Statistical Machine Learning Methodology for Individualized Treatment Rule Estimation in Precision Medicine

Precision medicine aims to deliver optimal, individualized treatments for patients by accounting for their unique characteristics. With a foundation in reinforcement learning, decision theory, and causal inference, the field of precision medicine has seen many advancements in recent years. Significant focus has been placed on creating algorithms to estimate individualized treatment rules (ITRs), which map from patient covariates to the space of available treatments with the goal of maximizing patient outcome. In Chapter 1, we extend ITR estimation methodology in the scenario where variance of the outcome is heterogeneous with respect to treatment and covariates. Accordingly, we propose Stabilized Direct Learning (SD-Learning), which utilizes heteroscedasticity in the error term through a residual reweighting framework that models residual variance via flexible machine learning algorithms such as XGBoost and random forests. We also develop an internal cross-validation scheme which determines the best residual model among competing models. Further, we extend this methodology to multi-arm treatment scenarios. In Chapter 2, we develop ITR estimation methodology for situations where clinical decision-making involves balancing multiple outcomes of interest. Our proposed framework estimates an ITR which maximizes a combination of the multiple clinical outcomes, accounting for the fact that patients may ascribe importance to outcomes differently (utility heterogeneity). This approach employs inverse reinforcement learning (IRL) techniques through an expert-augmentation solution, whereby physicians provide input to guide the utility estimation and ITR learning processes. In Chapter 3, we apply an end-to-end precision medicine workflow to novel data from older adults with Type 1 Diabetes in order to understand the heterogeneous treatment effects of continuous glucose monitoring (CGM) and develop an interpretable ITR to reveal patients for which CGM confers a major safety benefit. The results from this analysis elucidate the demographic and clinical markers which moderate CGM's success, provide the basis for using diagnostic CGM to inform therapeutic CGM decisions, and serve to augment clinical decision-making. Finally, in Chapter 4, as a future research direction, we propose a deep autoencoder framework which simultaneously performs feature selection and ITR optimization, contributing to methodology built for direct consumption of unstructured, high-dimensional data in the precision medicine pipeline.Doctor of Philosoph

Development and validation of multivariable prediction models for adverse COVID-19 outcomes in patients with IBD

Objectives Develop an individualised prognostic risk prediction tool for predicting the probability of adverse COVID-19 outcomes in patients with inflammatory bowel disease (IBD). Design and setting This study developed and validated prognostic penalised logistic regression models using reports to the international Surveillance Epidemiology of Coronavirus Under Research Exclusion for Inflammatory Bowel Disease voluntary registry from March to October 2020. Model development was done using a training data set (85% of cases reported 13 March–15 September 2020), and model validation was conducted using a test data set (the remaining 15% of cases plus all cases reported 16 September–20 October 2020). Participants We included 2709 cases from 59 countries (mean age 41.2 years (SD 18), 50.2% male). All submitted cases after removing duplicates were included. Primary and secondary outcome measures COVID-19 related: (1) Hospitalisation+: composite outcome of hospitalisation, ICU admission, mechanical ventilation or death; (2) Intensive Care Unit+ (ICU+): composite outcome of ICU admission, mechanical ventilation or death; (3) Death. We assessed the resulting models’ discrimination using the area under the curve of the receiver operator characteristic curves and reported the corresponding 95% CIs. Results Of the submitted cases, a total of 633 (24%) were hospitalised, 137 (5%) were admitted to the ICU or intubated and 69 (3%) died. 2009 patients comprised the training set and 700 the test set. The models demonstrated excellent discrimination, with a test set area under the curve (95% CI) of 0.79 (0.75 to 0.83) for Hospitalisation+, 0.88 (0.82 to 0.95) for ICU+ and 0.94 (0.89 to 0.99) for Death. Age, comorbidities, corticosteroid use and male gender were associated with a higher risk of death, while the use of biological therapies was associated with a lower risk. Conclusions Prognostic models can effectively predict who is at higher risk for COVID-19-related adverse outcomes in a population of patients with IBD. A free online risk calculator (https://covidibd.org/covid-19-risk-calculator/) is available for healthcare providers to facilitate discussion of risks due to COVID-19 with patients with IBD

Development of a Yoga-Based Cardiac Rehabilitation (Yoga-CaRe) Programme for Secondary Prevention of Myocardial Infarction

Cardiac rehabilitation (CR) after myocardial infarction is highly effective. It is unavailable in public hospitals in India due to limited resources. Our objective was to develop a scalable model of CR for India based on yoga, which could also appeal to some groups with low uptake of CR (e.g., ethnic minorities, women, and older people) globally. The intervention was developed using a structured process. A literature review and consultations with yoga experts, CR experts, and postmyocardial infarction patients were conducted to systematically identify and shortlist appropriate yoga exercises and postures, breathing exercises, meditation and relaxation practices, and lifestyle changes, which were incorporated into a conventional CR framework. The draft intervention was further refined based on the feedback from an internal stakeholder group and an external panel of international experts, before being piloted with yoga instructors and patients with myocardial infarction. A four-phase yoga-based CR (Yoga-CaRe) programme was developed for delivery by a single yoga instructor with basic training. The programme consists of a total of 13 instructor-led sessions (2 individual and 11 group) over a 3-month period. Group sessions include guided practice of yoga exercises and postures, breathing exercises, and meditation and relaxation practices, and support for the lifestyle change and coping through a moderated discussion. Patients are encouraged to self-practice daily at home and continue long-term with the help of a booklet and digital video disc (DVD). Family members/carers are encouraged to join throughout. In conclusion, a novel yoga-based CR programme has been developed, which promises to provide a scalable CR solution for India and an alternative choice for CR globally. It is currently being evaluated in a large multicentre randomised controlled trial across India

Yoga-Based Cardiac Rehabilitation After Acute Myocardial Infarction: A Randomized Trial.

BACKGROUND: Given the shortage of cardiac rehabilitation (CR) programs in India and poor uptake worldwide, there is an urgent need to find alternative models of CR that are inexpensive and may offer choice to subgroups with poor uptake (e.g., women and elderly). OBJECTIVES: This study sought to evaluate the effects of yoga-based CR (Yoga-CaRe) on major cardiovascular events and self-rated health in a multicenter randomized controlled trial. METHODS: The trial was conducted in 24 medical centers across India. This study recruited 3,959 patients with acute myocardial infarction with a median and minimum follow-up of 22 and 6 months. Patients were individually randomized to receive either a Yoga-CaRe program (n = 1,970) or enhanced standard care involving educational advice (n = 1,989). The co-primary outcomes were: 1) first occurrence of major adverse cardiovascular events (MACE) (composite of all-cause mortality, myocardial infarction, stroke, or emergency cardiovascular hospitalization); and 2) self-rated health on the European Quality of Life-5 Dimensions-5 Level visual analogue scale at 12 weeks. RESULTS: MACE occurred in 131 (6.7%) patients in the Yoga-CaRe group and 146 (7.4%) patients in the enhanced standard care group (hazard ratio with Yoga-CaRe: 0.90; 95% confidence interval [CI]: 0.71 to 1.15; p = 0.41). Self-rated health was 77 in Yoga-CaRe and 75.7 in the enhanced standard care group (baseline-adjusted mean difference in favor of Yoga-CaRe: 1.5; 95% CI: 0.5 to 2.5; p = 0.002). The Yoga-CaRe group had greater return to pre-infarct activities, but there was no difference in tobacco cessation or medication adherence between the treatment groups (secondary outcomes). CONCLUSIONS: Yoga-CaRe improved self-rated health and return to pre-infarct activities after acute myocardial infarction, but the trial lacked statistical power to show a difference in MACE. Yoga-CaRe may be an option when conventional CR is unavailable or unacceptable to individuals. (A study on effectiveness of YOGA based cardiac rehabilitation programme in India and United Kingdom; CTRI/2012/02/002408)

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Safety and efficacy of the ChAdOx1 nCoV-19 vaccine (AZD1222) against SARS-CoV-2: an interim analysis of four randomised controlled trials in Brazil, South Africa, and the UK.

BACKGROUND: A safe and efficacious vaccine against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), if deployed with high coverage, could contribute to the control of the COVID-19 pandemic. We evaluated the safety and efficacy of the ChAdOx1 nCoV-19 vaccine in a pooled interim analysis of four trials. METHODS: This analysis includes data from four ongoing blinded, randomised, controlled trials done across the UK, Brazil, and South Africa. Participants aged 18 years and older were randomly assigned (1:1) to ChAdOx1 nCoV-19 vaccine or control (meningococcal group A, C, W, and Y conjugate vaccine or saline). Participants in the ChAdOx1 nCoV-19 group received two doses containing 5 × 1010 viral particles (standard dose; SD/SD cohort); a subset in the UK trial received a half dose as their first dose (low dose) and a standard dose as their second dose (LD/SD cohort). The primary efficacy analysis included symptomatic COVID-19 in seronegative participants with a nucleic acid amplification test-positive swab more than 14 days after a second dose of vaccine. Participants were analysed according to treatment received, with data cutoff on Nov 4, 2020. Vaccine efficacy was calculated as 1 - relative risk derived from a robust Poisson regression model adjusted for age. Studies are registered at ISRCTN89951424 and ClinicalTrials.gov, NCT04324606, NCT04400838, and NCT04444674. FINDINGS: Between April 23 and Nov 4, 2020, 23 848 participants were enrolled and 11 636 participants (7548 in the UK, 4088 in Brazil) were included in the interim primary efficacy analysis. In participants who received two standard doses, vaccine efficacy was 62·1% (95% CI 41·0-75·7; 27 [0·6%] of 4440 in the ChAdOx1 nCoV-19 group vs71 [1·6%] of 4455 in the control group) and in participants who received a low dose followed by a standard dose, efficacy was 90·0% (67·4-97·0; three [0·2%] of 1367 vs 30 [2·2%] of 1374; pinteraction=0·010). Overall vaccine efficacy across both groups was 70·4% (95·8% CI 54·8-80·6; 30 [0·5%] of 5807 vs 101 [1·7%] of 5829). From 21 days after the first dose, there were ten cases hospitalised for COVID-19, all in the control arm; two were classified as severe COVID-19, including one death. There were 74 341 person-months of safety follow-up (median 3·4 months, IQR 1·3-4·8): 175 severe adverse events occurred in 168 participants, 84 events in the ChAdOx1 nCoV-19 group and 91 in the control group. Three events were classified as possibly related to a vaccine: one in the ChAdOx1 nCoV-19 group, one in the control group, and one in a participant who remains masked to group allocation. INTERPRETATION: ChAdOx1 nCoV-19 has an acceptable safety profile and has been found to be efficacious against symptomatic COVID-19 in this interim analysis of ongoing clinical trials. FUNDING: UK Research and Innovation, National Institutes for Health Research (NIHR), Coalition for Epidemic Preparedness Innovations, Bill & Melinda Gates Foundation, Lemann Foundation, Rede D'Or, Brava and Telles Foundation, NIHR Oxford Biomedical Research Centre, Thames Valley and South Midland's NIHR Clinical Research Network, and AstraZeneca

Safety and efficacy of the ChAdOx1 nCoV-19 vaccine (AZD1222) against SARS-CoV-2: an interim analysis of four randomised controlled trials in Brazil, South Africa, and the UK

Background A safe and efficacious vaccine against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), if deployed with high coverage, could contribute to the control of the COVID-19 pandemic. We evaluated the safety and efficacy of the ChAdOx1 nCoV-19 vaccine in a pooled interim analysis of four trials. Methods This analysis includes data from four ongoing blinded, randomised, controlled trials done across the UK, Brazil, and South Africa. Participants aged 18 years and older were randomly assigned (1:1) to ChAdOx1 nCoV-19 vaccine or control (meningococcal group A, C, W, and Y conjugate vaccine or saline). Participants in the ChAdOx1 nCoV-19 group received two doses containing 5 × 1010 viral particles (standard dose; SD/SD cohort); a subset in the UK trial received a half dose as their first dose (low dose) and a standard dose as their second dose (LD/SD cohort). The primary efficacy analysis included symptomatic COVID-19 in seronegative participants with a nucleic acid amplification test-positive swab more than 14 days after a second dose of vaccine. Participants were analysed according to treatment received, with data cutoff on Nov 4, 2020. Vaccine efficacy was calculated as 1 - relative risk derived from a robust Poisson regression model adjusted for age. Studies are registered at ISRCTN89951424 and ClinicalTrials.gov, NCT04324606, NCT04400838, and NCT04444674. Findings Between April 23 and Nov 4, 2020, 23 848 participants were enrolled and 11 636 participants (7548 in the UK, 4088 in Brazil) were included in the interim primary efficacy analysis. In participants who received two standard doses, vaccine efficacy was 62·1% (95% CI 41·0–75·7; 27 [0·6%] of 4440 in the ChAdOx1 nCoV-19 group vs71 [1·6%] of 4455 in the control group) and in participants who received a low dose followed by a standard dose, efficacy was 90·0% (67·4–97·0; three [0·2%] of 1367 vs 30 [2·2%] of 1374; pinteraction=0·010). Overall vaccine efficacy across both groups was 70·4% (95·8% CI 54·8–80·6; 30 [0·5%] of 5807 vs 101 [1·7%] of 5829). From 21 days after the first dose, there were ten cases hospitalised for COVID-19, all in the control arm; two were classified as severe COVID-19, including one death. There were 74 341 person-months of safety follow-up (median 3·4 months, IQR 1·3–4·8): 175 severe adverse events occurred in 168 participants, 84 events in the ChAdOx1 nCoV-19 group and 91 in the control group. Three events were classified as possibly related to a vaccine: one in the ChAdOx1 nCoV-19 group, one in the control group, and one in a participant who remains masked to group allocation. Interpretation ChAdOx1 nCoV-19 has an acceptable safety profile and has been found to be efficacious against symptomatic COVID-19 in this interim analysis of ongoing clinical trials

Finite Element Analysis to Characterize How Varying Patellar Loading Influences Pressure Applied to Cartilage: Model Evaluation

A finite element analysis (FEA) modeling technique has been developed to characterize how varying the orientation of the patellar tendon influences the patellofemoral pressure distribution. To evaluate the accuracy of the technique, models were created from MRI images to represent five knees that were previously tested in vitro to determine the influence of hamstrings loading on patellofemoral contact pressures. Hamstrings loading increased the lateral and posterior orientation of the patellar tendon. Each model was loaded at 40°, 60°, and 80° of flexion with quadriceps force vectors representing the experimental loading conditions. The orientation of the patellar tendon was represented for the loaded and unloaded hamstrings conditions based on experimental measures of tibiofemoral alignment. Similar to the experimental data, simulated loading of the hamstrings within the FEA models shifted the center of pressure laterally and increased the maximum lateral pressure. Significant (p \u3c 0.05) differences were identified for the center of pressure and maximum lateral pressure from paired t-tests carried out at the individual flexion angles. The ability to replicate experimental trends indicates that the FEA models can be used for future studies focused on determining how variations in the orientation of the patellar tendon related to anatomical or loading variations or surgical procedures influence the patellofemoral pressure distribution

Possible impact of the standardized Category IV regimen on multidrug-resistant tuberculosis patients in Mumbai

Background: Treatment of multidrug-resistant tuberculosis (MDR-TB) in the Programmatic Management of Drug-resistant TB program involves a standard regimen with a 6-month intensive phase and an 18-month continuation phase. However, the local drug resistance patterns in high MDR regions such as Mumbai may not be adequately reflected in the design of the regimen for that particular area. Setting: The study was carried out at a private Tertiary Level Hospital in Mumbai in a mycobacteriology laboratory equipped to perform the second-line drug susceptibility testing (DST). Objective: We attempted to analyze the impact of prescribing the standardized Category IV regimen to all patients receiving a DST at our mycobacteriology laboratory. Materials and Methods: All samples confirmed to be MDR-TB and tested for the second-line drugs at Hinduja Hospital′s Mycobacteriology Laboratory in the year 2012 were analyzed. Results: A total of 1539 samples were analyzed. Of these, 464 (30.14%) were MDR-TB, 867 (56.33%) were MDR with fluoroquinolone resistance, and 198 (12.8%) were extensively drug-resistant TB. The average number of susceptible drugs per sample was 3.07 ± 1.29 (assuming 100% cycloserine susceptibility). Taking 4 effective drugs to be the cut or an effective regimen, the number of patients receiving 4 or more effective drugs from the standardized directly observed treatment, short-course plus regimen would be 516 (33.5%) while 66.5% of cases would receive 3 or less effective drugs. Conclusion: Our study shows that a high proportion of patients will have resistance to a number of the first- and second-line drugs. Local epidemiology must be factored in to avoid amplification of resistance