Are there interindividual differences in the reactive hypoglycaemia response to breakfast? A replicate crossover trial.

BACKGROUND: Following consumption of a meal, circulating glucose concentrations can rise and then fall briefly below the basal/fasting concentrations. This phenomenon is known as reactive hypoglycaemia but to date no researcher has explored potential inter-individual differences in response to meal consumption. OBJECTIVE: We conducted a secondary analysis of existing data to examine inter-individual variability of reactive hypoglycaemia in response to breakfast consumption. METHODS: Using a replicate crossover design, 12 healthy, physically active men (age: 18-30 y, body mass index: 22.1 to 28.0 kg⋅m- 2) completed two identical control (continued overnight fasting) and two breakfast (444 kcal; 60% carbohydrate, 17% protein, 23% fat) conditions in randomised sequences. Blood glucose and lactate concentrations, serum insulin and non-esterified fatty acid concentrations, whole-body energy expenditure, carbohydrate and fat oxidation rates, and appetite ratings were determined before and 2 h after the interventions. Inter-individual differences were explored using Pearson's product-moment correlations between the first and second replicates of the fasting-adjusted breakfast response. Within-participant covariate-adjusted linear mixed models and a random-effects meta-analytical approach were used to quantify participant-by-condition interactions. RESULTS: Breakfast consumption lowered 2-h blood glucose by 0.44 mmol/L (95%CI: 0.76 to 0.12 mmol/L) and serum NEFA concentrations, whilst increasing blood lactate and serum insulin concentrations (all p < 0.01). Large, positive correlations were observed between the first and second replicates of the fasting-adjusted insulin, lactate, hunger, and satisfaction responses to breakfast consumption (all r > 0.5, 90%CI ranged from 0.03 to 0.91). The participant-by-condition interaction response variability (SD) for serum insulin concentration was 11 pmol/L (95%CI: 5 to 16 pmol/L), which was consistent with the τ-statistic from the random-effects meta-analysis (11.7 pmol/L, 95%CI 7.0 to 22.2 pmol/L) whereas effects were unclear for other outcome variables (e.g., τ-statistic value for glucose: 0 mmol/L, 95%CI 0.0 to 0.5 mmol/L). CONCLUSIONS: Despite observing reactive hypoglycaemia at the group level, we were unable to detect any meaningful inter-individual variability of the reactive hypoglycaemia response to breakfast. There was, however, evidence that 2-h insulin responses to breakfast display meaningful inter-individual variability, which may be explained by relative carbohydrate dose ingested and variation in insulin sensitivity of participants.

Assessing the Heterogeneity of Response of [68Ga] Ga-PSMA-11 PET/CT Lesions in Patients With Biochemical Recurrence of Prostate Cancer.

INTRODUCTION: Treatment of men with metastatic prostate cancer can be difficult due to the heterogeneity of response of lesions. [68Ga]Ga-PSMA-11 (PSMA) PET/CT assists with monitoring and directing clinical intervention; however, the impact of response heterogeneity has yet to be related to outcome measures. The aim of this study was to assess the impact of quantitative imaging information on the value of PSMA PET/CT to assess patient outcomes in response evaluation. PATIENTS AND METHODS: Baseline and follow-up (6 months) PSMA PET/CT of 162 men with oligometastatic PC treated with standard clinical care were acquired between 2015 and 2016 for analysis. An augmentative software medical device was used to track lesions between scans and quantify lesion change to categorize them as either new, increasing, stable, decreasing, or disappeared. Quantitative imaging features describing the size, intensity, extent, change, and heterogeneity of change (based on percent change in SUVtotal) among lesions were extracted and evaluated for association with overall survival (OS) using Cox regression models. Model performance was evaluated using the c-index. RESULTS: Forty-one (25%) of subjects demonstrated heterogeneous response at follow-up, defined as having at least 1 new or increasing lesion and at least 1 decreasing or disappeared lesion. Subjects with heterogeneous response demonstrated significantly shorter OS than subjects without (median OS = 76.6 months vs. median OS not reached, P < .05, c-index = 0.61). In univariate analyses, SUVtotal at follow-up was most strongly associated with OS (HR = 1.29 [1.19, 1.40], P < .001, c-index = 0.73). Multivariable models applied using heterogeneity of change features demonstrated higher performance (c-index = 0.79) than models without (c-index = 0.71-0.76, P < .05). CONCLUSION: Augmentative software tools enhance the evaluation change on serial PSMA PET scans and can facilitate lesional evaluation between timepoints. This study demonstrates that a heterogeneous response at a lesional level may impact adversely on patient outcomes and supports further investigation to evaluate the role of imaging to guide individualized patient management to improve clinical outcomes.

Time perspective profile and self-reported health on the EQ-5D.

OBJECTIVES: Time perspective (TP) is a psychological construct that is associated with several health-related behaviours, including healthy eating, smoking and adherence to medications. In this study, we aimed to examine the associations of TP profile with self-reported health on the EQ-5D-5L and to detect which domains display response heterogeneity (cut-point shift) for TP. METHODS: We conducted a secondary analysis of EQ-5D-5L data from a representative general population sample in Hungary (n = 996). The 17-item Zimbardo Time Perspective Inventory was used to measure individuals' TP on five subscales: past-negative, past-positive, present-fatalist, present-hedonist and future. The associations between TP subscales and EQ-5D-5L domain scores, EQ VAS and EQ-5D-5L index values were analysed by using partial proportional odds models and multivariate linear regressions. RESULTS: Respondents that scored higher on the past-negative and present-fatalist and lower on the present-hedonist and future subscales were more likely to report more health problems in at least one EQ-5D-5L domain (p < 0.05). Adjusting for socio-economic and health status, three EQ-5D-5L domains exhibited significant associations with various TP subscales (usual activities: present-fatalist and future, pain/discomfort: past-negative and future, anxiety/depression: past-negative, present-fatalist, present-hedonist and future). The anxiety/depression domain showed evidence of cut-point shift. CONCLUSIONS: This study identified response heterogeneity stemming from psychological characteristics in self-reported health on the EQ-5D-5L. TP seems to play a double role in self-reported health, firstly as affecting underlying health and secondly as a factor influencing one's response behavior. These findings increase our understanding of the non-health-related factors that affect self-reported health on standardized health status measures.

Response heterogeneity as a new biomarker of treatment response in patients with neuroendocrine tumors.

Aim: The RAISE project aimed to find a surrogate end point to predict treatment response early in patients with enteropancreatic neuroendocrine tumors (NET). Response heterogeneity, defined as the coexistence of responding and non-responding lesions, has been proposed as a predictive marker for progression-free survival (PFS) in patients with NETs. Patients & methods: Computerized tomography scans were analyzed from patients with multiple lesions in CLARINET (NCT00353496; n = 148/204). Cox regression analyses evaluated association between response heterogeneity, estimated using the standard deviation of the longest diameter ratio of target lesions, and NET progression. Results: Greater response heterogeneity at a given visit was associated with earlier progression thereafter: week 12 hazard ratio (HR; 95% confidence interval): 1.48 (1.20-1.82); p < 0.001; n = 148; week 36: 1.72 (1.32-2.24); p < 0.001; n = 108. HRs controlled for sum of longest diameter ratio: week 12: 1.28 (1.04-1.59); p = 0.020 and week 36: 1.81 (1.20-2.72); p = 0.005. Conclusion: Response heterogeneity independently predicts PFS in patients with enteropancreatic NETs. Further validation is required.

Neuroendocrine tumors (NET) are rare, slow-growing cancers that can grow in various parts of the body. By understanding how NETs are responding to treatment, doctors can choose the best treatment for a patient and monitor whether the treatment needs to be changed. Treatment response is determined using 'Response Evaluation Criteria in Solid Tumors (RECIST)': a technique which measures the size of tumors to assess whether they are shrinking. However, RECIST is not always useful in NETs, which grow slowly and rarely shrink. 'Response heterogeneity' describes the situation in which some tumors respond well to treatment, while other tumors in the same patient do not. Response heterogeneity may be important in understanding how tumors are responding to treatment and predicting outcomes for patients. Until now, the link between response heterogeneity and treatment response has not been studied in patients with NETs. The RAISE project examined data from a clinical trial of patients with NETs treated with lanreotide. In RAISE, response heterogeneity was estimated using imaging scans of NETs. Response heterogeneity was compared with factors such as tumor size and amounts of certain molecules found in the blood, to see how well response heterogeneity could predict outcomes for patients with NETs. In this study, response heterogeneity was linked with worse outcomes for patients. Therefore, it may be useful in understanding how NETs respond to treatment. Further research is needed in a different group of patients with NETs, and in patients receiving other treatments, to better understand response heterogeneity.

Baseline host determinants of robust human HIV-1 vaccine-induced immune responses: A meta-analysis of 26 vaccine regimens.

BACKGROUND: The identification of baseline host determinants that associate with robust HIV-1 vaccine-induced immune responses could aid HIV-1 vaccine development. We aimed to assess both the collective and relative performance of baseline characteristics in classifying individual participants in nine different Phase 1-2 HIV-1 vaccine clinical trials (26 vaccine regimens, conducted in Africa and in the Americas) as High HIV-1 vaccine responders. METHODS: This was a meta-analysis of individual participant data, with studies chosen based on participant-level (vs. study-level summary) data availability within the HIV-1 Vaccine Trials Network. We assessed the performance of 25 baseline characteristics (demographics, safety haematological measurements, vital signs, assay background measurements) and estimated the relative importance of each characteristic in classifying 831 participants as High (defined as within the top 25th percentile among positive responders or above the assay upper limit of quantification) versus Non-High responders. Immune response outcomes included HIV-1-specific serum IgG binding antibodies and Env-specific CD4+ T-cell responses assessed two weeks post-last dose, all measured at central HVTN laboratories. Three variable importance approaches based on SuperLearner ensemble machine learning were considered. FINDINGS: Overall, 30.1%, 50.5%, 36.2%, and 13.9% of participants were categorized as High responders for gp120 IgG, gp140 IgG, gp41 IgG, and Env-specific CD4+ T-cell vaccine-induced responses, respectively. When including all baseline characteristics, moderate performance was achieved for the classification of High responder status for the binding antibody responses, with cross-validated areas under the ROC curve (CV-AUC) of 0.72 (95% CI: 0.68, 0.76) for gp120 IgG, 0.73 (0.69, 0.76) for gp140 IgG, and 0.67 (95% CI: 0.63, 0.72) for gp41 IgG. In contrast, the collection of all baseline characteristics yielded little improvement over chance for predicting High Env-specific CD4+ T-cell responses [CV-AUC: 0.53 (0.48, 0.58)]. While estimated variable importance patterns differed across the three approaches, female sex assigned at birth, lower height, and higher total white blood cell count emerged as significant predictors of High responder status across multiple immune response outcomes using Approach 1. Of these three baseline variables, total white blood cell count ranked highly across all three approaches for predicting vaccine-induced gp41 and gp140 High responder status. INTERPRETATION: The identified features should be studied further in pursuit of intervention strategies to improve vaccine responses and may be adjusted for in analyses of immune response data to enhance statistical power. FUNDING: National Institute of Allergy and Infectious Diseases (UM1AI068635 to YH, UM1AI068614 to GDT, UM1AI068618 to MJM, and UM1 AI069511 to MCK), the Duke CFAR P30 AI064518 to GDT, and National Institute of Dental and Craniofacial Research (R01DE027245 to JJK). This work was also supported by the Bill and Melinda Gates Foundation. The content is solely the responsibility of the authors and does not necessarily represent the official views of any of the funding sources.

Response to school-based interventions for overweight and obesity: A systematic scoping review.

Heterogeneity of response to paediatric obesity interventions is one of the greatest challenges to obesity care. While evaluating school-based interventions by mean changes compared to control is important, it does not provide an understanding of the individual variability in response to intervention. The objective of this study was to comprehensively review school-based interventions that reported study results in terms of response and identify definitions of response used. A scoping review was conducted using a systematic search of five scientific databases from 2009 to 2021. Inclusion criteria included randomized controlled trial design, school-based setting, weight-based outcomes (e.g., BMI, BMI z-score), weight-based outcomes analysed among youth with overweight/obesity, a study conducted in a developed country and publication in English. A total of 26 reports representing 25 unique studies were included. Overall, 19% (5/26) of articles reported response. Response was defined in three ways: maintenance/decrease in BMI z-score, decrease in BMI z-score ≥0.10, and decrease in BMI z-score ≥0.20. Few school-based interventions identified an a priori intervention goal or identified the proportion of participants who responded to the intervention. Without such evaluation participants who do not benefit are likely to be overlooked.

An Investigation of Age-Related Differential Item Functioning in the EQ-5D-5L Using Item Response Theory and Logistic Regression.

OBJECTIVES: In economic evaluations, quality of life is measured using patient-reported outcome measures (PROMs), such as the EQ-5D-5L. A key assumption for the validity of PROMs data is measurement invariance, which requires that PROM items and response options are interpreted the same across respondents. If measurement invariance is violated, PROMs exhibit differential item functioning (DIF), whereby individuals from different groups with the same underlying health respond differently, potentially biasing scores. One important group of healthcare consumers who have been shown to have different views or priorities over health is older adults. This study investigates age-related DIF in the EQ-5D-5L using item response theory (IRT) and ordinal logistic regression approaches. METHODS: Multiple-group IRT models were used to investigate DIF, by assessing whether older adults aged 65+ years and younger adults aged 18 to 64 years with the same underlying health had different IRT parameter estimates and expected item and EQ-5D-5L level sum scores. Ordinal logistic regression was also used to examine whether DIF resulted in meaningful differences in expected EQ level sum scores. Effect sizes examined whether DIF indicated meaningful score differences. RESULTS: The anxiety/depression item exhibited meaningful DIF in both approaches, with older adults less likely to report problems. Pain/discomfort and mobility exhibited DIF to a lesser extent. CONCLUSIONS: When using the EQ-5D-5L to evaluate interventions and make resource allocation decisions, scoring bias due to DIF should be controlled for to prevent inefficient service provision, where the most cost-effective services are not provided, which could be detrimental to patients and the efficiency of health budgets.

Encouragement of subgroup assessment by the FDA.

Responses to a drug treatment can differ among subgroups of the population, including demographic subgroups, groups with different disease characteristics, and groups with different metabolic or excretory functions. The differences can be pharmacokinetic (PK) or pharmacodynamic (PD) affecting toxicity or effectiveness. In recent years wide availability of drug blood level data, including metabolite data, has made PK differences in subgroups very readily detectable, but PD differences are more difficult to detect and need to be carefully examined by assessment of effectiveness and toxicity in demographic and other subgroups, as illustrated by the forest plots examining multiple subgroups typically presented for cardiovascular outcome studies. Such examinations and presentations would probably be more broadly useful and informative if used to examine pooled outcome and toxicity data for symptomatic treatments.

BAGS: A Bayesian Adaptive Group Sequential Trial Design With Subgroup-Specific Survival Comparisons.

A Bayesian group sequential design is proposed that performs survival comparisons within patient subgroups in randomized trials where treatment-subgroup interactions may be present. A latent subgroup membership variable is assumed to allow the design to adaptively combine homogeneous subgroups, or split heterogeneous subgroups, to improve the procedure's within-subgroup power. If a baseline covariate related to survival is available, the design may incorporate this information to improve subgroup identification while basing the comparative test on the average hazard ratio. General guidelines are provided for calibrating prior hyperparameters and design parameters to control the overall Type I error rate and optimize performance. Simulations show that the design is robust under a wide variety of different scenarios. When two or more subgroups are truly homogeneous but differ from the other subgroups, the proposed method is substantially more powerful than tests that either ignore subgroups or conduct a separate test within each subgroup. Supplementary materials for this article are available online.

Heterogeneity analysis of MRI T2 maps for measurement of early tumor response to radiotherapy.

External beam radiotherapy (XRT) is a widely used cancer treatment, yet responses vary dramatically among patients. These differences are not accounted for in clinical practice, partly due to a lack of sensitive early response biomarkers. We hypothesize that quantitative magnetic resonance imaging (MRI) measures reflecting tumor heterogeneity can provide a sensitive and robust biomarker of early XRT response. MRI T2 mapping was performed every 72 hours following 10 Gy dose XRT in two models of pancreatic cancer propagated in the hind limb of mice. Interquartile range (IQR) of tumor T2 was presented as a potential biomarker of radiotherapy response compared with tumor growth kinetics, and biological validation was performed through quantitative histology analysis. Quantification of tumor T2 IQR showed sensitivity for detection of XRT-induced tumor changes 72 hours after treatment, outperforming T2-weighted and diffusion-weighted MRI, with very good robustness. Histological comparison revealed that T2 IQR provides a measure of spatial heterogeneity in tumor cell density, related to radiation-induced necrosis. Early IQR changes were found to correlate to subsequent tumor volume changes, indicating promise for treatment response prediction. Our preclinical findings indicate that spatial heterogeneity analysis of T2 MRI can provide a translatable method for early radiotherapy response assessment. We propose that the method may in future be applied for personalization of radiotherapy through adaptive treatment paradigms.

Heterogeneous Responses to Mechanical Force of Prostate Cancer Cells Inducing Different Metastasis Patterns.

The physical cues in the extracellular environment play important roles in cancer cell metastasis. However, how metastatic cancer cells respond to the diverse mechanical environments of metastatic sites is not fully understood. Here, substrates with different mechanical properties are prepared to simulate the extracellular mechanical environment of various human tissues. The prostate cancer (PC) cells derived from different cancer metastasis sites show heterogeneity in mechanical response. This heterogeneity mediates two distinct metastasis patterns. High stiffness promotes individual cell migration and proliferation by inducing Yes-associated protein and tafazzin (YAP/TAZ) nuclear localization in bone metastasis-derived cells, whereas low stiffness promotes cell migration and proliferation by inducing lymphatic metastasis-derived cells to form clusters characterized by high expression of CD44. The different metastasis patterns induced by the mechanical properties of the extracellular environment are crucial in the development of PC.

Functional and Symptomatic Individuality in the Response to Levothyroxine Treatment.

Background: For significant numbers of patients dissatisfied on standard levothyroxine (LT4) treatment for hypothyroidism, patient-specific responses to T4 could play a significant role. Aim: To assess response heterogeneity to LT4 treatment, identifying confounders and hidden clusters within a patient panel, we performed a secondary analysis using data from a prospective cross-sectional and retrospective longitudinal study. Methods: Multivariate and multivariable linear models adjusted for covariates (gender, age, and BMI) were stratified by disease-specific treatment indication. During follow-up, pooled observations were compared from the same patient presenting either with or without self-reported symptoms. Statistical analysis was extended to multilevel models to derive intra-class correlation coefficients and reliability measures during follow-up. Results: Equilibria between TSH, FT4, and FT3 serum concentrations in 342 patients were examined by treatment indication (benign goiter, autoimmune thyroiditis, thyroid carcinoma), consequently displaying complex interactive response patterns. Seventy-seven patients treated with LT4 and monitored for thyroid carcinoma presented, in association with changes in LT4 dose, either with hypothyroid symptoms or symptom-free. Significant biochemical differences appeared between the different presentations. Leveled trajectories by subject to relief from hypothyroid symptoms differed significantly, indicating distinct responses, and denying a single shared outcome. These were formally defined by a high coefficient of the intraclass correlation (ICC1, exceeding 0.60 in all thyroid parameters) during follow-up on multiple visits at the same LT4 dose, when lacking symptoms. The intra-personal clusters were clearly differentiated from random variability by random group resampling. Symptomatic change in these patients was strongly associated with serum FT3, but not with FT4 or TSH concentrations. In 25 patients transitioning from asymptomatic to symptomatically hyperthyroid, FT3 concentrations remained within the reference limits, whilst at the same time marked biochemical differences were apparent between the presentations. Conclusions: Considerable intra-individual clustering occurred in the biochemical and symptomatic responses to LT4 treatment, implying statistically multileveled response groups. Unmasking individual differences in the averaged treatment response hereby highlights clinically distinguishable subgroups within an indiscriminate patient panel. This, through well-designed larger clinical trials will better target the different therapeutic needs of individual patients.

Issues in the determination of 'responders' and 'non-responders' in physiological research.

NEW FINDINGS: What is the topic for this review? We discuss the dichotomization of continuous-level physiological measurements into 'responders' and 'non-responders' when interventions/treatments are examined in robust parallel-group studies. What advances does it highlight? Sample responder counts are biased by pre-to-post within-subject variability. Sample differences in counts may be explained wholly by differences in mean response, even without individual response heterogeneity and even if test-retest measurement error informs the choice of response threshold. A less biased and more informative approach uses the SD of individual responses to estimate the chance a new person from the population of interest will be a responder. ABSTRACT: As a follow-up to our 2015 review, we cover more issues on the topic of 'response heterogeneity', which we define as clinically important individual differences in the physiological responses to the same treatment/intervention that cannot be attributed to random within-subject variability. We highlight various pitfalls with the common practice of counting the number of 'responders', 'non-responders' and 'adverse responders' in samples that have been given certain treatments or interventions for research purposes. We focus on the classical parallel-group randomized controlled trial and assume typical good practice in trial design. We show that sample responder counts are biased because individuals differ in terms of pre-to-post within-subject random variability in the study outcome(s) and not necessarily treatment response. Ironically, sample differences in responder counts may be explained wholly by sample differences in mean response, even if there is no response heterogeneity at all. Sample comparisons of responder counts also have relatively low statistical precision. These problems do not depend on how the response threshold has been selected, e.g. on the basis of a measurement error statistic, and are not rectified fully by the use of confidence intervals for individual responses in the sample. The dichotomization of individual responses in a research sample is fraught with pitfalls. Less biased approaches for estimating the proportion of responders in a population of interest are now available. Importantly, these approaches are based on the SD for true individual responses, directly incorporating information from the control group.

Time-dependent AI-Modeling of the anticancer efficacy of synthesized gallic acid analogues.

BACKGROUND/AIM: Main objective of this study is mapping of the anticancer efficacy of synthesized gallic acid analogues using modeling and artificial intelligence (AI) over a large range of concentrations and exposure times to explore the underline mechanisms of drug action and draw careful inferences regarding drug response heterogeneity. METHODS: Two series of gallic acid derivatives i.e. esters and amides have been synthesized and characterized by FTIR, NMR and mass spectrometry. The compounds have been tested in vitro for their anticancer activity against wild type human ovarian cancer cell line A2780, prostate cancer cell line PC3 and normal human fibroblast cells 3T3. To completely characterize optimal anticancer activity, a comprehensive model using piecewise recursive Hill model is used to quantitatively assess the in vitro anticancer effect of the tested compounds as a function of concentration and exposure time for periods ranging from 24 to 72 h. A robust artificial intelligence approach i.e. the "Support Vector Machine (SVM) Learning Algorithm" is adopted to utilize the data obtained at different temporal values, to identify compounds that trail forecasting algorithm. RESULTS: All the synthesized analogues were found biocompatible. Significantly low EC50 values indicated that tested compounds have potent anticancer activity against A2780 cell line in comparison to PC3 cells where only few compounds generated same impact at almost 200 times high dose. On the basis of EC50 values, compounds 7 h, 7 m, 9c, 9b, 7c, 7b and 7 g were identified as the most active anticancer agent against A2780. Three major patterns of drug response heterogeneity were observed for different compounds in the form of multiple Hill graphs and shallow slopes. The anticancer efficiency of the compounds was verified using Machine learning SVM regression learner algorithm. For compounds 7a, 7b, 7e, 7 g, 7o, 7 r, 9b, 9e-9 g higher accuracy was found in predicted and experimentally obtained end point potency in terms of % viability. CONCLUSIONS: Pharmacodynamics modeling of anticancer potential of the synthesized compounds revealed that drug efficacy and response heterogeneity could be modulated by changing the exposure time to optimize therapeutic impact. Combining experimental results with AI based drug action forecasting, compounds 7b, 7 g, and 9b may be tested further as potent anticancer agent for in vivo studies. This approach may serve a useful tool for extrapolation of in vitro results for generating lead compounds in in vivo and preclinical studies.

A Multi-Center Comparison of O2peak Trainability Between Interval Training and Moderate Intensity Continuous Training.

There is heterogeneity in the observed O2peak response to similar exercise training, and different exercise approaches produce variable degrees of exercise response (trainability). The aim of this study was to combine data from different laboratories to compare O2peak trainability between various volumes of interval training and Moderate Intensity Continuous Training (MICT). For interval training, volumes were classified by the duration of total interval time. High-volume High Intensity Interval Training (HIIT) included studies that had participants complete more than 15 min of high intensity efforts per session. Low-volume HIIT/Sprint Interval Training (SIT) included studies using less than 15 min of high intensity efforts per session. In total, 677 participants across 18 aerobic exercise training interventions from eight different universities in five countries were included in the analysis. Participants had completed 3 weeks or more of either high-volume HIIT (n = 299), low-volume HIIT/SIT (n = 116), or MICT (n = 262) and were predominately men (n = 495) with a mix of healthy, elderly and clinical populations. Each training intervention improved mean O2peak at the group level (P < 0.001). After adjusting for covariates, high-volume HIIT had a significantly greater (P < 0.05) absolute O2peak increase (0.29 L/min) compared to MICT (0.20 L/min) and low-volume HIIT/SIT (0.18 L/min). Adjusted relative O2peak increase was also significantly greater (P < 0.01) in high-volume HIIT (3.3 ml/kg/min) than MICT (2.4 ml/kg/min) and insignificantly greater (P = 0.09) than low-volume HIIT/SIT (2.5 mL/kg/min). Based on a high threshold for a likely response (technical error of measurement plus the minimal clinically important difference), high-volume HIIT had significantly more (P < 0.01) likely responders (31%) compared to low-volume HIIT/SIT (16%) and MICT (21%). Covariates such as age, sex, the individual study, population group, sessions per week, study duration and the average between pre and post O2peak explained only 17.3% of the variance in O2peak trainability. In conclusion, high-volume HIIT had more likely responders to improvements in O2peak compared to low-volume HIIT/SIT and MICT.

Response heterogeneity in fitness, mobility and cognition with exercise-training in MS.

BACKGROUND: Exercise-training is a beneficial approach for improving function in persons with multiple sclerosis (MS). However, it is unlikely that every participant who engages in an exercise-training intervention will demonstrate similar benefits. Identifying factors that may influence the accrual of specific exercise-training benefits can aid in the development of optimized rehabilitation interventions for improving specific outcomes in MS. OBJECTIVE: This study described possible response heterogeneity in physical fitness, mobility and cognitive outcomes with exercise-training and identified baseline performance, compliance and demographic/clinical outcomes as possible predictors of exercise-related changes in those outcomes. METHODS: Thirty-two persons with MS-related mobility disability completed 6-months of multimodal exercise-training. Physical fitness, mobility and cognitive processing speed (CPS) were measured before and after the 6 months. RESULTS: There was response heterogeneity in fitness, mobility and cognitive outcomes with multimodal exercise-training. Low baseline aerobic fitness, slow walking speed and slow CPS were associated with greater exercise-related improvements in those respective outcomes. CONCLUSIONS: Those with MS-related mobility disability who have the lowest aerobic fitness, walking speed and CPS might benefit the most from multimodal exercise-training. This provides critical evidence for informing the development of a precision medicine framework for improving targeted outcomes with exercise-training in MS.

Response Heterogeneity With Exercise Training and Physical Activity Interventions Among Persons With Multiple Sclerosis.

Multiple sclerosis (MS) is a heterogeneous disease, both in its pathology and symptomology. This poses a challenge for the medical management and rehabilitation of MS; however, physical activity and exercise training are rehabilitation approaches that have demonstrated beneficial effects on many of the burdensome consequences of MS such as mobility impairment and fatigue. Given the heterogeneous course of MS, it is possible that outcomes of physical activity and exercise training interventions demonstrate heterogeneity both in the magnitude and pattern of change, but there has been little focus on response heterogeneity with these interventions among persons with MS. In this narrative review, a search of the existing literature was performed to identify studies that reported individual participant data, which was used to describe the variability in the response to physical activity and exercise training interventions among persons with MS. Inter-individual variability seemingly occurs across outcomes and modalities, which underscores the consideration of factors that might influence response heterogeneity. Factors related to MS disease characteristics, nervous system damage, and the degree of MS-related disability might influence individual responsiveness. Large-scale studies that permit the examination of heterogeneity and its predictors will inform future research on the area of physical activity and exercise training in MS, and lead to the development of individually tailored rehabilitation approaches that will more effectively elicit change.

A Patient-Centered Approach to Comparative Effectiveness Research Focused on Older Adults: Lessons From the Patient-Centered Outcomes Research Institute.

The mission of the Patient-Centered Outcomes Research Institute (PCORI) is to fund the production of high-quality evidence that will enable patients and clinicians to make informed, personalized healthcare decisions. Since 2012, the PCORI has invested $177 million in patient-centered comparative effectiveness research (CER) that specifically targets the health needs of older adults, with additional relevant studies in its broader portfolio. Developing the PCORI's research portfolio has provided us with significant insights into what factors to consider when conducting CER in older adult populations. When comparing the net benefit of two or more interventions for older adults, investigators should consider the following: absolute risk difference, competing risks, life expectancy, the difference between chronologic and physiologic age, the importance of patient preferences, and other potential drivers of variable treatment effects. Investigators should also engage older adults and their caregivers as partners throughout the research process. Their input helps to identify key outcomes of interest and insights about the conduct of the research. As the PCORI continues to support research that addresses the healthcare decisions of the rapidly growing older adult population, it needs to partner with patients and researchers to identify the most important questions to address. J Am Geriatr Soc 67:21-28, 2019.

Response heterogeneity: Challenges for personalised medicine and big data approaches in psychiatry and chronic pain.

Response rates to available treatments for psychological and chronic pain disorders are poor, and there is a substantial burden of suffering and disability for patients, who often cycle through several rounds of ineffective treatment. As individuals presenting to the clinic with symptoms of these disorders are likely to be heterogeneous, there is considerable interest in the possibility that different constellations of signs could be used to identify subgroups of patients that might preferentially benefit from particular kinds of treatment. To this end, there has been a recent focus on the application of machine learning methods to attempt to identify sets of predictor variables (demographic, genetic, etc.) that could be used to target individuals towards treatments that are more likely to work for them in the first instance. Importantly, the training of such models generally relies on datasets where groups of individual predictor variables are labelled with a binary outcome category - usually 'responder' or 'non-responder' (to a particular treatment). However, as previously highlighted in other areas of medicine, there is a basic statistical problem in classifying individuals as 'responding' to a particular treatment on the basis of data from conventional randomized controlled trials. Specifically, insufficient information on the partition of variance components in individual symptom changes mean that it is inappropriate to consider data from the active treatment arm alone in this way. This may be particularly problematic in the case of psychiatric and chronic pain symptom data, where both within-subject variability and measurement error are likely to be high. Here, we outline some possible solutions to this problem in terms of dataset design and machine learning methodology, and conclude that it is important to carefully consider the kind of inferences that particular training data are able to afford, especially in arenas where the potential clinical benefit is so large.

Activity of Mesothelin-Specific Chimeric Antigen Receptor T Cells Against Pancreatic Carcinoma Metastases in a Phase 1 Trial.

Pancreatic ductal adenocarcinoma (PDAC) is resistant to T-cell-mediated immunotherapy. We engineered T cells to transiently express a messenger RNA encoding a chimeric antigen receptor (CAR) specific for mesothelin, a protein that is overexpressed by PDAC cells. We performed a phase I study to evaluate the safety and efficacy of adoptive cell therapy with autologous mesothelin-specific CAR T cells (CARTmeso cells) in 6 patients with chemotherapy-refractory metastatic PDAC. Patients were given intravenous CARTmeso cells 3 times weekly for 3 weeks. None of the patients developed cytokine release syndrome or neurologic symptoms and there were no dose-limiting toxicities. Disease stabilized in 2 patients, with progression-free survival times of 3.8 and 5.4 months. We used 18F-2-fluoro-2-deoxy-D-glucose (FDG)-positron emission tomography/computed tomography imaging to monitor the metabolic active volume (MAV) of individual tumor lesions. The total MAV remained stable in 3 patients and decreased by 69.2% in 1 patient with biopsy-proven mesothelin expression; in this patient, all liver lesions had a complete reduction in FDG uptake at 1 month compared with baseline, although there was no effect on the primary PDAC. Transient CAR expression was detected in patients' blood after infusion and led to expansion of new immunoglobulin G proteins. Our results provide evidence for the potential antitumor activity of messenger RNA CARTmeso cells, as well as PDAC resistance to the immune response.