Identfying predictors of St. Louis encephalitis activity in Houston Texas

Generalized linear Poisson and logistic regression models were utilized to examine the relationship between temperature and precipitation and cases of Saint Louis encephalitis virus spread in the Houston metropolitan area. The models were investigated with and without repeated measures, with a first order autoregressive (AR1) correlation structure used for the repeated measures model. The two types of Poisson regression models, with and without correlation structure, showed that a unit increase in temperature measured in degrees Fahrenheit increases the occurrence of the virus 1.7 times and a unit increase in precipitation measured in inches increases the occurrence of the virus 1.5 times. Logistic regression did not show these covariates to be significant as predictors for encephalitis activity in Houston for either correlation structure. This discrepancy for the logistic model could be attributed to the small data set.^ Keywords: Saint Louis Encephalitis; Generalized Linear Model; Poisson; Logistic; First Order Autoregressive; Temperature; Precipitation. ^

Lifetime changes in body mass index and risk of breast cancer in minority women

Introduction: Obesity is an epidemic in the United States, especially among Hispanics and African-Americans. Studies of obesity and breast cancer risk and subtype have been conducted primarily in non-Hispanic whites. Obesity is inversely associated with premenopausal breast cancer, but both obesity and weight gain increase the risk of postmenopausal disease. Obesity has been associated with breast cancer subtype in many studies. Methods: To assess the association between changes in body mass index (BMI) over the lifetime, weight gain, and breast cancer in Mexican-American women, we conducted a case-control study using 149 cases and 330 age-matched controls. In a second study, we identified 212 African-American and 167 Mexican-American women with breast cancer in the ongoing ELLA Bi-National Breast Cancer Study, abstracted medical charts to classify tumors as ER+/PR+, HER2+, or ER-/PR-/HER2-, and assessed the association between lifetime changes in body mass index, weight gain, and breast cancer subtype. In both studies, growth mixture modeling was use to identify trajectories of change in BMI over the lifetime, and these trajectories were used as exposures in a logistic regression model to calculate odds ratios (OR). Results: There was no association between trajectories of change in BMI and breast cancer risk in Mexican-American women. In addition, BMI at ages 15 and 30 and at diagnosis was not associated with breast cancer. However, adult weight gain was inversely associated with breast cancer risk (per 5kg, OR=0.92, 95% CI: 0.85-0.99). The case-only analysis found no association between obesity at ages 15 and 30 and at diagnosis and breast cancer subtype. Further, there was no association between adult weight gain (defined as weight change from age 15 to time of diagnosis) and breast cancer subtype. Conclusions: Obesity was not associated with breast cancer risk in Mexican-American women, while adult weight gain reduced the risk independently of menopausal status. These results are contradictory of those in non-Hispanic white women and suggest that the etiology of breast cancer may differ by race/ethnicity. Further, obesity was not associated with breast cancer subtype in African-American and Mexican-American women, contrary to results in non-Hispanic white women. ^

Determinants of participation in worksite health risk appraisal (HRA) programs

The purpose of this study was to apply the Behavioral Model of Health Services Utilization to examine an existing worksite HRA program to identify and examine the roles of determinants of participation in HRA programs. The program consisted of three activities: questionnaire, physical examination, and group interpretation sessions. All of the 1821 employees were eligible for the program; 523 (29%) participated in at least one activity. Results from bivariate analyses suggest that being female, being white, having fewer dependents, and having higher medical claims for the past year were positively associated with participation. Results of logistic regression suggest that Age, Sex, Race, Marital, Number of Dependents, Job Title, Months with the Company, and a log transformed value of Employee's Total Medical Claims were all significant determinants of participation. Applications of the logistic regression models, other factors that should be investigated in future studies, and the limitations of the study were discussed. ^

Leukemia and occupational exposure to electromagnetic fields: An incident case-control study

The existence of an association between leukemia and electromagnetic fields (EMF) is still controversial. The results of epidemiologic studies of leukemia in occupational groups with exposure to EMF are inconsistent. Weak associations have been seen in a few studies. EMF assessment is lacking in precision. Reported dose-response relationships have been based on qualitative levels of exposure to EMF without regard to duration of employment or EMF intensity on the jobs. Furthermore, potential confounding factors in the associations were not often well controlled. The current study is an analysis of the data collected from an incident case-control study. The primary objective was to test the hypothesis that occupational exposure to EMF is associated with leukemia, including total leukemia (TL), myelogenous leukemia (MYELOG) and acute non-lymphoid leukemia (ANLL). Potential confounding factors: occupational exposure to benzene, age, smoking, alcohol consumption, and previous medical radiation exposures were controlled in multivariate logistic regression models. Dose-response relationships were estimated by cumulative occupational exposure to EMF, taking into account duration of employment and EMF intensity on the jobs. In order to overcome weaknesses of most previous studies, special efforts were made to improve the precision of EMF assessment. Two definitions of EMF were used and result discrepancies using the two definitions were observed. These difference raised a question as to whether the workers at jobs with low EMF exposure should be considered as non-exposed in future studies. In addition, the current study suggested use of lifetime cumulative EMF exposure estimates to determine dose-response relationship. The analyses of the current study suggest an association between ANLL and employment at selected jobs with high EMF exposure. The existence of an association between three types of leukemia and broader categories of occupational EMF exposure, is still undetermined. If an association does exist between occupational EMF exposure and leukemia, the results of the current study suggest that EMF might only be a potential factor in the promotion of leukemia, but not its initiation. ^

Investigating the effects of the 2007 Texas tobacco tax increase on the smoking behavior of adults

Smoking is major cause of premature mortality and morbidity in the United States. The health consequences of tobacco usage are increasingly concentrated in minority and lower socioeconomic groups. One of the most effective means of deterring tobacco consumption and generating revenue to fund prevention activities is the levying of excise taxes. In 2007 the state of Texas increased the excise tax on cigarettes by $1.00 per pack. This study sought to determine if there was a significant effect on smoking prevalence in the state by examining Behavioral Risk Factor Surveillance System (BRFSS) data for two years leading up to the tax increase-2005 and 2006- and two years post tax increase -2007 and 2008. Results were compared against a chi square distribution and three multiple logistic regression models were created to adjust for race/ethnicity, age, education and income. Results from this study show that there was not a significant decrease in smoking prevalence for most of the groups stratified by age, income and ethnicity. There was not a significant decrease in the younger adults aged 18-34 by income, ethnicity, or education. Smoking prevalence increased for some groups, e.g., Hispanic females. In the regression models, the tax effect was not significant. While overall prevalence decreased by 9%, there were not significant reductions among non-White or Hispanic survey participants. Taxed sales dropped by approximately 17% according to the Texas Comptroller. Without BRFSS data measuring daily cigarette consumption among current smokers, now not assessed, it is impossible to determine whether the discrepancy in reported prevalence and taxes sales is attributable to consumption of fewer cigarettes among smokers or tax avoidance.^

Influence of family meals on obesity and dietary behaviors among adolescents in India

The study objectives were to (i) Describe the frequency and priority of family meals, (ii) Compare the family mealtime environment by gender and SES, (iii) Examine the association between family meals and weight status among adolescents living in New Delhi, India, (iv) Examine the association between family meals and eating patterns (healthy/unhealthy) among adolescent boys and girls living in New Delhi, India. Survey and anthropometric data were collected from 8th and 10th grade students (n=1818) from four Government (public) schools and four private schools who participated in the HRIDAY study. Chi-square tests were used to evaluate if the distributions of outcomes and exposure varied by gender and SES groups. Logistic regression models were used to obtain the association of weight status (underweight / normal weight Vs overweight / obese) with frequency of family meals as the main exposure. Overall the prevalence of obesity was more among the mid- high SES group and in boys. Over half of the participants had 7 or more family meals in the past week. There was no statistically significant association seen between family meals and weight status. Majority of the participants believed that eating healthy food and maintaining a healthy weight was important and eating at least one family meal was important. Majority of the participants who ate more than 3 or more family meals eat healthy food and also ate fast food. Intervention strategies should focus on the high risk group. Private schools are appropriate settings for interventions. Eating with families should be encouraged and future research should examine family meal patterns.^

Prediction of sepsis in the burn intensive care unit patient

Sepsis is a significant cause for multiple organ failure and death in the burn patient, yet identification in this population is confounded by chronic hypermetabolism and impaired immune function. The purpose of this study was twofold: 1) determine the ability of the systemic inflammatory response syndrome (SIRS) and American Burn Association (ABA) criteria to predict sepsis in the burn patient; and 2) develop a model representing the best combination of clinical predictors associated with sepsis in the same population. A retrospective, case-controlled, within-patient comparison of burn patients admitted to a single intensive care unit (ICU) was conducted for the period January 2005 to September 2010. Blood culture results were paired with clinical condition: "positive-sick"; "negative-sick", and "screening-not sick". Data were collected for the 72 hours prior to each blood culture. The most significant predictors were evaluated using logistic regression, Generalized Estimating Equations (GEE) and ROC area under the curve (AUC) analyses to assess model predictive ability. Bootstrapping methods were employed to evaluate potential model over-fitting. Fifty-nine subjects were included, representing 177 culture periods. SIRS criteria were not found to be associated with culture type, with an average of 98% of subjects meeting criteria in the 3 days prior. ABA sepsis criteria were significantly different among culture type only on the day prior (p = 0.004). The variables identified for the model included: heart rate>130 beats/min, mean blood pressure<60 mmHg, base deficit<-6 mEq/L, temperature>36°C, use of vasoactive medications, and glucose>150 mg/d1. The model was significant in predicting "positive culture-sick" and sepsis state, with AUC of 0.775 (p < 0.001) and 0.714 (p < .001), respectively; comparatively, the ABA criteria AUC was 0.619 (p = 0.028) and 0.597 (p = .035), respectively. SIRS criteria are not appropriate for identifying sepsis in the burn population. The ABA criteria perform better, but only for the day prior to positive blood culture results. The time period useful to diagnose sepsis using clinical criteria may be limited to 24 hours. A combination of predictors is superior to individual variable trends, yet algorithms or computer support will be necessary for the clinician to find such models useful. ^

Effect of primary care availability and health insurance coverage on risk and cost of Preventable Hospitalizations in Harris County

Preventable Hospitalizations (PHs) are hospitalizations that can be avoided with appropriate and timely care in the ambulatory setting and hence are closely associated with primary care access in a community. Increased primary care availability and health insurance coverage may increase primary care access, and consequently may be significantly associated with risks and costs of PHs. Objective. To estimate the risk and cost of preventable hospitalizations (PHs); to determine the association of primary care availability and health insurance coverage with the risk and costs of PHs, first alone and then simultaneously; and finally, to estimate the impact of expansions in primary care availability and health insurance coverage on the burden of PHs among non-elderly adult residents of Harris County. Methods. The study population was residents of Harris County, age 18 to 64, who had at least one hospital discharge in a Texas hospital in 2008. The primary independent variables were availability of primary care physicians, availability of primary care safety net clinics and health insurance coverage. The primary dependent variables were PHs and associated hospitalization costs. The Texas Health Care Information Collection (THCIC) Inpatient Discharge data was used to obtain information on the number and costs of PHs in the study population. Risk of PHs in the study population, as well as average and total costs of PHs were calculated. Multivariable logistic regression models and two-step Heckman regression models with log-transformed costs were used to determine the association of primary care availability and health insurance coverage with the risk and costs of PHs respectively, while controlling for individual predisposing, enabling and need characteristics. Predicted PH risk and cost were used to calculate the predicted burden of PHs in the study population and the impact of expansions in primary care availability and health insurance coverage on the predicted burden. Results. In 2008, hospitalized non-elderly adults in Harris County had 11,313 PHs and a corresponding PH risk of 8.02%. Congestive heart failure was the most common PH. PHs imposed a total economic burden of $84 billion at an average of $7,449 per PH. Higher primary care safety net availability was significantly associated with the lower risk of PHs in the final risk model, but only in the uninsured. A unit increase in safety net availability led to a 23% decline in PH odds in the uninsured, compared to only a 4% decline in the insured. Higher primary care physician availability was associated with increased PH costs in the final cost model (β=0.0020; p<0.05). Lack of health insurance coverage increased the risk of PH, with the uninsured having 30% higher odds of PHs (OR=1.299; p<0.05), but reduced the cost of a PH by 7% (β=-0.0668; p<0.05). Expansions in primary care availability and health insurance coverage were associated with a reduction of about $1.6 million in PH burden at the highest level of expansion. Conclusions. Availability of primary care resources and health insurance coverage in hospitalized non-elderly adults in Harris County are significantly associated with the risk and costs of PHs. Expansions in these primary care access factors can be expected to produce significant reductions in the burden of PHs in Harris County.^

A cross-sectional analysis of the association between polycyclic aromatic hydrocarbons and diesel particulate matter exposures and hypertension among individuals of Mexican origin residing in Houston, TX

Background. Research has shown that elevations of only 10 mmHg diastolic blood pressure (BP) and 5 mmHg systolic BP are associated with substantial (as large as 50%) increases in risks for cardiovascular disease, a leading cause of death, worldwide. Epidemiological studies have found that particulate matter (PM) increases blood pressure (BP) and many biological mechanisms which may suggest that the organic matter of PM contributes to the increase in BP. To understand components of PM which may contribute to the increase in BP, this study focuses on diesel particulate matter (DPM) and polycyclic aromatic hydrocarbons (PAHs). To our knowledge, there have been only four epidemiological studies on BP and DPM, and no epidemiological studies on BP and PAHs. ^ Objective. Our objective was to evaluate the association between prevalent hypertension and two ambient exposures: DPM and PAHs amongst the Mano a Mano cohort. ^ Methods. The Mano a Mano cohort which was established by the M.D. Anderson Cancer Center in 2001, is comprised of individuals of Mexican origin residing in Houston, TX. Using geographical information systems, we linked modeled annual estimates of PAHs and DPM at the census track level from the U.S. Environmental Protection Agency's National-Scale Air Toxics Assessment to residential addresses of cohort members. Mixed-effects logistic regression models were applied to determine associations between DPM and PAHs and hypertension while adjusting for confounders. ^ Results. Ambient levels of DPM, categorized into quartiles, were not statistically associated with hypertension and did not indicate a dose response relationship. Ambient levels of PAHs, categorized into quartiles, were not associated with hypertension, but did indicate a dose response relationship in multiple models (for example: Q2: OR = 0.98; 95% CI, 0.73–1.31, Q3: OR = 1.08; 95% CI, 0.82–1.41, Q4: OR = 1.26; 95% CI, 0.94–1.70). ^ Conclusion. This is the first assessment to analyze the relationship between ambient levels of PAHs and hypertension and it is amongst a few studies investigating the association between ambient levels of DPM and hypertension. Future analyses are warranted to explore the effects DPM and PAHs using different categorizations in order to clarify their relationships with hypertension.^

The relationship between hospital financial performance and information technology integration strategy selection

In light of the new healthcare regulations, hospitals are increasingly reevaluating their IT integration strategies to meet expanded healthcare information exchange requirements. Nevertheless, hospital executives do not have all the information they need to differentiate between the available strategies and recognize what may better fit their organizational needs. ^ In the interest of providing the desired information, this study explored the relationships between hospital financial performance, integration strategy selection, and strategy change. The integration strategies examined – applied as binary logistic regression dependent variables and in the order from most to least integrated – were Single-Vendor (SV), Best-of-Suite (BoS), and Best-of-Breed (BoB). In addition, the financial measurements adopted as independent variables for the models were two administrative labor efficiency and six industry standard financial ratios designed to provide a broad proxy of hospital financial performance. Furthermore, descriptive statistical analyses were carried out to evaluate recent trends in hospital integration strategy change. Overall six research questions were proposed for this study. ^ The first research question sought to answer if financial performance was related to the selection of integration strategies. The next questions, however, explored whether hospitals were more likely to change strategies or remain the same when there was no external stimulus to change, and if they did change, they would prefer strategies closer to the existing ones. These were followed by a question that inquired if financial performance was also related to strategy change. Nevertheless, rounding up the questions, the last two probed if the new Health Information Technology for Economic and Clinical Health (HITECH) Act had any impact on the frequency and direction of strategy change. ^ The results confirmed that financial performance is related to both IT integration strategy selection and strategy change, while concurred with prior studies that suggested hospital and environmental characteristics are associated factors as well. Specifically this study noted that the most integrated SV strategy is related to increased administrative labor efficiency and the hybrid BoS strategy is associated with improved financial health (based on operating margin and equity financing ratios). On the other hand, no financial indicators were found to be related to the least integrated BoB strategy, except for short-term liquidity (current ratio) when involving strategy change. ^ Ultimately, this study concluded that when making IT integration strategy decisions hospitals closely follow the resource dependence view of minimizing uncertainty. As each integration strategy may favor certain organizational characteristics, hospitals traditionally preferred not to make strategy changes and when they did, they selected strategies that were more closely related to the existing ones. However, as new regulations further heighten revenue uncertainty while require increased information integration, moving forward, as evidence already suggests a growing trend of organizations shifting towards more integrated strategies, hospitals may be more limited in their strategy selection choices.^

Association between length of stay in the U.S. and diabetes risk factors among Chinese Americans in Houston, Texas in 2004-2005

Studies have suggested that acculturation is related to diabetes prevalence and risk factors among immigrant groups in the United States (U.S.), however scant data are available to investigate this relationship among Asian Americans and Asian American subgroups. The objective of this cross-sectional study was to examine the association between length of stay in the U.S. and type 2 diabetes prevalence and its risk factors among Chinese Americans in Houston, Texas. Data were obtained from the 2004-2005 Asian-American Health Needs Assessment in Houston, Texas (N=409 Chinese Americans) for secondary analysis in this study. Diabetes prevalence and risk factors (overweight/obesity and access to medical care) were based on self-report. Descriptive statistics summarized demographic characteristics, diabetes prevalence, and reasons for not seeing a doctor. Logistic regression, using an incremental modeling approach, was used to measure the association between length of stay and diabetes prevalence and related risk factors, while adjusting for the potential confounding factors of age, gender, education level, and income level. Although the prevalence of type 2 diabetes was highest among those living in the U.S. for more than 20 years, there was no significant association between length of stay in the U.S. and diabetes prevalence among these Chinese Americans after adjustment for confounding factors. No association was found between length of stay in the U.S. and overweight/obese status among this population either, after adjusting for confounding factors, too. On the other hand, a longer length of stay was significantly associated with increased health insurance coverage in both unadjusted and adjusted models. The findings of this study suggest that length of stay in the U.S. alone may not be an indicator for diabetes risk among Chinese Americans. Future research should consider alternative models to measure acculturation (e.g., models that reflect acculturation as a multi-dimensional, not uni-dimensional process), which may more accurately depict its effect on diabetes prevalence and related risk factors.^

Mixture modeling for joint analysis of survival, discrete, and continuous data

Mixture modeling is commonly used to model categorical latent variables that represent subpopulations in which population membership is unknown but can be inferred from the data. In relatively recent years, the potential of finite mixture models has been applied in time-to-event data. However, the commonly used survival mixture model assumes that the effects of the covariates involved in failure times differ across latent classes, but the covariate distribution is homogeneous. The aim of this dissertation is to develop a method to examine time-to-event data in the presence of unobserved heterogeneity under a framework of mixture modeling. A joint model is developed to incorporate the latent survival trajectory along with the observed information for the joint analysis of a time-to-event variable, its discrete and continuous covariates, and a latent class variable. It is assumed that the effects of covariates on survival times and the distribution of covariates vary across different latent classes. The unobservable survival trajectories are identified through estimating the probability that a subject belongs to a particular class based on observed information. We applied this method to a Hodgkin lymphoma study with long-term follow-up and observed four distinct latent classes in terms of long-term survival and distributions of prognostic factors. Our results from simulation studies and from the Hodgkin lymphoma study demonstrated the superiority of our joint model compared with the conventional survival model. This flexible inference method provides more accurate estimation and accommodates unobservable heterogeneity among individuals while taking involved interactions between covariates into consideration.^

Epidemiology of Acute Lung Injury and Acute Respiratory Distress Syndrome in children in Vietnam

Acute Lung Injury (ALI) and Acute Respiratory Distress Syndrome (ARDS) are life- threatening disorders that can result from many severe conditions and diseases. Since the American European Consensus Conference established the internationally accepted definition of ALI and ARDS, the epidemiology of pediatric ALI/ARDS has been described in some developed countries. In the developing world, however, there are very few data available regarding the burden, etiologies, management, outcome, and factors associated with outcomes of ALI/ARDS in children. ^ Therefore, we conducted this observational, clinical study to estimate the prevalence and case mortality rate of ALI/ARDS among a cohort of patients admitted to the pediatric intensive care unit (PICU) of the National Hospital of Pediatrics in Hanoi, the largest children's hospital in Vietnam. Etiologies and predisposing factors, and management strategies for pediatric ALI/ARDS were described. In addition, we determined the prevalence of HIV infection among children with ALI/ARDS in Vietnam. We also identified the causes of mortality and predictors of mortality and prolonged mechanical ventilation of children with ALI/ARDS. ^ A total of 1,051 patients consecutively admitted to the pediatric intensive care unit from January 2011 to January 2012 were screened daily for development of ALI/ARDS using the American-European Consensus Conference Guidelines. All identified patients with ALI/ARDS were followed until hospital discharge or death in the hospital. Patients' demographic and clinical data were collected. Multivariable logistic regression models were developed to identify independent predictors of mortality and other adverse outcome of ALI/ARDS. ^ Prevalence of ALI and ARDS was 9.6% (95% confidence interval, 7.8% to 11.4%) and 8.8% (95% confidence interval, 7.0% to 10.5%) of total PICU admissions, respectively. Infectious pneumonia and sepsis were the most common causes of ALI/ARDS accounting for 60.4% and 26.7% of cases, respectively. Prevalence of HIV infection among children with ALI/ARDS was 3.0%. The case fatality rate of ALI/ARDS was 63.4% (95% confidence interval, 53.8% to 72.9%). Multiple organ failure and refractory hypoxemia were the main causes of death. Independent predictors of mortality and prolonged mechanical ventilation were male gender, duration of intensive care stay prior to ALI/ARDS diagnosis, level of oxygenation defect measured by PaO2/FiO2 ratio at ALI/ARDS diagnosis, presence of non-pulmonary organ dysfunction at day one and day three after ALI/ARDS diagnosis, and presence of hospital acquired infection. ^ The results of this study demonstrated that ALI/ARDS was a common and severe condition in children in Vietnam. The level of both pulmonary and non-pulmonary organ damage influenced survival of patients with ALI/ARDS. Strategies for preventing ALI/ARDS and for clinical management of the disease are necessary to reduce the associated risks.^

Relationship of hospital volume to patient mortality, length of stay and total costs in patients receiving brain surgery for cancer: A nationwide analysis

Better morbidity and mortality outcomes associated with increased hospital procedural volume have been demonstrated across a number of different medical procedures. Existence of such a volume-outcome relationship is posited to lead to increased specialization of care, such that patients requiring specific procedures are funneled to physicians and hospitals that achieve a minimum volume of such procedures each year. In this study, the 2009 Nationwide Inpatient Sample is used to examine the relationship between hospital volume and patient outcome among patients undergoing procedures related to malignant brain cancer. Multiple regression models were used to examine the impact of hospital volume on length of inpatient stay and cost of inpatient stay; logistic regression was used to examine the impact of hospital volume on morbidity. Hospital volume was found to be a significant predictor of both length of stay and cost of stay. Hospital volume was associated with a lower length of stay, but was also associated with increased costs. Hospital volume was not found to be a statistically significant predictor of morbidity, though less than three percent of this sample died while in the hospital. Volume is indeed a significant predictor of outcome for procedures related to brain malignancies, though further research regarding the cost of such procedures is recommended.^

Data quality in trauma transfusion studies and the impact of missing data on predicting massive transfusion

Maximizing data quality may be especially difficult in trauma-related clinical research. Strategies are needed to improve data quality and assess the impact of data quality on clinical predictive models. This study had two objectives. The first was to compare missing data between two multi-center trauma transfusion studies: a retrospective study (RS) using medical chart data with minimal data quality review and the PRospective Observational Multi-center Major Trauma Transfusion (PROMMTT) study with standardized quality assurance. The second objective was to assess the impact of missing data on clinical prediction algorithms by evaluating blood transfusion prediction models using PROMMTT data. RS (2005-06) and PROMMTT (2009-10) investigated trauma patients receiving ≥ 1 unit of red blood cells (RBC) from ten Level I trauma centers. Missing data were compared for 33 variables collected in both studies using mixed effects logistic regression (including random intercepts for study site). Massive transfusion (MT) patients received ≥ 10 RBC units within 24h of admission. Correct classification percentages for three MT prediction models were evaluated using complete case analysis and multiple imputation based on the multivariate normal distribution. A sensitivity analysis for missing data was conducted to estimate the upper and lower bounds of correct classification using assumptions about missing data under best and worst case scenarios. Most variables (17/33=52%) had <1% missing data in RS and PROMMTT. Of the remaining variables, 50% demonstrated less missingness in PROMMTT, 25% had less missingness in RS, and 25% were similar between studies. Missing percentages for MT prediction variables in PROMMTT ranged from 2.2% (heart rate) to 45% (respiratory rate). For variables missing >1%, study site was associated with missingness (all p≤0.021). Survival time predicted missingness for 50% of RS and 60% of PROMMTT variables. MT models complete case proportions ranged from 41% to 88%. Complete case analysis and multiple imputation demonstrated similar correct classification results. Sensitivity analysis upper-lower bound ranges for the three MT models were 59-63%, 36-46%, and 46-58%. Prospective collection of ten-fold more variables with data quality assurance reduced overall missing data. Study site and patient survival were associated with missingness, suggesting that data were not missing completely at random, and complete case analysis may lead to biased results. Evaluating clinical prediction model accuracy may be misleading in the presence of missing data, especially with many predictor variables. The proposed sensitivity analysis estimating correct classification under upper (best case scenario)/lower (worst case scenario) bounds may be more informative than multiple imputation, which provided results similar to complete case analysis.^