Linear Models for Multivariate Repeated Measures Data

In this dissertation we focus mainly on the analysis of continuous multivariate repeated measurements data based on the assumption of multivariate normality. However certain aspects of the analysis of univariate repeated measures data are also considered. Typically, we have measurements on p variables (possibly correlated) in the form of px1 vectors yijk observed at k = 1,2, ...,tij occasions on j = 1,2, ..., ni individuals from i = 1,2, ..., g groups. We assume a naturally occurring covariance structure Vij ⊗ ∑ among the p variables on the jth individual from ith group made at tij occasions. Here Vij and ∑ are positive definite matrices of order tij x tij and p x p respectively. We develop a general linear model approach to accommodate both balanced and unbalanced repeated measures data. Our main results are: (1) construction of Rao\u27s score test for a simpler model with p=1 (univariate case) and Vij having a structure as in a mixed effects model, (2) comparison of all the methods for analyzing univariate repeated measures data with time varying covariates, (3) derivation of the maximum likelihood estimates of the covariance matrices V and ∑ in the balanced case, (4) derivation of Satterthwaite type approximation to the distribution of multivariate quadratic forms, (5) estimation of degrees of freedom for these approximations, and (6) derivation of the maximum likelihood estimates of the covariance parameters under certain specific covariance structures for unbalanced case. Rao\u27s score test is derived in Chapter 2. Analysis of repeated measures in the presence of time varying covariates is a useful but difficult problem. In Chapter 3, we review the existing methods for analyzing repeated measured data with time varying covariates and discuss their computational aspects using SAS software. We also point out that a linear model approach yields a unified tool to analyze these data. In Chapter 4, various results about balanced multivariate repeated measures models are derived. We present the entire scheme of analysis of balanced multivariate data including the computational details. Finally, the analysis of unbalanced multivariate repeated measures is discussed in Chapter 5. In this case we assume two commonly used covariance structures namely equicorrelation and autoregressive structures for Vij and derive the maximum likelihood estimates of the unknown parameters

Glaucoma-associated long-term mortality in a rural cohort from India: the Andhra Pradesh Eye Disease Study.

AIM: To evaluate glaucoma-associated mortality in a rural cohort in India. METHODS: The study cohort comprised individuals aged 40 years and above who took part in the Andhra Pradesh Eye Disease Study (APEDS1) during 1996-2000. All participants underwent detailed comprehensive eye examination. Glaucoma was defined using International Society of Geographic and Epidemiologic Ophthalmology criteria. This cohort was followed up after a decade (June 2009 to January 2010; APEDS2). Mortality HR analysis for ocular risk factors was performed using Cox proportional hazards regression after adjusting for sociodemographic, lifestyle and clinical variables. RESULTS: In APEDS1, 2790 individuals aged more than or equal to 40 years were examined. 47.4% were male. Forty-five participants had primary open angle glaucoma (POAG) and 66 had primary angle closure disease (PACD). Ten years later, 1879 (67.3%) were available, 739 (26.5%) had died and 172 (6.2%) had migrated; whereas 22 of the 45 (48.8%) with POAG and 22 of the 66 (33.3%) with PACD had died. In univariate analysis, a higher mortality was associated with POAG (HR 1.9; 95% CI 1.23 to 2.94), pseudoexfoliation (HR 2.79; 95% CI 2.0 to 3.89), myopia (HR 1.78; 95% CI 1.54 to 2.06) and unit increase in cup:disc ratio (HR 4.49; 95% CI 2.64 to 7.64). In multivariable analysis, only cup:disc ratio remained independently associated with mortality (HR 2.5; 95% CI 1.3 to 5.1). The association remained significant when other ocular parameters were included in the model (HR 2.1; 95% CI 1.03 to 4.2). CONCLUSIONS: This is the first longitudinal study to assess the association of glaucoma and mortality in a rural longitudinal cohort in India. Increased cup:disc ratio could be a potential marker for ageing and would need further validation

Cataract, visual impairment and long-term mortality in a rural cohort in India: the Andhra Pradesh Eye Disease Study.

BACKGROUND: A large-scale prevalence survey of blindness and visual impairment (The Andhra Pradesh Eye Diseases Study [APEDS1]) was conducted between 1996-2000 on 10,293 individuals of all ages in three rural and one urban clusters in Andhra Pradesh, Southern India. More than a decade later (June 2009-March 2010), APEDS1 participants in rural clusters were traced (termed APEDS2) to determine ocular risk factors for mortality in this longitudinal cohort. METHODS AND FINDINGS: Mortality hazard ratio (HR) analysis was performed for those aged >30 years at APEDS1, using Cox proportional hazard regression models to identify associations between ocular exposures and risk of mortality. Blindness and visual impairment (VI) were defined using Indian definitions. 799/4,188 (19.1%) participants had died and 308 (7.3%) had migrated. Mortality was higher in males than females (p<0.001). In multivariable analysis, after adjusting for age, gender, diabetes, hypertension, body mass index, smoking and education status the mortality HR was 1.9 (95% CI: 1.5-2.5) for blindness; 1.4 (95% CI: 1.2-1.7) for VI; 1.8 (95% CI: 1.4-2.3) for pure nuclear cataract, 1.5 (95% CI: 1.1-2.1) for pure cortical cataract; 1.96 (95% CI: 1.6-2.4) for mixed cataract, 2.0 (95% CI: 1.4-2.9) for history of cataract surgery, and 1.58 (95% CI: 1.3-1.9) for any cataract. When all these factors were included in the model, the HRs were attenuated, being 1.5 (95% CI: 1.1-2.0) for blindness and 1.2 (95% CI: 0.9-1.5) for VI. For lens type, the HRs were as follows: pure nuclear cataract, 1.6 (95% CI: 1.3-2.1); pure cortical cataract, 1.5 (95% CI: 1.1-2.1); mixed cataract, 1.8 (95% CI: 1.4-2.2), and history of previous cataract surgery, 1.8 (95% CI: 1.3-2.6). CONCLUSIONS: All types of cataract, history of cataract surgery and VI had an increased risk of mortality that further suggests that these could be potential markers of ageing

A multi-targeted approach to suppress tumor-promoting inflammation

Cancers harbor significant genetic heterogeneity and patterns of relapse following many therapies are due to evolved resistance to treatment. While efforts have been made to combine targeted therapies, significant levels of toxicity have stymied efforts to effectively treat cancer with multi-drug combinations using currently approved therapeutics. We discuss the relationship between tumor-promoting inflammation and cancer as part of a larger effort to develop a broad-spectrum therapeutic approach aimed at a wide range of targets to address this heterogeneity. Specifically, macrophage migration inhibitory factor, cyclooxygenase-2, transcription factor nuclear factor-κB, tumor necrosis factor alpha, inducible nitric oxide synthase, protein kinase B, and CXC chemokines are reviewed as important antiinflammatory targets while curcumin, resveratrol, epigallocatechin gallate, genistein, lycopene, and anthocyanins are reviewed as low-cost, low toxicity means by which these targets might all be reached simultaneously. Future translational work will need to assess the resulting synergies of rationally designed antiinflammatory mixtures (employing low-toxicity constituents), and then combine this with similar approaches targeting the most important pathways across the range of cancer hallmark phenotypes

Combination of everolimus with trastuzumab plus paclitaxel as first-line treatment for patients with HER2-positive advanced breast cancer (BOLERO-1) : a phase 3, randomised, double-blind, multicentre trial

BACKGROUND : mTOR inhibition has been shown to reverse trastuzumab resistance from hyperactivated the PIK/AKT/mTOR pathway due to PTEN loss, by sensitizing PTEN-deficient tumors towards trastuzumab. The BOLERO-1 study evaluated the efficacy and safety of adding everolimus to trastuzumab and paclitaxel as first-line therapy for HER2+ advanced breast cancer (ABC). METHODS : In this phase III, randomized, double-blind trial, patients were enrolled across 141 sites in 28 countries. Eligible patients were ≥18 years of age, with locally assessed HER2+ advanced breast cancer (ABC), with Eastern Cooperative Oncology Group performance status of 0-1, who had not received prior trastuzumab or chemotherapy for ABC, had measurable disease as per Response Evaluation Criteria in Solid Tumors or bone lesions in the absence of measurable disease, without prior systemic therapy for advanced disease except endocrine therapy. The patients were randomized 2:1 (with an interactive voice and web response system) to receive either daily everolimus (10 mg/day) orally or placebo plus weekly trastuzumab intravenously at 4 mg/kg loading dose on Day-1 with subsequent weekly doses of 2 mg/kg of each 4-week cycle plus paclitaxel intravenously at a dose of 80 mg/m2 on days 1, 8, and 15 of each 4- week cycle. Randomization was stratified according to prior use of trastuzumab and visceral metastasis. Patients and investigators were blinded to the assigned treatments. Identity of experimental treatments was concealed by use of everolimus and placebo that were identical in packaging, labelling, appearance, and administration schedule. The two primary objectives were investigator-assessed progression-free survival (PFS) in the full study population and in the subset of patients with hormone receptor-negative (HR) breast cancer at baseline; the latter was added during the course of the study, prior to unblinding based on new clinical and biological findings from other studies. All efficacy analyses were based on the intention-to-treat population. Enrolment for this trial is closed and results of the final PFS analyses are presented here. Clinicaltrials.gov identifier: NCT00876395. FINDINGS : Between 10-Sep-2009 and 16-Dec-2012, 719 patients were randomized to receive everolimus (n=480) or placebo (n=239). Median follow-up was 41.3 months (IQR: 35.4 – 46.6 months). INTERPRETATION : The primary objective in the full population was not met; median PFS was 15.0 months with everolimus vs 14.5 months with placebo (hazard ratio, 0.89; 95% CI, 0.73-1.08; p=0.1166). In the HR subpopulation (n=311), median PFS with everolimus was 20.3 months vs 13.1 months with placebo (hazard ratio, 0.66; 95% CI, 0.48-0.91; p=0.0049), however, the protocol-specified statistical significance threshold (p=0.0044) was not crossed. The most common adverse events (AEs) with everolimus vs placebo were stomatitis (314 [66.5%] vs 77 [32.4%] patients), diarrhea (267 [56.6%] vs 111 [46.6%] patients), and alopecia (221 [46.8%] vs 125 [52.5%]). The most frequently reported grade 3/4 AEs in the EVE arm vs PBO arm were neutropenia (117 [24.8%] of 472 patients vs 35 [14.7%] of 238 patients), stomatitis (59 [12.5%] of 472 patients vs 3 [1.3%] of 238 patients), anemia (46 [9.7%] of 472 patients vs 6 [2.5%] of 238 patients) and diarrhea (43 [9.1%] of 472 patients vs 10 [4.2%] of 238 patients) On-treatment AE-related deaths were reported in 17 [3.6%] vs 0% of patients respectively.Interpretation: The primary objective of PFS was not met. However, consistent with the preliminary observations from BOLERO-3, everolimus prolonged median PFS by 7.2 months in patients with HR, HER2+ ABC, which warrants further investigation. The safety profile was generally consistent with what was previously reported in BOLERO-3. Proactive monitoring and early management of AEs in patients treated with everolimus and chemotherapy is critical..Novartis Pharmaceuticals Corporation.http://www.journals.elsevier.com/the-lancet-oncology2016-07-31hb201

Experimental Study with Enhanced Vision System Prototype Unit

The National Civil Aircraft (NCA) being developed at National Aerospace Laboratories (NAL) is expected to have the capability of operation from airports with minimal infrastructure and instrumentation facility under all-weather conditions. The key enabling technology for this is an Integrated Enhanced and Synthetic Vision System (IESVS), which is a combination of Enhanced Vision System (EVS), Synthetic Vision System (SVS), and Head-Up Display. A prototype of EVS consisting of Forward Looking Infrared (FLIR) camera and CCD color camera is developed and tested at NAL. A Simulink block is developed to acquire the image data in real time (online) from a four channel frame grabber. An image fusion algorithm based on wavelets is developed to fuse the images from CCD and FLIR cameras. The affine transform used for image registration is computed by selecting the control points from both CCD and FLIR images. Test results from the experiments conducted on the runway during day and night (runway lights ON/OFF) conditions are presented

Experimental Study with Enhanced Vision System Prototype Unit- poster

The National Civil Aircraft (NCA) being developed at National Aerospace Laboratories (NAL) is expected to have the capability of operation from airports with minimal infrastructure and instrumentation facility under all-weather conditions. The key enabling technology for this is an Integrated Enhanced and Synthetic Vision System (IESVS), which is a combination of Enhanced Vision System (EVS), Synthetic Vision System (SVS), and Head-Up Display. A prototype of EVS consisting of Forward Looking Infrared (FLIR) camera and CCD color camera is developed and tested at NAL. A Simulink block is developed to acquire the image data in real time (online) from a four channel frame grabber. An image fusion algorithm based on wavelets is developed to fuse the images from CCD and FLIR cameras. The affine transform used for image registration is computed by selecting the control points from both CCD and FLIR images. Test results from the experiments conducted on the runway during day and night (runway lights ON/OFF) conditions are presented

Experimental Study with Enhanced Vision System Prototype Unit

The National Civil Aircraft (NCA) being developed at National Aerospace Laboratories (NAL) is expected to have the capability of operation from airports with minimal infrastructure and instrumentation facility under all-weather conditions. The key enabling technology for this is an Integrated Enhanced and Synthetic Vision System (IESVS), which is a combination of Enhanced Vision System (EVS), Synthetic Vision System (SVS), and Head-Up Display. A prototype of EVS consisting of Forward Looking Infra Red (FLIR) camera and CCD color camera is developed and tested at NAL. A Simulink block is developed to acquire the image data in real time (online) from a four channel frame grabber. An image fusion algorithm based on wavelets is developed to fuse the images from CCD and FLIR cameras. The affine transform used for image registration is computed by selecting the control points from both CCD and FLIR images. Test results from the experiments conducted on the runway during day and night (runway lights ON/OFF) conditions are presented

AIRCRAFT FUEL ESTIMATION BY LEAST SQUARE TECHNIQUE

A least square estimation technique has been proposed for in-flight fuel estimation for a high performance combat aircraft. This paper presents the details of least square models for aircraft fuel estimation, the procedure for building the least square models and their fidelity to estimate the fuel quantity in the multiple internal fuel tanks of the aircraft from flight data. The performance of the fuel estimation by least square technique has been verified with 56 different post flight data with different maneuvers including probe failure cases and compared with lookup table based estimates, the technique currently being used on the aircraft. Few results of fuel quantity estimates are presented and discussed. Sensitivity of the least square model based fuel estimation technique to probe failures has been studied by simulating multiple probe failures in flight data

Analysis of multivariate repeated measures data with a Kronecker product structured covariance matrix

In this article we consider a set of t repeated measurements on p variables (or characteristics) on each of the n individuals. Thus, data on each individual is a p 2 t matrix. The n individuals themselves may be divided and randomly assigned to g groups. Analysis of these data using a MANOVA model, assuming that the data on an individual has a covariance matrix which is a Kronecker product of two positive definite matrices, is considered. The well-known Satterthwaite type approximation to the distribution of a quadratic form in normal variables is extended to the distribution of a multivariate quadratic form in multivariate normal variables. The multivariate tests using this approximation are developed for testing the usual hypotheses. Results are illustrated on a data set. A method for analysing unbalanced data is also discussed.