Interpretation Of Treatment Effects Research Articles

Modeling item-level heterogeneous treatment effects: A tutorial with the glmer function from the lme4 package in R.

Recent advancements in education scholarship have introduced Item Response Theory (IRT) models to address treatment heterogeneity at the assessment item level. These models for item-level heterogeneous treatment effects (IL-HTE) enable detailed analyses of treatments that may have varying impacts on individual items within an assessment. This article offers a comprehensive tutorial for applied researchers interested in implementing IL-HTE analysis in R, utilizing the lme4 package. Using empirical data from a second-grade reading comprehension assessment as a running example, this tutorial emphasizes model-building strategies, interpretation techniques, visualization methods, and extensions. By following this tutorial, researchers will gain practical insights into utilizing IL-HTE analysis for enhanced understanding and interpretation of treatment effects at the item level.

Preoperative conservative treatment is insufficiently described in clinical trials of lumbar fusion: a scoping review.

To identify how pre-surgical conservative care is characterized and reported in randomized controlled trials of adults undergoing elective lumbar fusion, including duration and type of treatment. The study design is a scoping review. Data sources include PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Ovid Medline, EMBASE, and Cochrane Central Register of Controlled Trials (CENTRAL). All randomized controlled trials published in English between January 1, 2005, and February 15, 2022, assessing lumbar fusion as the intervention were included in this review. Of 166 studies, 62.0% reported a failure in conservative care prior to lumbar fusion, but only 15.1% detailed the type of specific conservative carereceived. None of the trials provided sufficient details to understand the nature of the pre-surgical conservative treatment, such as frequency, recency/timing, or dosage of conservative interventions. Although roughly two-thirds of trials reported thatpatients failed conservative care prior to receiving a lumbar fusion, few studies named the conservative intervention provided and no studies provided any details regarding dosing or recency of care. This lack of information creates ambiguity in the surgical decision-making process, setting the assumption that all patients received adequate conservative care prior to surgery. Details about pre-surgical conservative care should be disclosed to allow for appropriate clinical application, decision-making, and interpretation of treatment effects.

Generating the Right Evidence at the Right Time: Principles of a New Class of Flexible Augmented Clinical Trial Designs.

To support informed decision making, clear descriptions of the beneficial and harmful effects of a treatment are needed by various stakeholders. The current paradigm is to generate evidence sequentially through different experiments. However, data generated later, perhaps through observational studies, can be difficult to compare with earlier randomized trial data, resulting in confusion in understanding and interpretation of treatment effects. Moreover, the scientific questions these later experiments can serve to answer often remain vague. We propose Flexible Augmented Clinical Trial for Improved eVidence gEneration (FACTIVE), a new class of study designs enabling flexible augmentation of confirmatory randomized controlled trials with concurrent and close-to-real-world elements. Our starting point is to use clearly defined objectives for evidence generation, which are formulated through early discussion with health technology assessment (HTA) bodies and are additional to regulatory requirements for authorization of a new treatment. These enabling designs facilitate estimation of certain well-defined treatment effects in the confirmatory part and other complementary treatment effects in a concurrent real-world part. Each stakeholder should use the evidence that is relevant within their own decision-making framework. High quality data are generated under one single protocol and the use of randomization ensures rigorous statistical inference and interpretation within and between the different parts of the experiment. Evidence for the decision making of HTA bodies could be available earlier than is currently the case.

Disease progression model using the integrated Alzheimer's Disease Rating Scale.

An Alzheimer's disease (AD) dementia disease progression model was developed based on the integrated Alzheimer's Disease Rating Scale (iADRS). Data from 3483 placebo participants in six AD trials were used to develop the disease progression model with NONMEM (version 7.4.2) and examined for mild cognitive impairment, and mild and moderate dementia due to AD. Baseline iADRS score was significantly influenced by AD symptomatic medication use, EXPEDITION2 enrollment (included moderate AD participants), age, and baseline Mini-Mental State Examination (MMSE) score. Rate of disease progression increased across disease stage and was significantly influenced by AD medication use, age, and baseline MMSE score. Apolipoprotein E ε4 carrier status did not influence baseline iADRS score or disease progression. These results demonstrate a disease progression model describing the time course of the iADRS across the AD severity spectrum. This model can assist future clinical trials in study design optimization and treatment effect interpretation. A disease progression model described the integrated Alzheimer's Disease Rating Scale (iADRS) time course in mild cognitive impairment to moderate Alzheimer's disease. Using the linear regression model, iADRS scores can be calculated for Mini-Mental State Examination scores. Results can help optimize future clinical trial design and aid in understanding treatment effects.

Combined Oxytocin and Cognitive Behavioral Social Skills Training for Social Function in People With Schizophrenia

A significant proportion of people with schizophrenia are characterized by impaired ability to socially engage with others. The development of effective interventions for social functioning remains a central therapeutic challenge. Cognitive-behavioral social skills training (CBSST) has been found to improve social functioning in schizophrenia, but with only medium effect sizes. Intranasal oxytocin also has prosocial effects, but also only with modest effect sizes. This study assessed whether the addition of intranasal oxytocin to CBSST can strengthen their impact on social function. Participants (N = 62) with schizophrenia or schizoaffective disorder entered a 24-week, double-blind, placebo-controlled, randomized clinical trial with a 3-month follow-up evaluation at 2 sites: Maryland and San Diego. Participants were randomized to either intranasal oxytocin 36 IU (3 sprays) twice a day (n = 31) or intranasal placebo-oxytocin (3 sprays) twice a day (n = 31). All participants received CBSST plus a social cognition skills training module (48 total sessions). There were no significant treatment group differences in social functioning, positive symptoms, negative symptoms, defeatist beliefs, or asocial beliefs. The interpretation of treatment effects was complicated by site effects, whereby participants in San Diego began the trial with greater severity of impairments and subsequently showed greater improvements compared with participants in Maryland. The results did not support the utility of add-on intranasal oxytocin to psychosocial rehabilitation interventions like CBSST for improvement in social function (ClinicalTrials.gov trial number: NCT01752712).

Measuring change in health-related quality of life: the impact of different analytical methods on the interpretation of treatment effects in glioma patients.

BackgroundDifferent analytical methods may lead to different conclusions about the impact of treatment on health-related quality of life (HRQoL). This study aimed to examine 3 different methods to evaluate change in HRQoL and to study whether these methods result in different conclusions.MethodsHRQoL data from 15 randomized clinical trials were combined (CODAGLIO project). Change in HRQoL scores, measured with the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 and BN20 questionnaires, was analyzed in 3 ways: (1) at the group level, comparing mean changes in scale/item scores between treatment arms, (2) at the patient level per scale/item, calculating the percentage of patients that deteriorated, improved, or remained stable per scale/item, and (3) at the individual patient level, combining all scales/items.ResultsBaseline and first follow-up HRQoL data were available for 3727 patients. At the group scale/item level, only the item “hair loss” showed a significant and clinically relevant change (ie, ≥10 points) over time, whereas change scores on the other scales/items were statistically significant only (all P < .001; range in change score, 0.1-6.2). Although a large proportion of patients had stable HRQoL over time (range, 27%-84%) on the patient level per scale/item, many patients deteriorated (range, 6%-43%) or improved (range, 8%-32%) on a specific scale/item. At the individual patient level, the majority of patients (86%) showed both deterioration and improvement, whereas only 1% remained stable on all scales.ConclusionsDifferent analytical methods of changes in HRQoL result in distinct conclusions of treatment effects, all of which may be relevant for informing clinical decision making.

Advanced multimodal imaging in differentiating glioma recurrence from post-radiotherapy changes.

Gliomas are the most common malignant primary brain tumor, and their prognosis is extremely poor. Radiotherapy is an important treatment for glioma patients, but the changes caused by radiotherapy have brought difficulties in clinical image evaluation because differentiating glioma recurrence from post-radiotherapy changes including pseudo-progression (PD) and radiation necrosis (RN) remains a challenge. Therefore, accurate and reliable imaging evaluation is very important for making clinical decisions. In recent years, advanced multimodal imaging techniques have been applied to achieve the goal of better differentiating glioma recurrence from post-radiotherapy changes for minimizing errors associated with interpretation of treatment effects. In this review, we discuss the recent applications of advanced multimodal imaging such as diffusion MRI sequences, amide proton transfer MRI sequences, perfusion MRI sequences, MR spectroscopy and multinuclides PET/CT in the evaluation of post-radiotherapy treatment response in glioma patients and highlight their potential role in differentiating post-radiotherapy changes from glioma recurrence.

Identifying inconsistency in network meta-analysis: Is the net heat plot a reliable method?

One of the biggest challenges for network meta‐analysis is inconsistency, which occurs when the direct and indirect evidence conflict. Inconsistency causes problems for the estimation and interpretation of treatment effects and treatment contrasts. Krahn and colleagues proposed the net heat approach as a graphical tool for identifying and locating inconsistency within a network of randomized controlled trials. For networks with a treatment loop, the net heat plot displays statistics calculated by temporarily removing each design one at a time, in turn, and assessing the contribution of each remaining design to the inconsistency. The net heat plot takes the form of a matrix which is displayed graphically with coloring indicating the degree of inconsistency in the network. Applied to a network of individual participant data assessing overall survival in 7531 patients with lung cancer, we were surprised to find no evidence of important inconsistency from the net heat approach; this contradicted other approaches for assessing inconsistency such as the Bucher approach, Cochran's Q statistic, node‐splitting, and the inconsistency parameter approach, which all suggested evidence of inconsistency within the network at the 5% level. Further theoretical work shows that the calculations underlying the net heat plot constitute an arbitrary weighting of the direct and indirect evidence which may be misleading. We illustrate this further using a simulation study and a network meta‐analysis of 10 treatments for diabetes. We conclude that the net heat plot does not reliably signal inconsistency or identify designs that cause inconsistency.

The minimal clinically important difference of the Richmond Agitation-Sedation Scale in patients with cancer with agitated delirium.

The Richmond Agitation-Sedation Scale (RASS) is commonly used to assess psychomotor activity; however, to the authors' knowledge, its minimal clinically important difference (MCID) has not been determined to date. The objective of the current study was to identify the MCID for RASS using 2 anchor-based approaches. The current study was a secondary analysis of a randomized controlled trial to compare the effect of lorazepam versus placebo as an adjuvant to haloperidol for persistent agitation in patients with delirium. The primary outcome was change in RASS (10-point numeric rating scale ranging from -5 [unarousable] to +4 [combative]) from baseline to 8 hours after treatment administration. The sensitivity-specificity and within-patient change methods were used to identify the MCID, with the anchor being patient comfort after the study intervention as perceived by caregivers and nurses. A total of 90 patients were randomized and 58 (64%) received the study medication for restlessness/agitation (mean baseline RASS, 1.6). A total of 23 caregivers (61%) and 23 nurses (55%) perceived that the patient was more comfortable after treatment. Using the sensitivity-specificity method, the optimal RASS reduction was ≥4 points according to both caregivers (sensitivity of 61% and specificity of 80%; area under the curve, 0.71) and nurses (sensitivity of 73% and specificity of 84%; area under the curve, 0.78). The RASS cutoff value based on the within-patient change method was similar (-4.2 for caregivers and -4.0 for nurses). For patients with persistent restlessness/agitation, a reduction of ≥4 points in RASS was considered to be the MCID for both nurses and caregivers. These preliminary findings may have implications for sample size calculation and the interpretation of treatment effect in future delirium trials. Cancer 2018;124:2246-52. © 2018 American Cancer Society.

Baseline EDSS proportions in MS clinical trials affect the overall outcome and power: A cautionary note

Background: In randomized clinical trials, when treatments do not work equally effectively across stratifications of participants, observed event rates may differ from those hypothesized leading to deviations in estimated power. Objectives: To investigate the effect of distributions of baseline Expanded Disability Status Scale (EDSS) proportions in relapsing-remitting multiple sclerosis (RRMS) on the trial outcome, confirmed disability progression rate (CDPR), and power. Methods: We reported CDPRs in the CombiRx trial by baseline EDSS and by groups (1st (0, 1), 2nd (1.5, 2), 3rd (2.5, 3), and 4th (⩾3.5)) and investigated the effect of different combinations of baseline EDSS proportions on the trial outcome and power. Results: There were 244 (25.4%) participants in the 1st group, 368 (38.4%) in the 2nd group, 223 (23.3%) in the 3rd group, and 124 (12.9%) in the 4th group with CDPRs of 40.1%, 13.9%, 11.2%, and 16.9%, respectively. Both CDPR and power increased when the proportion of the 1st group increased in hypothetical trials with equal sample sizes in each arm, and a 10% increase in the 1st group led to a 5% increase in power. Conclusion: Various baseline EDSS proportions yielded different CDPRs and power, suggesting caution in interpretation of treatment effects across trials that enrolled participants with different proportions of baseline EDSS.

Technical pre-analytical effects on the clinical biochemistry of Atlantic salmon (Salmo salar L.).

Clinical biochemistry has long been utilized in human and veterinary medicine as a vital diagnostic tool, but despite occasional studies showing its usefulness in monitoring health status in Atlantic salmon (Salmo salar L.), it has not yet been widely utilized within the aquaculture industry. This is due, in part, to a lack of an agreed protocol for collection and processing of blood prior to analysis. Moreover, while the analytical phase of clinical biochemistry is well controlled, there is a growing understanding that technical pre‐analytical variables can influence analyte concentrations or activities. In addition, post‐analytical interpretation of treatment effects is variable in the literature, thus making the true effect of sample treatment hard to evaluate. Therefore, a number of pre‐analytical treatments have been investigated to examine their effect on analyte concentrations and activities. In addition, reference ranges for salmon plasma biochemical analytes have been established to inform veterinary practitioners and the aquaculture industry of the importance of clinical biochemistry in health and disease monitoring. Furthermore, a standardized protocol for blood collection has been proposed.

Therapeutic adherence and competence scales for Developmentally Adapted Cognitive Processing Therapy for adolescents with PTSD

BackgroundThe assessment of therapeutic adherence and competence is often neglected in psychotherapy research, particularly in children and adolescents; however, both variables are crucial for the interpretation of treatment effects.ObjectiveOur aim was to develop, adapt, and pilot two scales to assess therapeutic adherence and competence in a recent innovative program, Developmentally Adapted Cognitive Processing Therapy (D-CPT), for adolescents suffering from posttraumatic stress disorder (PTSD) after childhood abuse.MethodTwo independent raters assessed 30 randomly selected sessions involving 12 D-CPT patients (age 13–20 years, M age=16.75, 91.67% female) treated by 11 therapists within the pilot phase of a multicenter study.ResultsThree experts confirmed the relevance and appropriateness of each item. All items and total scores for adherence (intraclass correlation coefficients [ICC]=0.76–1.00) and competence (ICC=0.78–0.98) yielded good to excellent inter-rater reliability. Cronbach's alpha was 0.59 for the adherence scale and 0.96 for the competence scale.ConclusionsThe scales reliably assess adherence and competence in D-CPT for adolescent PTSD patients. The ratings can be helpful in the interpretation of treatment effects, the assessment of mediator variables, and the identification and training of therapeutic skills that are central to achieving good treatment outcomes. Both adherence and competence will be assessed as possible predictor variables for treatment success in future D-CPT trials.

The analysis of incontinence episodes and other count data in patients with overactive bladder by Poisson and negative binomial regression.

Clinical studies in overactive bladder have traditionally used analysis of covariance or nonparametric methods to analyse the number of incontinence episodes and other count data. It is known that if the underlying distributional assumptions of a particular parametric method do not hold, an alternative parametric method may be more efficient than a nonparametric one, which makes no assumptions regarding the underlying distribution of the data. Therefore, there are advantages in using methods based on the Poisson distribution or extensions of that method, which incorporate specific features that provide a modelling framework for count data. One challenge with count data is overdispersion, but methods are available that can account for this through the introduction of random effect terms in the modelling, and it is this modelling framework that leads to the negative binomial distribution. These models can also provide clinicians with a clearer and more appropriate interpretation of treatment effects in terms of rate ratios. In this paper, the previously used parametric and non-parametric approaches are contrasted with those based on Poisson regression and various extensions in trials evaluating solifenacin and mirabegron in patients with overactive bladder. In these applications, negative binomial models are seen to fit the data well.

Using the probability-probability plot and index to augment interpretation of treatment effect for patient-reported outcome measures

The interpretation of treatment effect can pose challenges, especially for patient-reported outcomes. As subjective assessments, patient-reported outcomes frequently lack a historical record to support what their scores mean, making their interpretation of treatment differences challenging. We show how the probability-probability (p-p) plot a graph of the test-treatment distribution percentiles versus the control-treatment distribution percentiles, can complement and supplement interpretation of treatment effect. From this plot, we introduce the p-p index as a new measure of treatment effect, illustrating the method with two examples. The p-p index represents, across all percentiles, the average difference in percentile rank for any pair of subjects on two different treatments with the same outcome score. This measure, which complements other metrics of treatment effect, captures full information by integrating across all percentiles and thus accurately summarizes and augments the interpretation of treatment effect.

Competing mortality (CM) risk in patients with resected stage I and II non-small cell lung cancer (NSCLC): A Surveillance, Epidemiology, and End Results (SEER) analysis.

7563 Background: CM risk has been identified as a potential confounder in the interpretation of treatment effects in head and neck cancer (Rose et al. J Clin Oncol. 2011). Lung cancer patients (pts) are at considerable risk for CM due to their advanced age at diagnosis and smoking related chronic diseases. We plan to identify risk factors for CM in pts with early stage NSCLC and develop a statistical model to estimate the effect of CM on power calculation for lung cancer clinical trials. Methods: Using SEER registry we identified 32104 pts who had undergone surgical resection with or without radiation for stage I and II NSCLC between 1994 and 2006. The data set was split into two groups: training set (75%) and testing set (25%). Risk factors for lung cancer-specific mortality (LCSM) and CM were identified using training data by Gray’s sub-distribution regression of competing risk. Pts from the testing data were then stratified according to CM risk and the impact of this risk on power loss was evaluated. Results: The 5-year cumulative incidence of death from lung cancer, other causes and overall mortality was 32.7%, 14.2% and 46.9% respectively. Risk factors for CM were: age (hazard ratio [HR] 1.05), male gender (HR 1.43), divorced (HR 1.30), widowed (HR 1.23) or single (HR 1.29) marital status, squamous (HR 1.40) or not-otherwise-specified (HR 1.22) histology, stage I NSCLC (HR 1.27) and sublobar resection (HR 1.23). The 5-year cumulative incidence of CM in low, mid and high-risk tertiles was 7%, 14% and 21% respectively. Sample size calculations based on all-cause mortality (ACM) result in over-estimation of power as the risk for CM increases. In order to restore the underestimated power in LCSM, 19% and 35% more pts are required in the mid and high CM risk groups respectively (Table). Conclusions: Our findings indicate that conventional sample size calculation methods can result in significant loss of power and incorporating CM risk models in power estimation should be considered for clinical trials involving early stage NSCLC pts. [Table: see text]

Neuropsychiatric deep brain stimulation for translational neuroimaging

From a neuroimaging point of view, deep brain stimulation (DBS) in psychiatric disorders represents a unique source of information to probe results gained in functional, structural and molecular neuroimaging studies in vivo. However, the implementation has, up to now, been restricted by the heterogeneity of the data reported in DBS studies. The aim of the present study was therefore to provide a comprehensive and standardized database of currently used DBS targets in selected psychiatric disorders (obsessive-compulsive disorder (OCD), treatment-resistant depression (TRD), Gilles de la Tourette syndrome (GTS)) to enable topological comparisons between neuroimaging results and stimulation areas. A systematic literature research was performed and all peer-reviewed publications until the year 2012 were included. Literature research yielded a total of 84 peer-reviewed studies including about 296 psychiatric patients. The individual stimulation data of 37 of these studies meeting the inclusion criteria which included a total of 202 patients (63 OCD, 89 TRD, 50 GTS) was translated into MNI stereotactic space with respect to AC origin in order to identify key targets. The created database can be used to compare DBS target areas in MNI stereotactic coordinates with: 1) activation patterns in functional brain imaging (fMRI, phfMRI, PET, MET, EEG); 2) brain connectivity data (e.g., MR-based DTI/tractography, functional and effective connectivity); 3) quantitative molecular distribution data (e.g., neuroreceptor PET, post-mortem neuroreceptor mapping); 4) structural data (e.g., VBM for neuroplastic changes). Vice versa, the structural, functional and molecular data may provide a rationale to define new DBS targets and adjust/fine-tune currently used targets in DBS based on this overview in stereotactic coordinates. Furthermore, the availability of DBS data in stereotactic space may facilitate the investigation and interpretation of treatment effects and side effect of DBS by comparing these to neuroimaging results. The present study thus improves comparability between functional, structural and molecular data in standard stereotactic space gained in neuroimaging studies with surgical targets for DBS, which is among other possible implications of crucial importance for the definition of new targets for effective DBS.

Response shift in quality of life assessment in patients with chronic back pain and chronic ischaemic heart disease

Purpose: To examine the extent and type of influence of response shift (RS) (reconceptualization, reprioritization, recalibration) on the assessment of changes in health-related quality of life (HRQoL) after the inpatient rehabilitation of patients with chronic back pain and chronic ischaemic heart disease. Methods: RS was assessed using the then-test and structural equation modelling (SEM) approaches. HRQoL was recorded in a questionnaire study at the start and end of rehabilitation using disease-specific instruments. Global items were also developed to collect data on HRQoL at the start and end of rehabilitation, as well as for the retrospective evaluation of HRQoL at the beginning of rehabilitation via the then-test. Results: There are small recalibration effects in the then-test in both diseases in nearly every item which may underestimate the actual effects of change. Using the SEM approach, uniform and non-uniform recalibration effects appear in a few of the scales that cause true change scores to be under- and over-estimated. Conclusion: RS reflects a phenomenon that should be included when assessing HRQoL to allow a more valid interpretation of treatment effects. The results of SEM approach, however, suggest that RS does not lead to fundamentally different results in rehabilitation effects.Implications for RehabilitationThe predominant method for evaluating rehabilitation effects is to assess the patients’ subjectively perceived health status before and after treatment.RS characterizes changes in the respondent’s internal evaluation standards and therefore threatens the validity of change scores deriving from pre- test–post-test data.Small RS effects also occur in a rehabilitation setting of patients with chronic back pain and chronic ischaemic heart disease leading to an under- or overestimation of true treatment effects.RS should be included in the assessment to enable a more valid evaluation of rehabilitation effects.

Cause and Event: Supporting Causal Claims through Logistic Models

Efforts to identify and support credible causal claims have received intense interest in the research community, particularly over the past few decades. In this paper, we focus on the use of statistical procedures designed to support causal claims for a treatment or intervention when the response variable of interest is dichotomous. We identify seven key features of logistic regression studies that should play a critical role in estimating a causal effect and discuss their implications for causal inference. These include elaboration of research design, clarification of link function, model specification, challenges and limitations of sample size, interpretation of treatment effect through odds ratios, statistical tests and examination of model fit, and the potential for multilevel logistic models in pursuit of causal claims. Our recommendations are intended to guide researchers in the critical evaluation of logistic regression models for analyses culminating in causal claims and to promote stronger design and modeling strategies for reliable causal inference.

Clinical epidemiology and individualized medicine

Clinical epidemiology and individualized medicine

Comparative imaging between in vitro binding and in vivo PET

From a neuroimaging point of view, deep brain stimulation (DBS) in psychiatric disorders represents a unique source of information to probe results gained in functional, structural and molecular neuroimaging studies in vivo. However, the implementation has, up to now, been restricted by the heterogeneity of the data reported in DBS studies. The aim of the present study was therefore to provide a comprehensive and standardized database of currently used DBS targets in selected psychiatric disorders (obsessive–compulsive disorder (OCD), treatment-resistant depression (TRD), Gilles de la Tourette syndrome (GTS)) to enable topological comparisons between neuroimaging results and stimulation areas. A systematic literature research was performed and all peer-reviewed publications until the year 2012 were included. Literature research yielded a total of 84 peer-reviewed studies including about 296 psychiatric patients. The individual stimulation data of 37 of these studies meeting the inclusion criteria which included a total of 202 patients (63 OCD, 89 TRD, 50 GTS) was translated into MNI stereotactic space with respect to AC origin in order to identify key targets.The created database can be used to compare DBS target areas in MNI stereotactic coordinates with: 1) activation patterns in functional brain imaging (fMRI, phfMRI, PET, MET, EEG); 2) brain connectivity data (e.g., MR-based DTI/tractography, functional and effective connectivity); 3) quantitative molecular distribution data (e.g., neuroreceptor PET, post-mortem neuroreceptor mapping); 4) structural data (e.g., VBM for neuroplastic changes). Vice versa, the structural, functional and molecular data may provide a rationale to define new DBS targets and adjust/fine-tune currently used targets in DBS based on this overview in stereotactic coordinates. Furthermore, the availability of DBS data in stereotactic space may facilitate the investigation and interpretation of treatment effects and side effect of DBS by comparing these to neuroimaging results. The present study thus improves comparability between functional, structural and molecular data in standard stereotactic space gained in neuroimaging studies with surgical targets for DBS, which is among other possible implications of crucial importance for the definition of new targets for effective DBS.