to target intracellular antigens. In the context of intracellular protein misfolding and aggregation, such as tau pathology in Alzheimer's disease, intrabodies have become an interesting approach as there is the possibility to target early stages of aggregation. As such, we engineered three anti-tau monoclonal antibodies into single-chain variable fragments for cytoplasmic expression and activity: PT51, PT77, and hTau21. Due to the reducing environment of the cytoplasm, single-chain variable fragment (scFv) aggregation is commonly observed. Therefore, we also performed complementarity-determining region (CDR) grafting into three different stable frameworks to rescue solubility and intracellular binding. All three scFvs retained binding to tau after cytoplasmic expression in HEK293 cells, in at least one of the frameworks. Subsequently, we show their capacity to interfere with either mouse or mutant human tau aggregation in two different primary mouse neuron models and organotypic hippocampal slice cultures. Collectively, our work extends the current knowledge on intracellular tau targeting with intrabodies, providing three scFv intrabodies that can be used as immunological tools to target tau inside cells.

Measuring respiratory syncytial virus infection severity in hospitalized children using the Pediatric Respiratory Syncytial Virus Electronic Severity and Outcome Rating System (PRESORS).

BACKGROUND: The Pediatric Respiratory Syncytial Virus Electronic Severity and Outcome Rating System (PRESORS) was developed to assess the severity of respiratory syncytial virus (RSV) infection in children. Because young children cannot report how they feel or function, ratings are based on observations by the child's caregiver (Observer-Reported Outcome questionnaire [ObsRO]) and clinician (Clinician-Reported Outcome questionnaire [ClinRO]). This prospective study aimed to evaluate the psychometric properties of the PRESORS. METHODS: The PRESORS version 6 ObsRO and ClinRO were evaluated in children with RSV infection requiring hospitalization in centers in the United States, Argentina, and Chile. Assessments were performed from days 1 to 7 by the child's caregiver and clinician. To assess inter-rater reliability, two clinicians independently performed the ClinRO near in time. RESULTS: A total of 124 children aged ≤36 months were enrolled (mean age, 8 months). Factor analysis demonstrated that RSV severity consists of two dimensions, respiratory signs and illness behavior, and that these dimensions were consistent over time. The inter-rater reliability for the ClinRO was 0.66 (95% confidence interval [CI], 0.55-0.75) but improved to 0.79 (95% CI, 0.71-0.86) after removing one outlying site, suggesting that quantifying RSV severity is not trivial, even using qualified raters, but that an adequate inter-rater reliability is achievable with the PRESORS through adequate training. ClinRO and ObsRO displayed acceptable internal consistency and acceptable convergent validity with the Respiratory Syncytial Virus Network Scale, global impression scores, and key hospital characteristics. CONCLUSIONS: The PRESORS is relevant and appropriate for assessing the severity of RSV infection in infants requiring hospitalization.

Validation of the monocyte activation test with three therapeutic monoclonal antibodies.

Pharmaceutical products intended for parenteral use must be free from pyrogenic (fever-inducing) contamination. Pyrogens comprise endotoxins from Gram-negative bacteria and non-endotoxin pyrogens from Gram-positive bacteria, viruses, and fungi. The longstanding compendial test for pyrogens is the rabbit pyrogen test, but in 2010 the monocyte acti-vation test (MAT) for pyrogenic and pro-inflammatory contaminants was introduced into the European Pharmacopoeia (Ph. Eur.) as a non-animal replacement for the rabbit pyrogen test. The present study describes the first product-specific Good Manufacturing Practice validation of Ph. Eur. MAT, Quantitative Test, Method A for the testing of three therapeutic monoclonal antibodies. The study used the MAT version with cryo-preserved peripheral blood mononuclear cells and interleukin-6 as the readout. Much of the data presented here for one of the antibodies was included in a successful product license application to the European Medicines Agency.

Identifying individual predictive factors for treatment efficacy.

Given the heterogeneous responses to therapy and the high cost of treatments, there is an increasing interest in identifying pretreatment predictors of therapeutic effect. Clearly, the success of such an endeavor will depend on the amount of information that the patient-specific variables convey about the individual causal treatment effect on the response of interest. In the present work, using causal inference and information theory, a strategy is proposed to evaluate individual predictive factors for cancer immunotherapy efficacy. In a first step, the methodology proposes a causal inference model to describe the joint distribution of the pretreatment predictors and the individual causal treatment effect. Further, in a second step, the so-called predictive causal information (PCI), a metric that quantifies the amount of information the pretreatment predictors convey on the individual causal treatment effects, is introduced and its properties are studied. The methodology is applied to identify predictors of therapeutic success for a therapeutic vaccine in advanced lung cancer. A user-friendly R library EffectTreat is provided to carry out the necessary calculations.

Implementing the meta-analytic approach for the evaluation of surrogate endpoints in SAS and R: a word of caution.

The meta-analytic approach has become the gold-standard methodology for the evaluation of surrogate endpoints and several implementations are currently available in SAS and R. The methodology is based on hierarchical models that are numerically demanding and, when the amount of data is limited, maximum likelihood algorithms may not converge or may converge to an ill-conditioned maximum such as a boundary solution. This may produce misleading conclusions and have negative implications for the evaluation of new drugs. In the present work, we explore the use of two distinct functions in R (lme and lmer) and the MIXED procedure in SAS to assess the validity of putative surrogate endpoints in the meta-analytic framework, via simulations and the analysis of a real case study. We describe some problems found with the lmer function in R that led to a poorer performance as compared with the lme function and MIXED procedure.

The individual-level surrogate threshold effect in a causal-inference setting with normally distributed endpoints.

In the meta-analytic surrogate evaluation framework, the trial-level coefficient of determination Rtrial2 quantifies the strength of the association between the expected causal treatment effects on the surrogate (S) and the true (T) endpoints. Burzykowski and Buyse supplemented this metric of surrogacy with the surrogate threshold effect (STE), which is defined as the minimum value of the causal treatment effect on S for which the predicted causal treatment effect on T exceeds zero. The STE supplements Rtrial2 with a more direct clinically interpretable metric of surrogacy. Alonso et al. proposed to evaluate surrogacy based on the strength of the association between the individual (rather than expected) causal treatment effects on S and T. In the current paper, the individual-level surrogate threshold effect (ISTE) is introduced in the setting where S and T are normally distributed variables. ISTE is defined as the minimum value of the individual causal treatment effect on S for which the lower limit of the prediction interval around the individual causal treatment effect on T exceeds zero. The newly proposed methodology is applied in a case study, and it is illustrated that ISTE has an appealing clinical interpretation. The R package surrogate implements the methodology and a web appendix (supporting information) that details how the analyses can be conducted in practice is provided.

Regression-Based Normative Data for Children From Latin America: Phonological Verbal Fluency Letters M, R, and P.

This study is part of a larger project to generate norms for letter verbal fluency test (VFT) in 3,284 children from nine Latin American countries. The letter VFT (letters M, R, and P) was administered and multiple linear regressions, including age, age2, MPE (mean parental education), MPE2, sex, and interactions were used as predictors. Results showed significant differences across countries for all scores. Age affected scores linearly except for Ecuador (P-letter), in which a quadratic effect was found. Scores increased linearly as a function of MPE, with the exception of Mexico (R-letter), in which a quadratic effect was found. Age by MPE (M- and P-letters), and age by MPE2 (R-letter) interactions were found in Mexico. Sex had an impact on letter R in Cuba, and letter P in Ecuador and Paraguay. Age2 by sex interaction was found in Ecuador (P-letter). These norms will be useful for clinical neuropsychologists in these countries to evaluate their patients' verbal fluency.

On the relationship between association and surrogacy when both the surrogate and true endpoint are binary outcomes.

The relationship between association and surrogacy has been the focus of much debate in the surrogate marker literature. Recently, the individual causal association (ICA) has been introduced as a metric of surrogacy in the causal inference framework, when both the surrogate and the true endpoint are normally distributed and when both are binary. Earlier work on the normal case has demonstrated that, although the ICA and the adjusted association are related metrics, their relationship strongly depends on unidentifiable parameters and, consequently, the association between both endpoints conveys little information on the validity of the surrogate. In addition, in the normal setting, the magnitude of the ICA does not depend on the mean of the outcomes. The latter implies that identifiable parameters such as mean responses and treatment effects provide no information on the validity of the surrogate. In the present work it is shown that this is fundamentally different in the binary case. We demonstrate that the observed association between the outcomes as well as the success rates in both treatment groups are quite predictive for the ICA. It is shown that finding a good surrogate will be more likely when the association between the endpoints is large, there are sizeable treatment effects and the success rates for both endpoints are similar in both treatment groups. These results are demonstrated using extensive simulations and illustrated on a case study in multi-drug resistant tuberculosis.

Identifying predictive biomarkers of CIMAvaxEGF success in non-small cell lung cancer patients.

BACKGROUND: Immunosenescence biomarkers and peripheral blood parameters are evaluated separately as possible predictive markers of immunotherapy. Here, we illustrate the use of a causal inference model to identify predictive biomarkers of CIMAvaxEGF success in the treatment of Non-Small Cell Lung Cancer Patients. METHODS: Data from a controlled clinical trial evaluating the effect of CIMAvax-EGF were analyzed retrospectively, following a causal inference approach. Pre-treatment potential predictive biomarkers included basal serum EGF concentration, peripheral blood parameters and immunosenescence biomarkers. The proportion of CD8 + CD28- T cells, CD4+ and CD8+ T cells, CD4/CD8 ratio and CD19+ B cells. The 33 patients with complete information were included. The predictive causal information (PCI) was calculated for all possible models. The model with a minimum number of predictors, but with high prediction accuracy (PCI > 0.7) was selected. Good, rare and poor responder patients were identified using the predictive probability of treatment success. RESULTS: The mean of PCI increased from 0.486, when only one predictor is considered, to 0.98 using the multivariate approach with all predictors. The model considering the proportion of CD4+ T cell, basal Epidermal Growth Factor (EGF) concentration, neutrophil to lymphocyte ratio, Monocytes, and Neutrophils as predictors were selected (PCI > 0.74). Patients predicted as good responders according to the pre-treatment biomarkers values treated with CIMAvax-EGF had a significant higher observed survival compared with the control group (p = 0.03). No difference was observed for bad responders. CONCLUSIONS: Peripheral blood parameters and immunosenescence biomarkers together with basal EGF concentration in serum resulted in good predictors of the CIMAvax-EGF success in advanced NSCLC. Future research should explore molecular and genetic profile as biomarkers for CIMAvax-EGF and it combination with immune-checkpoint inhibitors. The study illustrates the application of a new methodology, based on causal inference, to evaluate multivariate pre-treatment predictors. The multivariate approach allows realistic predictions of the clinical benefit of patients and should be introduced in daily clinical practice.

[Formula: see text] Measuring visual matching and short-term recognition memory with the CANTAB® Delayed Matching to Sample task in schoolchildren: Effects of demographic influences, multiple outcome measures and regression-based normative data.

The study aims to establish demographically corrected, pediatric norms for the computerized Delayed Matching to Sample (DMS) test, a measure of "visual matching ability and short-term visual recognition memory, for non-verbalisable problems". The DMS was administered to n = 184 children aged 5.10 to 14.5 years old. The DMS is a 4-choice recognition task of non-verbal, abstract patterns. The child has "to select, among four different choice patterns, the one that matches a complex visual pattern presented," i.e., (the target stimulus). The DMS consists of two conditions: a) the overt condition in which the target stimulus and four choice patterns are shown simultaneously and b) the covert condition, in which the choice patterns are shown after the target pattern is covered. The DMS test provides three outcome measures: the accuracy score (i.e., the number of correct patterns selected), latency (i.e., the response speed) and the probability of making an error after an incorrect response. These outcome measures were calculated for both conditions and for both conditions combined. Results showed that demographic variables, such as age, sex, and/or level of parental education (LPE) affected scores on these outcome measures. Based on these data, demographically corrected norms were established for all outcome measures, per condition and for both conditions combined.

A reflection on the causal interpretation of individual-level surrogacy.

At the beginning of the 21st century, a new paradigm was introduced for the evaluation of surrogate endpoints based on meta-analysis. In this paradigm, the putative surrogate is assessed at two different levels, the so-called, trial and individual level. Trial level surrogacy is defined as the association between the expected causal treatment effects across different trials populations, whereas the individual level is defined as the association between the surrogate and true endpoints, after adjusting by trial and treatment. It has been argued that the individual level surrogacy does not have a causal interpretation and, consequently, it is a poor metric of surrogacy. In the present work, an alternative definition of individual level surrogacy is introduced based on individual causal treatment effects. In addition, using the maximum entropy principle, a direct link between the individual level surrogacy, as defined in the meta-analytic approach, and the newly proposed definition is established. This new perspective sets the individual level surrogacy in a more coherent framework with respect to the trial level and bridges the two main schools of thought in this domain, namely, the causal inference and meta-analytic schools.

Normative data for verbal fluency in healthy Latin American adults: Letter M, and fruits and occupations categories.

OBJECTIVE: To generate normative data for the verbal fluency tests (VFT-letter M, fruits, and occupations categories) in Spanish-speaking adult populations, with country-specific adjustments for age, education, and sex when appropriate. METHOD: The sample consisted of 3,977 healthy adults from 11 countries in Latin America (Argentina, Bolivia, Chile, Cuba, El Salvador, Guatemala, Honduras, Mexico, Paraguay, Peru, and Puerto Rico; sample size per country ranged between n = 184 and n = 1,300). Each participant was administered the VFT as part of a larger neuropsychological battery. Scores for letter M, fruits, and occupations categories were normed using multiple linear regressions. The country-specific regression models included age, age2, education, education2, and sex as predictors. RESULTS: The final multiple linear regression models showed that age affected the performance on these tests but not uniformly. For example, M letter scores decrease linearly with age except for Argentina, Guatemala, and Mexico, in which quadratic age effect was found. Scores also increase linearly as a function of education but not in all countries. For example, a quadratic education effect was found for the fruits category in Bolivia, Honduras, and Paraguay. Sex had a significant impact on the M letter category fluency in Guatemala, fruits category in Guatemala and Peru, and occupations' category in Mexico. CONCLUSIONS: This study presents verbal fluency test normative data across 11 countries in Latin America. These norms are expected to be useful for neuropsychologists of these countries. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

A reflection on the possibility of finding a good surrogate.

Surrogate endpoints need to be statistically evaluated before they can be used as substitutes of true endpoints in clinical studies. However, even though several evaluation methods have been introduced over the last decades, the identification of good surrogate endpoints remains practically and conceptually challenging. In the present work, the question regarding the existence of a good surrogate is addressed using information-theoretic concepts, within a causal-inference framework. The methodology can help practitioners to assess, given a clinically relevant true endpoint and a treatment of interest, the chances of finding a good surrogate endpoint in the first place. The methodology focuses on binary outcomes and is illustrated using data from the Initial Glaucoma Treatment Study. Furthermore, a newly developed and user friendly R package Surrogate is provided to carry out the necessary calculations.

Assessing the predictive value of a binary surrogate for a binary true endpoint based on the minimum probability of a prediction error.

The individual causal association (ICA) has recently been introduced as a metric of surrogacy in a causal-inference framework. The ICA is defined on the unit interval and quantifies the association between the individual causal effect on the surrogate (ΔS) and true (ΔT) endpoint. In addition, the ICA offers a general assessment of the surrogate predictive value, taking value 1 when there is a deterministic relationship between ΔT and ΔS, and value 0 when both causal effects are independent. However, when one moves away from the previous two extreme scenarios, the interpretation of the ICA becomes challenging. In the present work, a new metric of surrogacy, the minimum probability of a prediction error (PPE), is introduced when both endpoints are binary, ie, the probability of erroneously predicting the value of ΔT using ΔS. Although the PPE has a more straightforward interpretation than the ICA, its magnitude is bounded above by a quantity that depends on the true endpoint. For this reason, the reduction in prediction error (RPE) attributed to the surrogate is defined. The RPE always lies in the unit interval, taking value 1 if prediction is perfect and 0 if ΔS conveys no information on ΔT. The methodology is illustrated using data from two clinical trials and a user-friendly R package Surrogate is provided to carry out the validation exercise.

A maximum entropy approach for the evaluation of surrogate endpoints based on causal inference.

The maximum entropy principle offers a constructive criterion for setting up probability distributions on the basis of partial knowledge. In the present work, the principle is applied to tackle an important problem in the surrogate marker field, namely, the evaluation of a binary outcome as a putative surrogate for a binary true endpoint within a causal inference framework. In the first step, the maximum entropy principle is used to determine the relative frequencies associated with the values of the vector of potential outcomes. Subsequently, in the second step, these relative frequencies are used in combination with two newly proposed metrics of surrogacy, the so-called individual causal association and the surrogate predictive function, to assess the validity of the surrogate. The procedure is conceptually similar to the use of noninformative or reference priors in Bayesian statistics. Additionally, approximate, identifiable bounds are proposed for the estimands of interest, and their performance is studied via simulations. The methods are illustrated using data from a clinical trial involving schizophrenic patients, and a newly developed and user-friendly R package Surrogate is provided to carry out the validation exercise.

Evaluation of six months sputum culture conversion as a surrogate endpoint in a multidrug resistant-tuberculosis trial.

The emergence of multidrug resistant-tuberculosis (MDR-TB), defined as Mycobacterium tuberculosis strains with in vitro resistance to at least isoniazid and rifampicin, has necessitated evaluation and validation of appropriate surrogate endpoints for treatment response in drug trials for MDR-TB. The trial that has demonstrated efficacy of bedaquiline, a diarylquinoline that inhibits mycobacterial ATP synthase, possesses the requisite features to conduct this evaluation. Approval of bedaquiline for use in MDR-TB was based primarily on the results of the controlled C208 Stage II study (ClinicalTrials.gov number, NCT00449644) including 160 patients randomized 1:1 to receive bedaquiline or placebo for 24 weeks when added to an 18-24-month preferred five-drug background regimen. Since randomization in C208 Stage II was preserved until study end, the trial results allow for the investigation of the complex relationship between sustained durable outcome with either Week 8 or Week 24 culture conversion as putative surrogate endpoints. The relationship between Week 120 outcome with Week 8 or Week 24 culture conversion was investigated using a descriptive analysis and with a recently developed statistical methodology for surrogate endpoint evaluation using methods of causal inference. The results demonstrate that sputum culture conversion at 24 weeks is more reliable than sputum culture conversion at 8 weeks when assessing the outcome of adding one new drug to a MDR-TB regimen.

Cognitive functioning in the general population: Factor structure and association with mental disorders-The neuropsychological test battery of the mental health module of the German Health Interview and Examination Survey for Adults (DEGS1-MH).

The objective of this study is to obtain population level data about cognitive functions and their association with mental disorders. We here report factor analytic and psychometric findings of a neuropsychological test battery and examine the association of current and past mental disorders with cognitive function in a large nationwide population-based sample of 18- to 79-year-old adults in Germany (n = 3,667) participating in the mental health module of the German Health Interview and Examination Survey for Adults 2008-2011. Confirmatory factor analysis confirmed verbal memory and executive function factors. Older age was strongly associated with lower verbal memory and executive function and with higher vocabulary scores. After adjustment for age, sex, and education, rather modest decrements were found for verbal memory (ß = -.118, p = .002) and executive functions (ß = -.191, p < .001) in participants with any current mental disorder (n = 442) compared to those without (n = 3,201). Small decrements in memory (ß = -.064, p = .031) and executive function (ß = -.111, p < .001) were found in participants with any mental disorder in the last 12 months but not in those with past (fully or partially remitted) mental disorders, compared to participants without a history of mental disorder. More fine-grained analyses of these data will investigate the complex interplay between cognition, health behaviors, and specific mental and somatic diseases.

Predictive factors influencing pregnancy rates after intrauterine insemination with frozen donor semen: a prospective cohort study.

The extent to which certain parameters can influence pregnancy rates after intrauterine insemination with frozen donor semen was examined prospectively. Between July 2011 and September 2015, 402 women received 1264 IUI cycles with frozen donor semen in a tertiary referral infertility centre. A case report form was used to collect data prospectively. The primary outcome measure was clinical pregnancy rate (CPR), confirmed by detection of a gestational sac and fetal heartbeat using ultrasonography at 7-8 weeks of gestation. Statistical analysis was carried out using generalized estimating equations (GEE) to account for the correlation between observations from the same patient. Overall, CPR per cycle was 17.2%. Multivariate GEE analysis revealed the following parameters as predictive for a successful pregnancy outcome: female age (P = 0.0003), non-smoking or smoking fewer than 15 cigarettes a day (P = 0.0470 and P = 0.0235, respectively), secondary infertility (P = 0.0062), low progesterone levels at day zero of the cycle (P = 0.0164) and use of ovarian stimulation with HMG and recombinant FSH compared with clomiphene citrate and natural cycle (P = 0.0006 and P = 0.0004, respectively). These parameters were the most important factors influencing the success rate in a sperm donation programme.

Predictive value of different covariates influencing pregnancy rate following intrauterine insemination with homologous semen: a prospective cohort study.

The aim was to examine the value of different covariates in the prediction of intrauterine insemination (IUI) success. Between July 2011 and September 2015, data from 1401 IUI cycles with homologous semen in 556 couples were collected prospectively, by questionnaire, in a tertiary referral infertility centre. Statistical analysis was performed using generalized estimating equations (GEEs). GEEs were used instead of an ordinary logistic regression model to take into account the correlation between observations from the same person. The primary outcome parameter was clinical pregnancy rate (CPR), confirmed with a gestational sac and fetal heartbeat on ultrasonography at 7-8 weeks. An overall CPR of 9.5% per cycle was observed. Univariate statistical analysis revealed female and male age, male smoking, female body mass index, ovarian stimulation and inseminating motile count (IMC) as covariates significantly influencing CPR per cycle. Multivariate GEE analysis revealed that the only valuable prognostic covariates included female age, male smoking and infertility status (i.e. primary/secondary infertility). IMC showed a significant curvilinear relationship, with first an increase and then a decrease in pregnancy rate.