Biomarker circadian rhythm profiles in critically ill mechanically ventilated patients

Objective: To explore the natural trajectory of core body temperature (CBT) and cortisol (CORT) circadian rhythms in mechanically ventilated intensive care unit (MV ICU) patients. ^ Design: Prospective, observational, time-series pilot study. ^ Setting: Medical-surgical and pulmonary ICUs in a tertiary care hospital. ^ Sample: Nine (F = 3, M = 6) adults who were mechanically ventilated within 12 hrs of ICU admission with mean ± SD age of 65.2 ± 14 years old. ^ Measurements: Core body temperature and environmental measures of light, sound, temperature, and relative humidity were logged in 1-min intervals. Hourly urine specimens and 2-hr interval blood specimens were collected for up to 7 consecutive days for CORT assay. Mechanical ventilation days, ICU length of stay, and ICU mortality were documented. Acute Physiology and Chronic Health Evaluation (APACHE) II scores were computed for each study day. The data of each biologic and environmental variable were analyzed using single cosinor analysis of 24-hr serial segments. One patient did not complete the study because mortality occurred within 8 hrs of enrollment. Nine ICU patients completed the study in 1.6 to 7.0 days. ^ Results: No normal circadian rhythm pattern was found when the cosinor-derived parameters of amplitude (one-half the peak-trough variability) and acrophase (peak time) were compared with cosinor-derived parameter reference ranges of healthy, diurnally active humans, although 83% of patient-day CBT segments showed statistically significant (p ≤ .05) and biologically meaningful (R2≥ 0.30) 24-hr rhythms with abnormal cosinor parameters. Cosinor parameters of the environmental temporal profiles showed 27% of light, 76% of ambient temperature, and 78% of relative humidity serial segments had a significant and meaningful 24-hr diurnal pattern. Average daily light intensity varied from 34 to 187 lx with a maximum light exposure of 1877 lx. No sound measurement segment had a statistically significant cosine pattern, and numerous 1-minute interval peaks ≥ 60 dB occurred around the clock. Average daily ambient temperature and relative humidity varied from 19 to 24°C and from 25% to 61%, respectively. There was no statistically significant association between CBT or clinical outcomes and cosinor-derived parameters of the environmental variables. Circadian rhythms of urine and plasma CORT were deferred for later analysis. ^ Conclusions: The natural trajectory of the CBT circadian rhythm in MV ICU patients demonstrated persistent cosinor parameter alteration, even when a significant and meaningful 24-hr rhythm was present. The ICU environmental measures showed erratic light and sound exposures. Room temperature and relative humidity data produced the highest rate of significant and meaningful diurnal 24-hr patterns. Additional research is needed to clarify relations among the CBT biomarker of the circadian clock and environmental variables of MV ICU patients. ^

Bayesian and survival model for tumor relapse status and disease-specific survival, with applications to breast cancer

Breast cancer is the most common non-skin cancer and the second leading cause of cancer-related death in women in the United States. Studies on ipsilateral breast tumor relapse (IBTR) status and disease-specific survival will help guide clinic treatment and predict patient prognosis.^ After breast conservation therapy, patients with breast cancer may experience breast tumor relapse. This relapse is classified into two distinct types: true local recurrence (TR) and new ipsilateral primary tumor (NP). However, the methods used to classify the relapse types are imperfect and are prone to misclassification. In addition, some observed survival data (e.g., time to relapse and time from relapse to death)are strongly correlated with relapse types. The first part of this dissertation presents a Bayesian approach to (1) modeling the potentially misclassified relapse status and the correlated survival information, (2) estimating the sensitivity and specificity of the diagnostic methods, and (3) quantify the covariate effects on event probabilities. A shared frailty was used to account for the within-subject correlation between survival times. The inference was conducted using a Bayesian framework via Markov Chain Monte Carlo simulation implemented in softwareWinBUGS. Simulation was used to validate the Bayesian method and assess its frequentist properties. The new model has two important innovations: (1) it utilizes the additional survival times correlated with the relapse status to improve the parameter estimation, and (2) it provides tools to address the correlation between the two diagnostic methods conditional to the true relapse types.^ Prediction of patients at highest risk for IBTR after local excision of ductal carcinoma in situ (DCIS) remains a clinical concern. The goals of the second part of this dissertation were to evaluate a published nomogram from Memorial Sloan-Kettering Cancer Center, to determine the risk of IBTR in patients with DCIS treated with local excision, and to determine whether there is a subset of patients at low risk of IBTR. Patients who had undergone local excision from 1990 through 2007 at MD Anderson Cancer Center with a final diagnosis of DCIS (n=794) were included in this part. Clinicopathologic factors and the performance of the Memorial Sloan-Kettering Cancer Center nomogram for prediction of IBTR were assessed for 734 patients with complete data. Nomogram for prediction of 5- and 10-year IBTR probabilities were found to demonstrate imperfect calibration and discrimination, with an area under the receiver operating characteristic curve of .63 and a concordance index of .63. In conclusion, predictive models for IBTR in DCIS patients treated with local excision are imperfect. Our current ability to accurately predict recurrence based on clinical parameters is limited.^ The American Joint Committee on Cancer (AJCC) staging of breast cancer is widely used to determine prognosis, yet survival within each AJCC stage shows wide variation and remains unpredictable. For the third part of this dissertation, biologic markers were hypothesized to be responsible for some of this variation, and the addition of biologic markers to current AJCC staging were examined for possibly provide improved prognostication. The initial cohort included patients treated with surgery as first intervention at MDACC from 1997 to 2006. Cox proportional hazards models were used to create prognostic scoring systems. AJCC pathologic staging parameters and biologic tumor markers were investigated to devise the scoring systems. Surveillance Epidemiology and End Results (SEER) data was used as the external cohort to validate the scoring systems. Binary indicators for pathologic stage (PS), estrogen receptor status (E), and tumor grade (G) were summed to create PS+EG scoring systems devised to predict 5-year patient outcomes. These scoring systems facilitated separation of the study population into more refined subgroups than the current AJCC staging system. The ability of the PS+EG score to stratify outcomes was confirmed in both internal and external validation cohorts. The current study proposes and validates a new staging system by incorporating tumor grade and ER status into current AJCC staging. We recommend that biologic markers be incorporating into revised versions of the AJCC staging system for patients receiving surgery as the first intervention.^ Chapter 1 focuses on developing a Bayesian method to solve misclassified relapse status and application to breast cancer data. Chapter 2 focuses on evaluation of a breast cancer nomogram for predicting risk of IBTR in patients with DCIS after local excision gives the statement of the problem in the clinical research. Chapter 3 focuses on validation of a novel staging system for disease-specific survival in patients with breast cancer treated with surgery as the first intervention. ^

An outbreak of Multi-Drug Resistant Acinetobacter in the burn intensive care unit of a large tertiary care center

Risk factors for Multi-Drug Resistant Acinetobacter (MDRA) acquisition were studied in patients in a burn intensive care unit (ICU) where there was an outbreak of MDRA. Forty cases were matched with eighty controls based on length of stay in the Burn ICU and statistical analysis was performed on data for several different variables. Matched analysis showed that mechanical ventilation, transport ventilation, number of intubations, number of bronchoscopy procedures, total body surface area burn, and prior Methicillin Resistant Staphylococcus aureus colonization were all significant risk factors for MDRA acquisition. ^ MDRA remains a significant threat to the burn population. Treatment for burn patients with MDRA is challenging as resistance to antibiotics continues to increase. This study underlined the need to closely monitor the most critically ill ventilated patients during an outbreak of MDRA as they are the most at risk for MDRA acquisition.^

Comparison of two statistical methods for rare variant association analysis

Studies have shown that rare genetic variants have stronger effects in predisposing common diseases, and several statistical methods have been developed for association studies involving rare variants. In order to better understand how these statistical methods perform, we seek to compare two recently developed rare variant statistical methods (VT and C-alpha) on 10,000 simulated re-sequencing data sets with disease status and the corresponding 10,000 simulated null data sets. The SLC1A1 gene has been suggested to be associated with diastolic blood pressure (DBP) in previous studies. In the current study, we applied VT and C-alpha methods to the empirical re-sequencing data for the SLC1A1 gene from 300 whites and 200 blacks. We found that VT method obtains higher power and performs better than C-alpha method with the simulated data we used. The type I errors were well-controlled for both methods. In addition, both VT and C-alpha methods suggested no statistical evidence for the association between the SLC1A1 gene and DBP. Overall, our findings provided an important comparison of the two statistical methods for future reference and provided preliminary and pioneer findings on the association between the SLC1A1 gene and blood pressure.^

The relationship of obesity and cardiovascular disease

Aim. To review published literature on the relationship of obesity and cardiovascular disease.^ Methods. To look at all the studies published on the topic from 2005.^ Results. In the studies done prior to 2011, body mass index and in particular waist to hip ratio (51.57) was found to be associated with coronary heart disease. But, this relationship was challenged by the latest Lancet 2011meta-analysis 1 which concluded that singly or in combination, body-mass index, waist circumference, and waist-to-hip ratio did not importantly improve prediction of first-onset cardiovascular disease when additional information exists on blood pressure, history of diabetes, and cholesterol measures were available. Furthermore, they also found long-term reproducibility of BMI to be superior to that of waist-to-hip ratio (or waist circumference). Interestingly, body mass index in later childhood and early adult life showed positive association with coronary heart disease later in life 2. In US female health professionals 3 increasing body mass index was found to be associated with increased coronary heart disease risk. Overall 4, physical activity was found to be independently associated with fewer risk factors, less coronary artery disease, and fewer adverse events in women. Finally, obesity was found to be associated with increased overall cardiovascular mortality and coronary heart disease mortality 5.^ Conclusions. There is insufficient data to draw guidelines regarding parameters of obesity affecting cardiovascular disease. But there is data to support that lower body mass index would lead to decreased cardiovascular disease mortality. And physical activity has a direct association with less coronary artery disease in women.^

Risk factors of pneumonia in traumatic spinal-cord-injured patients

Pneumonia is a well-documented and common respiratory infection in patients with acute traumatic spinal cord injuries, and may recur during the course of acute care. Using data from the North American Clinical Trials Network (NACTN) for Spinal Cord Injury, the incidence, timing, and recurrence of pneumonia were analyzed. The two main objectives were (1) to investigate the time and potential risk factors for the first occurrence of pneumonia using the Cox Proportional Hazards model, and (2) to investigate pneumonia recurrence and its risk factors using a Counting Process model that is a generalization of the Cox Proportional Hazards model. The results from survival analysis suggested that surgery, intubation, American Spinal Injury Association (ASIA) grade, direct admission to a NACTN site and age (older than 65 or not) were significant risks for first event of pneumonia and multiple events of pneumonia. The significance of this research is that it has the potential to identify patients at the time of admission who are at high risk for the incidence and recurrence of pneumonia. Knowledge and the time of occurrence of pneumonias are important factors for the development of prevention strategies and may also provide some insights into the selection of emerging therapies that compromise the immune system. ^

Logistic regression with Markov chains as covariates

The tobacco-specific nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) is an obvious carcinogen for lung cancer. Since CBMN (Cytokinesis-blocked micronucleus) has been found to be extremely sensitive to NNK-induced genetic damage, it is a potential important factor to predict the lung cancer risk. However, the association between lung cancer and NNK-induced genetic damage measured by CBMN assay has not been rigorously examined. ^ This research develops a methodology to model the chromosomal changes under NNK-induced genetic damage in a logistic regression framework in order to predict the occurrence of lung cancer. Since these chromosomal changes were usually not observed very long due to laboratory cost and time, a resampling technique was applied to generate the Markov chain of the normal and the damaged cell for each individual. A joint likelihood between the resampled Markov chains and the logistic regression model including transition probabilities of this chain as covariates was established. The Maximum likelihood estimation was applied to carry on the statistical test for comparison. The ability of this approach to increase discriminating power to predict lung cancer was compared to a baseline "non-genetic" model. ^ Our method offered an option to understand the association between the dynamic cell information and lung cancer. Our study indicated the extent of DNA damage/non-damage using the CBMN assay provides critical information that impacts public health studies of lung cancer risk. This novel statistical method could simultaneously estimate the process of DNA damage/non-damage and its relationship with lung cancer for each individual.^

Is there an association between choline/betaine dietary intake and lung cancer?

Choline and betaine are important methyl donors that contribute to protein and phospholipid synthesis and DNA methylation. They can either be obtained through diet or synthesized de novo. Evidence from human and animal research indicates that choline metabolic pathways may be activated during a variety of diseases, including cancer. Studies have been conducted to investigate the role of dietary intake of choline and betaine on cancers, but results vary among studies by cancer types, and no such study had been conducted for lung cancer. We conducted a case-control study to explore the association between choline and betaine dietary intake and lung cancer. A total of 2807 cases and 2919 controls were included in the study. After adjusting for total calorie intake, age, sex, race and smoking status, multivariable logistic regression analysis revealed a significant negative association between choline/betaine intake and lung cancer. Specifically, we observed that higher choline intake was associated with reduced lung cancer odds, and the association did not differ significantly by smoking status. A similar negative trend was observed in the association between betaine intake and lung cancer after adjusting for total calorie intake, age, sex, smoking status, race, and pack-years of smoking. However, this association was strongly affected by smoking. No significant association was observed with increased betaine intake and lung cancer among never smokers, but higher betaine intake was strongly associated with reduced lung cancer odds among smokers, and lower odds ratios were observed among current smokers than among former smokers. Our results suggest that high intake of choline may be protective for lung cancer independent of smoking status, while high betaine intake may mitigate the adverse effect of smoking on lung cancer, and help prevent lung cancer among smokers.^

A systematic review of personalized therapy in patients with advanced cancer

Background: An increased understanding of the pathogenesis of cancer at the molecular level has led to the development of personalized cancer therapy based on the mutation status of the tumor. Tailoring treatments to genetic signatures has improved treatment outcomes in patients with advanced cancer. We conducted a meta-analysis to provide a quantitative summary of the response to treatment on a phase I clinical trial matched to molecular aberration in patients with advanced solid tumors. ^ Methods: Original studies that reported the results of phase I clinical trials in patients with advanced cancer treated with matched anti-cancer therapies between January 2006 and November 2011 were identified through an extensive search of Medline, Embase, Web of Science and Cochrane Library databases. Odds Ratio (OR) with 95% confidence interval (CI) was estimated for each study to assess the strength of an association between objective response rate (ORR) and mutation status. Random effects model was used to estimate the pooled OR and their 95% CI was derived. Funnel plot was used to assess publication bias. ^ Results: Thirteen studies published between January 2006 and November 2011that reported on responses to matched phase I clinical trials in patients with advanced cancer were included in the meta-analysis. Nine studies reported on the responses seen in 538 of the 835 patients with driver mutations responsive to therapy and seven studies on the responses observed in 234 of the 306 patients with mutation predictive for negative response. Random effects model was used to estimate pooled OR, which was 7.767(95% CI = 4.199 − 14.366; p-value=0.000) in patients with activating mutations that were responsive to therapy and 0.287 (95% CI = 0.119 − 0.694; p-value=0.009) in patients with mutation predictive of negative response. ^ Conclusion: It is evident from the meta-analysis that somatic mutations present in tumor tissue of patients are predictive of responses to therapy in patients with advanced cancer in phase I setting. Plethora of research and growing evidence base indicate that selection of patients based on mutation analysis of the tumor and personalizing therapy is a step forward in the war against cancer.^

Estimates of life expectancy gains from reducing/eliminating major causes of death in the USA: An update analysis for population in 2001--2008

Evaluation of the impact of a disease on life expectancy is an important part of public health. Potential gains in life expectancy (PGLE) that can properly take into account the competing risks are an effective indicator for measuring the impact of the multiple causes of death. This study aimed to measure the PGLEs from reducing/eliminating the major causes of death in the USA from 2001 to 2008. To calculate the PGLEs due to the elimination of specific causes of death, the age-specific mortality rates for heart disease, malignant neoplasms, Alzheimer disease, kidney diseases and HIV/AIDS and life table constructing data were obtained from the National Center for Health Statistics, and the multiple decremental life tables were constructed. The PGLEs by elimination of heart disease, malignant neoplasms or HIV/AIDS continued decreasing from 2001 to 2008, but the PGLE by elimination of Alzheimer's disease or kidney diseases revealed increased trends. The PGLEs (by years) for all race, male, female, white, white male, white female, black, black male and black female at birth by complete elimination of heart disease 2001–2008 were 0.336–0.299, 0.327–0.301, 0.344–0.295, 0.360–0.315, 0.349–0.317, 0.371–0.316,0.278–0.251, 0.272–0.255, and 0.282–0.246 respectively. Similarly, the PGLEs (by years) for all race, male, female, white, white male, white female, black, black male and black female at birth by complete elimination of malignant neoplasms, Alzheimer's disease, kidney disease or HIV/AIDS 2001–2008 were also uncovered, respectively. Most diseases affect specific population, such as, HIV/AIDS tends to have a greater impact on people of working age, heart disease and malignant neoplasms have a greater impact on people over 65 years of age, but Alzheimer's disease and kidney diseases have a greater impact on people over 75 years of age. To measure the impact of these diseases on life expectancy in people of working age, partial multiple decremental life tables were constructed and the PGLEs were computed by partial or complete elimination of various causes of death during the working years. Thus, the results of the study outlined a picture of how each single disease could affect the life expectancy in age-, race-, or sex-specific population in USA. Therefore, the findings would not only assist to evaluate current public health improvements, but also provide useful information for future research and disease control programs.^

Trastuzumab use and risk of congestive heart failure in older breast cancer patients

Trastuzumab is a humanized-monoclonal antibody, developed specifically for HER2-neu over-expressed breast cancer patients. Although highly effective and well tolerated, it was reported associated with Congestive Heart Failure (CHF) in clinical trial settings (up to 27%). This leaves a gap where, Trastuzumab-related CHF rate in general population, especially older breast cancer patients with long term treatment of Trastuzumab remains unknown. This thesis examined the rates and risk factors associated with Trastuzumab-related CHF in a large population of older breast cancer patients. A retrospective cohort study using the existing Surveillance, Epidemiology and End Results (SEER) and Medicare linked de-identified database was performed. Breast cancer patients ≥ 66 years old, stage I-IV, diagnosed in 1998-2007, fully covered by Medicare but no HMO within 1-year before and after first diagnosis month, received 1st chemotherapy no earlier than 30 days prior to diagnosis were selected as study cohort. The primary outcome of this study is a diagnosis of CHF after starting chemotherapy but none CHF claims on or before cancer diagnosis date. ICD-9 and HCPCS codes were used to pool the claims for Trastuzumab use, chemotherapy, comorbidities and CHF claims. Statistical analysis including comparison of characteristics, Kaplan-Meier survival estimates of CHF rates for long term follow up, and Multivariable Cox regression model using Trastuzumab as a time-dependent variable were performed. Out of 17,684 selected cohort, 2,037 (12%) received Trastuzumab. Among them, 35% (714 out of 2037) were diagnosed with CHF, compared to 31% (4784 of 15647) of CHF rate in other chemotherapy recipients (p<.0001). After 10 years of follow-up, 65% of Trastuzumab users developed CHF, compared to 47% in their counterparts. After adjusting for patient demographic, tumor and clinical characteristics, older breast cancer patients who used Trastuzumab showed a significantly higher risk in developing CHF than other chemotherapy recipients (HR 1.69, 95% CI 1.54 - 1.85). And this risk is increased along with the increment of age (p-value < .0001). Among Trastuzumab users, these covariates also significantly increased the risk of CHF: older age, stage IV, Non-Hispanic black race, unmarried, comorbidities, Anthracyclin use, Taxane use, and lower educational level. It is concluded that, Trastuzumab users in older breast cancer patients had 69% higher risk in developing CHF than non-Trastuzumab users, much higher than the 27% increase reported in younger clinical trial patients. Older age, Non-Hispanic black race, unmarried, comorbidity, combined use with Anthracycline or Taxane also significantly increase the risk of CHF development in older patients treated with Trastuzumab. ^

Cataract surgery in cancer patients and its impact on quality of life as measured by the National Eye Institute Visual Functioning Questionnaire - 25 (NEI-VFQ-25)

Purpose. The measurement of quality of life has become an important topic in healthcare and in the allocation of limited healthcare resources. Improving the quality of life (QOL) in cancer patients is paramount. Cataract removal and lens implantation appears to improve patient well-being of cancer patients, though a formal measurement has never been published in the US literature. In this current study, National Eye Institute Visual Functioning Questionnaire (NEI-VFQ-25), a validated vision quality of life metric, was used to study the change in vision-related quality of life in cancer patients who underwent cataract extraction with intraocular lens implantation. ^ Methods. Under an IRB approved protocol, cancer patients who underwent cataract surgery with intraocular lens implantation (by a single surgeon) from December 2008 to March 2011, and who had completed a pre- and postoperative NEI-VFQ-25 were retrospectively reviewed. Post-operative data was collected at their routine 4-6 week post-op visit. Patients' demographics, cancer history, their pre and postoperative ocular examinations, visual acuities, and NEI-VFQ-25 with twelve components were included in the evaluation. The responses were evaluated using the Student t test, Spearman correlation and Wilcoxon signed rank test. ^ Results. 63 cases of cataract surgery (from 54 patients) from the MD Anderson Cancer Center were included in the study. Cancer patients had a significant improvement in the visual acuity (P<0.0001) postoperatively, along with a significant increase in vision-related quality of life (P<0.0001). Patients also had a statistically significant improvement in ten of the twelve subcategories which are addressed in the NEI-VFQ-25. ^ Conclusions. In our study, cataract extraction and intraocular implantation showed a significant impact on the vision-related quality of life in cancer patients. Although this study includes a small sample size, it serves as a positive pilot study to evaluate and quantify the impact of a surgical intervention on QOL in cancer patients and may help to design a larger study to measure vision related QOL per dollar spent for health care cost in cancer patients.^

Detecting genetic and nutritional lung cancer risk factors related to folate metabolism using Bayesian generalized linear models

Complex diseases, such as cancer, are caused by various genetic and environmental factors, and their interactions. Joint analysis of these factors and their interactions would increase the power to detect risk factors but is statistically. Bayesian generalized linear models using student-t prior distributions on coefficients, is a novel method to simultaneously analyze genetic factors, environmental factors, and interactions. I performed simulation studies using three different disease models and demonstrated that the variable selection performance of Bayesian generalized linear models is comparable to that of Bayesian stochastic search variable selection, an improved method for variable selection when compared to standard methods. I further evaluated the variable selection performance of Bayesian generalized linear models using different numbers of candidate covariates and different sample sizes, and provided a guideline for required sample size to achieve a high power of variable selection using Bayesian generalize linear models, considering different scales of number of candidate covariates. ^ Polymorphisms in folate metabolism genes and nutritional factors have been previously associated with lung cancer risk. In this study, I simultaneously analyzed 115 tag SNPs in folate metabolism genes, 14 nutritional factors, and all possible genetic-nutritional interactions from 1239 lung cancer cases and 1692 controls using Bayesian generalized linear models stratified by never, former, and current smoking status. SNPs in MTRR were significantly associated with lung cancer risk across never, former, and current smokers. In never smokers, three SNPs in TYMS and three gene-nutrient interactions, including an interaction between SHMT1 and vitamin B12, an interaction between MTRR and total fat intake, and an interaction between MTR and alcohol use, were also identified as associated with lung cancer risk. These lung cancer risk factors are worthy of further investigation.^

Effect of patient accrual patterns on power and size of log-rank test for time-to-event outcome in clinical trials

The determination of size as well as power of a test is a vital part of a Clinical Trial Design. This research focuses on the simulation of clinical trial data with time-to-event as the primary outcome. It investigates the impact of different recruitment patterns, and time dependent hazard structures on size and power of the log-rank test. A non-homogeneous Poisson process is used to simulate entry times according to the different accrual patterns. A Weibull distribution is employed to simulate survival times according to the different hazard structures. The current study utilizes simulation methods to evaluate the effect of different recruitment patterns on size and power estimates of the log-rank test. The size of the log-rank test is estimated by simulating survival times with identical hazard rates between the treatment and the control arm of the study resulting in a hazard ratio of one. Powers of the log-rank test at specific values of hazard ratio (≠1) are estimated by simulating survival times with different, but proportional hazard rates for the two arms of the study. Different shapes (constant, decreasing, or increasing) of the hazard function of the Weibull distribution are also considered to assess the effect of hazard structure on the size and power of the log-rank test. ^

Performance of HbA1c for classifying diabetes and diagnostic threshold for diabetes among the Mexican American border community

Objective. In 2009, the International Expert Committee recommended the use of HbA1c test for diagnosis of diabetes. Although it has been recommended for the diagnosis of diabetes, its precise test performance among Mexican Americans is uncertain. A strong “gold standard” would rely on repeated blood glucose measurement on different days, which is the recommended method for diagnosing diabetes in clinical practice. Our objective was to assess test performance of HbA1c in detecting diabetes and pre-diabetes against repeated fasting blood glucose measurement for the Mexican American population living in United States-Mexico border. Moreover, we wanted to find out a specific and precise threshold value of HbA1c for Diabetes Mellitus (DM) and pre-diabetes for this high-risk population which might assist in better diagnosis and better management of patient diabetes. ^ Research design and methods. We used CCHC dataset for our study. In 2004, the Cameron County Hispanic Cohort (CCHC), now numbering 2,574, was established drawn from randomly selected households on the basis of 2000 Census tract data. The CCHC study randomly selected a subset of people (aged 18-64 years) in CCHC cohort households to determine the influence of SES on diabetes and obesity. Among the participants in Cohort-2000, 67.15% are female; all are Hispanic. ^ Individuals were defined as having diabetes mellitus (Fasting plasma glucose [FPG] ≥ 126 mg/dL or pre-diabetes (100 ≤ FPG < 126 mg/dL). HbA1c test performance was evaluated using receiver operator characteristic (ROC) curves. Moreover, change-point models were used to determine HbA1c thresholds compatible with FPG thresholds for diabetes and pre-diabetes. ^ Results. When assessing Fasting Plasma Glucose (FPG) is used to detect diabetes, the sensitivity and specificity of HbA1c≥ 6.5% was 75% and 87% respectively (area under the curve 0.895). Additionally, when assessing FPG to detect pre-diabetes, the sensitivity and specificity of HbA1c≥ 6.0% (ADA recommended threshold) was 18% and 90% respectively. The sensitivity and specificity of HbA1c≥ 5.7% (International Expert Committee recommended threshold) for detecting pre-diabetes was 31% and 78% respectively. ROC analyses suggest HbA1c as a sound predictor of diabetes mellitus (area under the curve 0.895) but a poorer predictor for pre-diabetes (area under the curve 0.632). ^ Conclusions. Our data support the current recommendations for use of HbA1c in the diagnosis of diabetes for the Mexican American population as it has shown reasonable sensitivity, specificity and accuracy against repeated FPG measures. However, use of HbA1c may be premature for detecting pre-diabetes in this specific population because of the poor sensitivity with FPG. It might be the case that HbA1c is differentiating the cases more effectively who are at risk of developing diabetes. Following these pre-diabetic individuals for a longer-term for the detection of incident diabetes may lead to more confirmatory result.^