Faculty Bibliography

PURPOSE/OBJECTIVE:Previously, we introduced a state-based 2-dimensional continuous-time hidden Markov model (2D CT HMM) to model the pattern of detected glaucoma changes using structural and functional information simultaneously. The purpose of this study was to evaluate the detected glaucoma change prediction performance of the model in a real clinical setting using a retrospective longitudinal dataset. DESIGN/METHODS:Longitudinal, retrospective study. PARTICIPANTS/METHODS:One hundred thirty-four eyes from 134 participants diagnosed with glaucoma or as glaucoma suspects (average follow-up, 4.4±1.2 years; average number of visits, 7.1±1.8). METHODS:A 2D CT HMM model was trained using OCT (Cirrus HD-OCT; Zeiss, Dublin, CA) average circumpapillary retinal nerve fiber layer (cRNFL) thickness and visual field index (VFI) or mean deviation (MD; Humphrey Field Analyzer; Zeiss). The model was trained using a subset of the data (107 of 134 eyes [80%]) including all visits except for the last visit, which was used to test the prediction performance (training set). Additionally, the remaining 27 eyes were used for secondary performance testing as an independent group (validation set). The 2D CT HMM predicts 1 of 4 possible detected state changes based on 1 input state. MAIN OUTCOME MEASURES/METHODS:Prediction accuracy was assessed as the percentage of correct prediction against the patient's actual recorded state. In addition, deviations of the predicted long-term detected change paths from the actual detected change paths were measured. RESULTS:Baseline mean ± standard deviation age was 61.9±11.4 years, VFI was 90.7±17.4, MD was -3.50±6.04 dB, and cRNFL thickness was 74.9±12.2 μm. The accuracy of detected glaucoma change prediction using the training set was comparable with the validation set (57.0% and 68.0%, respectively). Prediction deviation from the actual detected change path showed stability throughout patient follow-up. CONCLUSIONS:The 2D CT HMM demonstrated promising prediction performance in detecting glaucoma change performance in a simulated clinical setting using an independent cohort. The 2D CT HMM allows information from just 1 visit to predict at least 5 subsequent visits with similar performance.

Gastroesophageal reflux disease (GERD) and Barrett's Esophagus (BE), which are prevalent in the World Trade Center (WTC) exposed and general populations, negatively impact quality of life and cost of healthcare. GERD, a risk factor of BE, is linked to obstructive airways disease (OAD). We aim to identify serum biomarkers of GERD/BE, and assess the respiratory and clinical phenotype of a longitudinal cohort of never-smoking, male, WTC-exposed rescue workers presenting with pulmonary symptoms. Biomarkers collected soon after WTC-exposure were evaluated in optimized predictive models of GERD/BE. In the WTC-exposed cohort, the prevalence of BE is at least 6 times higher than in the general population. GERD/BE cases had similar lung function, D_LCO, bronchodilator response and long-acting beta-agonist use compared to controls. In confounder-adjusted regression models, TNF-alpha ≥ 6 pg/mL predicted both GERD and BE. GERD was also predicted by C-peptide ≥ 360 pg/mL, while BE was predicted by fractalkine ≥ 250 pg/mL and IP-10 ≥ 290 pg/mL. Finally, participants with GERD had significantly increased use of short-acting beta-agonist compared to controls. Overall, biomarkers sampled prior to GERD/BE presentation showed strong predictive abilities of disease development. This study frames future investigations to further our understanding of aerodigestive pathology due to particulate matter exposure.

A strong positive association has been observed between circulating anti-Mullerian hormone (AMH), a biomarker of ovarian reserve, and breast cancer risk in three prospective studies. Confirming this association is important because of the paucity of biomarkers of breast cancer risk in premenopausal women. We conducted a consortium study including ten prospective cohorts that had collected blood from premenopausal women. A nested case-control design was implemented within each cohort. A total of 2,835 invasive (80%) and in situ (20%) breast cancer cases were individually matched to controls (n = 3,122) on age at blood donation. AMH was measured using a high sensitivity enzyme-linked immunoabsorbent assay. Conditional logistic regression was applied to the aggregated dataset. There was a statistically significant trend of increasing breast cancer risk with increasing AMH concentration (ptrend across quartiles < 0.0001) after adjusting for breast cancer risk factors. The odds ratio (OR) for breast cancer in the top versus bottom quartile of AMH was 1.60 (95% CI = 1.31-1.94). Though the test for interaction was not statistically significant (pinteraction = 0.15), the trend was statistically significant only for tumors positive for both estrogen receptor (ER) and progesterone receptor (PR): ER+/PR+: ORQ4-Q1 = 1.96, 95% CI = 1.46-2.64, ptrend <0.0001; ER+/PR-: ORQ4-Q1 = 0.82, 95% CI = 0.40-1.68, ptrend = 0.51; ER-/PR+: ORQ4-Q1 = 3.23, 95% CI =0.48-21.9, ptrend = 0.26; ER-/PR-: ORQ4-Q1 = 1.15, 95% CI = 0.63-2.09, ptrend = 0.60. The association was observed for both pre- (ORQ4-Q1 = 1.35, 95% CI= 1.05-1.73) and post-menopausal (ORQ4-Q1 =1.61, 95% CI = 1.03 - 2.53) breast cancer (pinteraction = 0.34). In this large consortium study, we confirmed that AMH is associated with breast cancer risk, with a 60% increase in risk for women in the top vs. bottom quartile of AMH.

World Trade Center-particulate matter(WTC-PM) exposure and metabolic-risk are associated with WTC-Lung Injury(WTC-LI). The receptor for advanced glycation end-products (RAGE) is most highly expressed in the lung, mediates metabolic risk, and single-nucleotide polymorphisms at the AGER-locus predict forced expiratory volume(FEV). Our objectives were to test the hypotheses that RAGE is a biomarker of WTC-LI in the FDNY-cohort and that loss of RAGE in a murine model would protect against acute PM-induced lung disease. We know from previous work that early intense exposure at the time of the WTC collapse was most predictive of WTC-LI therefore we utilized a murine model of intense acute PM-exposure to determine if loss of RAGE is protective and to identify signaling/cytokine intermediates. This study builds on a continuing effort to identify serum biomarkers that predict the development of WTC-LI. A case-cohort design was used to analyze a focused cohort of male never-smokers with normal pre-9/11 lung function. Odds of developing WTC-LI increased by 1.2, 1.8 and 1.0 in firefighters with soluble RAGE (sRAGE)>/=97pg/mL, CRP>/=2.4mg/L, and MMP-9