Prediction of multiple infections after severe burn trauma: a prospective cohort study.

OBJECTIVE: To develop predictive models for early triage of burn patients based on hypersusceptibility to repeated infections. BACKGROUND: Infection remains a major cause of mortality and morbidity after severe trauma, demanding new strategies to combat infections. Models for infection prediction are lacking. METHODS: Secondary analysis of 459 burn patients (≥16 years old) with 20% or more total body surface area burns recruited from 6 US burn centers. We compared blood transcriptomes with a 180-hour cutoff on the injury-to-transcriptome interval of 47 patients (≤1 infection episode) to those of 66 hypersusceptible patients [multiple (≥2) infection episodes (MIE)]. We used LASSO regression to select biomarkers and multivariate logistic regression to built models, accuracy of which were assessed by area under receiver operating characteristic curve (AUROC) and cross-validation. RESULTS: Three predictive models were developed using covariates of (1) clinical characteristics; (2) expression profiles of 14 genomic probes; (3) combining (1) and (2). The genomic and clinical models were highly predictive of MIE status [AUROCGenomic = 0.946 (95% CI: 0.906-0.986); AUROCClinical = 0.864 (CI: 0.794-0.933); AUROCGenomic/AUROCClinical P = 0.044]. Combined model has an increased AUROCCombined of 0.967 (CI: 0.940-0.993) compared with the individual models (AUROCCombined/AUROCClinical P = 0.0069). Hypersusceptible patients show early alterations in immune-related signaling pathways, epigenetic modulation, and chromatin remodeling. CONCLUSIONS: Early triage of burn patients more susceptible to infections can be made using clinical characteristics and/or genomic signatures. Genomic signature suggests new insights into the pathophysiology of hypersusceptibility to infection may lead to novel potential therapeutic or prophylactic targets.

Prognostication of Mortality in Critically Ill Patients With Severe Infections.

BACKGROUND: The purpose of this study was to confirm the prognostic value of pancreatic stone protein (PSP) in patients with severe infections requiring ICU management and to develop and validate a model to enhance mortality prediction by combining severity scores with biomarkers. METHODS: We enrolled prospectively patients with severe sepsis or septic shock in mixed tertiary ICUs in Switzerland (derivation cohort) and Brazil (validation cohort). Severity scores (APACHE [Acute Physiology and Chronic Health Evaluation] II or Simplified Acute Physiology Score [SAPS] II) were combined with biomarkers obtained at the time of diagnosis of sepsis, including C-reactive-protein, procalcitonin (PCT), and PSP. Logistic regression models with the lowest prediction errors were selected to predict in-hospital mortality. RESULTS: Mortality rates of patients with septic shock enrolled in the derivation cohort (103 out of 158) and the validation cohort (53 out of 91) were 37% and 57%, respectively. APACHE II and PSP were significantly higher in dying patients. In the derivation cohort, the models combining either APACHE II, PCT, and PSP (area under the receiver operating characteristic curve [AUC], 0.721; 95% CI, 0.632-0.812) or SAPS II, PCT, and PSP (AUC, 0.710; 95% CI, 0.617-0.802) performed better than each individual biomarker (AUC PCT, 0.534; 95% CI, 0.433-0.636; AUC PSP, 0.665; 95% CI, 0.572-0.758) or severity score (AUC APACHE II, 0.638; 95% CI, 0.543-0.733; AUC SAPS II, 0.598; 95% CI, 0.499-0.698). These models were externally confirmed in the independent validation cohort. CONCLUSIONS: We confirmed the prognostic value of PSP in patients with severe sepsis and septic shock requiring ICU management. A model combining severity scores with PCT and PSP improves mortality prediction in these patients.

Identification of Low-Risk Patients with Acute Symptomatic Pulmonary Embolism for Outpatient Therapy.

RATIONALE: Patients with acute symptomatic pulmonary embolism (PE) deemed to be at low risk for early complications might be candidates for partial or complete outpatient treatment. OBJECTIVES: To develop and validate a clinical prediction rule that accurately identifies patients with PE and low risk of short-term complications and to compare its prognostic ability with two previously validated models (i.e., the Pulmonary Embolism Severity Index [PESI] and the Simplified PESI [sPESI]) METHODS: Multivariable logistic regression of a large international cohort of patients with PE prospectively enrolled in the RIETE (Registro Informatizado de la Enfermedad TromboEmbólica) registry. MEASUREMENTS AND MAIN RESULTS: All-cause mortality, recurrent PE, and major bleeding up to 10 days after PE diagnosis were determined. Of 18,707 eligible patients with acute symptomatic PE, 46 (0.25%) developed recurrent PE, 203 (1.09%) bled, and 471 (2.51%) died. Predictors included in the final model were chronic heart failure, recent immobilization, recent major bleeding, cancer, hypotension, tachycardia, hypoxemia, renal insufficiency, and abnormal platelet count. The area under receiver-operating characteristic curve was 0.77 (95% confidence interval [CI], 0.75-0.78) for the RIETE score, 0.72 (95% CI, 0.70-0.73) for PESI (P < 0.05), and 0.71 (95% CI, 0.69-0.73) for sPESI (P < 0.05). Our RIETE score outperformed the prognostic value of PESI in terms of net reclassification improvement (P < 0.001), integrated discrimination improvement (P < 0.001), and sPESI (net reclassification improvement, P < 0.001; integrated discrimination improvement, P < 0.001). CONCLUSIONS: We built a new score, based on widely available variables, that can be used to identify patients with PE at low risk of short-term complications, assisting in triage and potentially shortening duration of hospital stay.

Modelling body mass index and endometrial cancer risk in a pooled-analysis of three case-control studies.

OBJECTIVE: To quantify the relation between body mass index (BMI) and endometrial cancer risk, and to describe the shape of such a relation. DESIGN: Pooled analysis of three hospital-based case-control studies. SETTING: Italy and Switzerland. POPULATION: A total of 1449 women with endometrial cancer and 3811 controls. METHODS: Multivariate odds ratios (OR) and 95% confidence intervals (95% CI) were obtained from logistic regression models. The shape of the relation was determined using a class of flexible regression models. MAIN OUTCOME MEASURE: The relation of BMI with endometrial cancer. RESULTS: Compared with women with BMI 18.5 to <25 kg/m(2) , the odds ratio was 5.73 (95% CI 4.28-7.68) for women with a BMI ≥35 kg/m(2) . The odds ratios were 1.10 (95% CI 1.09-1.12) and 1.63 (95% CI 1.52-1.75) respectively for an increment of BMI of 1 and 5 units. The relation was stronger in never-users of oral contraceptives (OR 3.35, 95% CI 2.78-4.03, for BMI ≥30 versus <25 kg/m(2) ) than in users (OR 1.22, 95% CI 0.56-2.67), and in women with diabetes (OR 8.10, 95% CI 4.10-16.01, for BMI ≥30 versus <25 kg/m(2) ) than in those without diabetes (OR 2.95, 95% CI 2.44-3.56). The relation was best fitted by a cubic model, although after the exclusion of the 5% upper and lower tails, it was best fitted by a linear model. CONCLUSIONS: The results of this study confirm a role of elevated BMI in the aetiology of endometrial cancer and suggest that the risk in obese women increases in a cubic nonlinear fashion. The relation was stronger in never-users of oral contraceptives and in women with diabetes. TWEETABLE ABSTRACT: Risk of endometrial cancer increases with elevated body weight in a cubic nonlinear fashion.

Association between Long-Term Exposure to Traffic-Related Air Pollution and Subclinical Atherosclerosis: The REGICOR Study

Background: Epidemiological evidence of the effects of long-term exposure to air pollu tion on the chronic processes of athero genesis is limited. Objective: We investigated the association of long-term exposure to traffic-related air pollu tion with subclinical atherosclerosis, measured by carotid intima media thickness (IMT) and ankle–brachial index (ABI). Methods: We performed a cross-sectional analysis using data collected during the reexamination (2007–2010) of 2,780 participants in the REGICOR (Registre Gironí del Cor: the Gerona Heart Register) study, a population-based prospective cohort in Girona, Spain. Long-term exposure across residences was calculated as the last 10 years’ time-weighted average of residential nitrogen dioxide (NO2) estimates (based on a local-scale land-use regression model), traffic intensity in the nearest street, and traffic intensity in a 100 m buffer. Associations with IMT and ABI were estimated using linear regression and multinomial logistic regression, respectively, controlling for sex, age, smoking status, education, marital status, and several other potential confounders or intermediates. Results: Exposure contrasts between the 5th and 95th percentiles for NO2 (25 μg/m), traffic intensity in the nearest street (15,000 vehicles/day), and traffic load within 100 m (7,200,000 vehicle-m/day) were associated with differences of 0.56% (95% CI: –1.5, 2.6%), 2.32% (95% CI: 0.48, 4.17%), and 1.91% (95% CI: –0.24, 4.06) percent difference in IMT, respectively. Exposures were positively associated with an ABI of > 1.3, but not an ABI of < 0.9. Stronger associations were observed among those with a high level of education and in men ≥ 60 years of age. Conclusions: Long-term traffic-related exposures were associated with subclinical markers of atherosclerosis. Prospective studies are needed to confirm associations and further examine differences among population subgroups.key words: ankle–brachial index, average daily traffic, cardiovascular disease, exposure assessment, exposure to tailpipe emissions, intima media thickness, land use regression model, Mediterranean diet, nitrogen dioxide

Mood and anxiety disorders across the adult lifespan: a European perspective

BACKGROUND: The World Mental Health Survey Initiative (WMHSI) has advanced our understanding of mental disorders by providing data suitable for analysis across many countries. However, these data have not yet been fully explored from a cross-national lifespan perspective. In particular, there is a shortage of research on the relationship between mood and anxiety disorders and age across countries. In this study we used multigroup methods to model the distribution of 12-month DSM-IV/CIDI mood and anxiety disorders across the adult lifespan in relation to determinants of mental health in 10 European Union (EU) countries. METHOD: Logistic regression was used to model the odds of any mood or any anxiety disorder as a function of age, gender, marital status, urbanicity and employment using a multigroup approach (n = 35500). This allowed for the testing of specific lifespan hypotheses across participating countries. RESULTS: No simple geographical pattern exists with which to describe the relationship between 12-month prevalence of mood and anxiety disorders and age. Of the adults sampled, very few aged ≥ 80 years met DSM-IV diagnostic criteria for these disorders. The associations between these disorders and key sociodemographic variables were relatively homogeneous across countries after adjusting for age. CONCLUSIONS: Further research is required to confirm that there are indeed stages in the lifespan where the reported prevalence of mental disorders is low, such as among younger adults in the East and older adults in the West. This project illustrates the difficulties in conducting research among different age groups simultaneously.

Nutrimetabolomics fingerprinting to identify biomarkers of bread exposure in a free-living population from the PREDIMED study cohort

Bread is one of the most widely consumed foods. Its impact on human health is currently of special interest for researchers. We aimed to identify biomarkers of bread consumption by applying a nutrimetabolomic approach to a free-living population. An untargeted HPLC q-TOF-MS and multivariate analysis was applied to human urine from 155 subjects stratified by habitual bread consumption in three groups: non-consumers of bread (n = 56), white-bread consumers (n = 48) and whole-grain bread consumers (n = 51). The most differential metabolites (variable importance for projection ≥1.5) included compounds originating from cereal plant phytochemicals such as benzoxazinoids and alkylresorcinol metabolites, and compounds produced by gut microbiota (such as enterolactones, hydroxybenzoic and dihydroferulic acid metabolites). Pyrraline, riboflavin, 3-indolecarboxylic acid glucuronide, 2,8-dihydroxyquinoline glucuronide and N-α-acetylcitrulline were also tentatively identified. In order to combine multiple metabolites in a model to predict bread consumption, a stepwise logistic regression analysis was used. Receiver operating curves were constructed to evaluate the global performance of individual metabolites and their combination. The area under the curve values [AUC (95 % CI)] of combined models ranged from 77.8 % (69.1 86.4 %) to 93.7 % (89.4 98.1 %), whereas the AUC for the metabolites included in the models had weak values when they were evaluated individually: from 58.1 % (46.6 69.7 %) to 78.4 % (69.8 87.1 %). Our study showed that a daily bread intake significantly impacted on the urinary metabolome, despite being examined under uncontrolled free-living conditions. We further concluded that a combination of several biomarkers of exposure is better than a single biomarker for the predictive ability of discriminative analysis.

Nutrimetabolomics fingerprinting to identify biomarkers of bread exposure in a free-living population from the PREDIMED study cohort

Bread is one of the most widely consumed foods. Its impact on human health is currently of special interest for researchers. We aimed to identify biomarkers of bread consumption by applying a nutrimetabolomic approach to a free-living population. An untargeted HPLC q-TOF-MS and multivariate analysis was applied to human urine from 155 subjects stratified by habitual bread consumption in three groups: non-consumers of bread (n = 56), white-bread consumers (n = 48) and whole-grain bread consumers (n = 51). The most differential metabolites (variable importance for projection ≥1.5) included compounds originating from cereal plant phytochemicals such as benzoxazinoids and alkylresorcinol metabolites, and compounds produced by gut microbiota (such as enterolactones, hydroxybenzoic and dihydroferulic acid metabolites). Pyrraline, riboflavin, 3-indolecarboxylic acid glucuronide, 2,8-dihydroxyquinoline glucuronide and N-α-acetylcitrulline were also tentatively identified. In order to combine multiple metabolites in a model to predict bread consumption, a stepwise logistic regression analysis was used. Receiver operating curves were constructed to evaluate the global performance of individual metabolites and their combination. The area under the curve values [AUC (95 % CI)] of combined models ranged from 77.8 % (69.1 86.4 %) to 93.7 % (89.4 98.1 %), whereas the AUC for the metabolites included in the models had weak values when they were evaluated individually: from 58.1 % (46.6 69.7 %) to 78.4 % (69.8 87.1 %). Our study showed that a daily bread intake significantly impacted on the urinary metabolome, despite being examined under uncontrolled free-living conditions. We further concluded that a combination of several biomarkers of exposure is better than a single biomarker for the predictive ability of discriminative analysis.

Konkurssin ennustaminen ja makrotaloudelliset muuttujat: rakennusalan pk-yritykset

Tämän tutkimuksen tavoitteena on selvittää kannattaako makrotaloudellisia muuttujia käyttää tunnuslukujen lisäksi yrityksen konkurssin ennustamisessa. Perinteiset konkurssinennustamismallit hyödyntävät pelkästään tilinpäätöksestä saatavia tunnuslukuja eivätkä huomioi yrityksen toimintaympäristöä ja sen muutoksia. Aiemmissa tutkimuksissa makrotaloudellisilla muuttujilla on pystytty parantamaan perinteisiä ennustamismalleja. Tutkimus toteutetaan luomalla kolme erilaista konkurssinennustamismallia logistista regressioanalyysiä hyödyntäen ja vertailemalla niiden paremmuutta. Tutkimustulokset osoittavat, että rakennusalan pk-yritysten konkursseja pystytään ennustamaan kolmen tunnusluvun mallilla. Taloudellisen ajanjakson, jolta yrityksen tiedot ovat peräisin, huomioiminen ei tuo malliin lisäarvoa eikä paranna ennustamiskykyä merkittävästi.

Konkurssin ennustaminen ja makrotaloudelliset muuttujat: rakennusalan pk-yritykset

Tämän tutkimuksen tavoitteena on selvittää kannattaako makrotaloudellisia muuttujia käyttää tunnuslukujen lisäksi yrityksen konkurssin ennustamisessa. Perinteiset konkurssinennustamismallit hyödyntävät pelkästään tilinpäätöksestä saatavia tunnuslukuja eivätkä huomioi yrityksen toimintaympäristöä ja sen muutoksia. Aiemmissa tutkimuksissa makrotaloudellisilla muuttujilla on pystytty parantamaan perinteisiä ennustamismalleja. Tutkimus toteutetaan luomalla kolme erilaista konkurssinennustamismallia logistista regressioanalyysiä hyödyntäen ja vertailemalla niiden paremmuutta. Tutkimustulokset osoittavat, että rakennusalan pk-yritysten konkursseja pystytään ennustamaan kolmen tunnusluvun mallilla. Taloudellisen ajanjakson, jolta yrityksen tiedot ovat peräisin, huomioiminen ei tuo malliin lisäarvoa eikä paranna ennustamiskykyä merkittävästi.

Leptin is not associated independently with hypertension in Japanese-Brazilian women

We evaluated the relationship of leptin with hypertension adjusted for body mass index (BMI) and/or waist circumference in a population of Japanese-Brazilian women aged > or = 30 years with centrally distributed adiposity. After excluding diabetic subjects, the study subjects - who participated in a population-based study on the prevalence of metabolic syndrome - showed prevalence rates of obesity (BMI > or = 25 kg/m²) and central adiposity (waist > or = 80 cm) of 32.0 and 37.8%, respectively. The hypertensive group (N = 162) was older, had higher BMI (24.9 ± 4.2 vs 23.3 ± 3.4 kg/m², P < 0.001), waist circumference (81.1 ± 10.1 vs 76.3 ± 8.2 cm, P < 0.001) and insulin levels (8.0 ± 6.2 vs 7.1 ± 4.9 µU/mL, P < 0.05) than the normotensive group (N = 322) and showed an unfavorable metabolic profile (higher 2-h plasma glucose, C-reactive protein and non-HDL cholesterol levels). Leptin did not differ between groups (8.2 ± 6.8 vs 7.2 ± 6.6 ng/mL, P = 0.09, for hypertensive vs normotensive, respectively) and its levels correlated significantly with anthropometric variables but not with blood pressure. Logistic regression analysis indicated that age and waist were independently associated with hypertension but not with homeostasis model assessment of insulin resistance or leptin levels. The lack of an independent association of hypertension with metabolic parameters (2-h glucose, C-reactive protein and non-HDL cholesterol) after adjustment for central adiposity suggested that visceral fat deposition may be the common mediator of the disturbances of the metabolic syndrome. Our data indicate that age and waist are major determinants of hypertension in this population of centrally obese (waist > or = 80 cm) Japanese-Brazilian women, but do not support a role for leptin in the elevation of blood pressure.

Can course format influence the performance of students in an advanced cardiac life support (ACLS) program?

Advanced cardiac life support (ACLS) is a problem-based course that employs simulation techniques to teach the standard management techniques of cardiovascular emergencies. Its structure is periodically revised according to new versions of the American Heart Association guidelines. Since it was introduced in Brazil in 1996, the ACLS has been through two conceptual and structural changes. Detailed documented reports on the effect of these changes on student performance are limited. The objective of the present study was to evaluate the effect of conceptual and structural changes of the course on student ACLS performance at a Brazilian training center. This was a retrospective study of 3266 students divided into two groups according to the teaching model: Model 1 (N = 1181; 1999-2003) and Model 2 (N = 2085; 2003-2007). Model 2 increased practical skill activities to 75% of the total versus 60% in Model 1. Furthermore, the teaching material provided to the students before the course was more objective than that used for Model 1. Scores greater than 85% in the theoretical evaluation and approval in the evaluation of practice by the instructor were considered to be a positive outcome. Multiple logistic regression was used to adjust for potential confounders (specialty, residency, study time, opportunity to enhance practical skills during the course and location where the course was given). Compared to Model 1, Model 2 presented odds ratios (OR) indicating better performance in the theoretical (OR = 1.34; 95%CI = 1.10-1.64), practical (OR = 1.19; 95%CI = 0.90-1.57), and combined (OR = 1.38; 95%CI = 1.13-1.68) outcomes. Increasing the time devoted to practical skills did not improve the performance of ACLS students.

IGF2, LEPR, POMC, PPARG, and PPARGC1 gene variants are associated with obesity-related risk phenotypes in Brazilian children and adolescents

Association studies of genetic variants and obesity and/or obesity-related risk factors have yielded contradictory results. The aim of the present study was to determine the possible association of five single-nucleotide polymorphisms (SNPs) located in the IGF2, LEPR, POMC, PPARG, and PPARGC1genes with obesity or obesity-related risk phenotypes. This case-control study assessed overweight (n=192) and normal-weight (n=211) children and adolescents. The SNPs were analyzed using minisequencing assays, and variables and genotype distributions between the groups were compared using one-way analysis of variance and Pearson's chi-square or Fisher's exact tests. Logistic regression analysis adjusted for age and gender was used to calculate the odds ratios (ORs) for selected phenotype risks in each group. No difference in SNP distribution was observed between groups. In children, POMC rs28932472(C) was associated with lower diastolic blood pressure (P=0.001), higher low-density lipoprotein (LDL) cholesterol (P=0.014), and higher risk in overweight children of altered total cholesterol (OR=7.35, P=0.006). In adolescents, IGF2 rs680(A) was associated with higher glucose (P=0.012) and higher risk in overweight adolescents for altered insulin (OR=10.08, P=0.005) and homeostasis model of insulin resistance (HOMA-IR) (OR=6.34, P=0.010). PPARGrs1801282(G) conferred a higher risk of altered insulin (OR=12.31, P=0.003), and HOMA-IR (OR=7.47, P=0.005) in overweight adolescents. PARGC1 rs8192678(A) was associated with higher triacylglycerols (P=0.005), and LEPR rs1137101(A) was marginally associated with higher LDL cholesterol (P=0.017). LEPR rs1137101(A) conferred higher risk for altered insulin, and HOMA-IR in overweight adolescents. The associations observed in this population suggested increased risk for cardiovascular diseases and/or type 2 diabetes later in life for individuals carrying these alleles.

The impact of tobacco control policies on university students' smoking in Ontario

Objective. Despite steady declines in the prevalence of tobacco use among Canadians, young adult tobacco use has remained stubbornly high over the past two decades (CTUMS, 2005a). Currently in Ontario, young adults have the highest proportion of smokers of all age cohorts at 26%. A growing body of evidence shows that smoking restrictions and other tobacco control policies can reduce tobacco use and consumption among adults and deter initiation among youth; whether young adult university students' smoking participation is influenced by community smoking restrictions, campus tobacco control policies or both remains an empirical question. The purpose of this study is to examine the relationship among current smoking status of students on university campuses across Ontario and various tobacco control policies, 3including clean air bylaws of students' home towns, clean air by-laws of the community where the university is situated, and campus policies. Methods. Two data sets were used. The 200512006 Tobacco Use in a Representative Sample of Post-Secondary Students data set provides information about the tobacco use of 10,600 students from 23 universities and colleges across Ontario. Data screening for this study reduced the sample to 5,114 17-to-24 year old undergraduate students from nine universities. The second data set is researcher-generated and includes information about strength and duration of, and students' exposure to home town, local and campus tobacco control policies. Municipal by-laws (of students' home towns and university towns) were categorized as weak, moderate or strong based on criteria set out in the Ontario Municipal By-law Report; campus policies were categorized in a roughly parallel fashion. Durations of municipal and campus policies were calculated; and length of students' exposure to the policies was estimated (all in months). Multinomial logistic regression analyses were used to examine the relationship between students' current smoking status (daily, less-than-daily, never-smokers) and the following policy measures: strength of, duration of, and students' exposure to campus policy; strength of, duration of, and students' exposure to the by-law in the university town; and, strength of, duration of, and students' exposure to the by-law in the home town they grew up in. Sociodemographic variables were controlled for. Results. Among the Ontario university students surveyed, 7.0% currently use tobacco daily and 15.4% use tobacco less-than-daily. The proportions of students experiencing strong tobacco control policies in their home town, the community in which their university is located and at their current university were 33.9%,64.1 %, and 31.3% respectively. However, 13.7% of students attended a university that had a weak campus policy. Multinomial logistic regressions suggested current smoking status was associated with university town by-law strength, home town by-law strength and the strength of the campus tobacco control policy. In the fmal model, after controlling for sociodemographic factors, a strong by-law in the university town and a strong by-law in students' home town were associated with reduced odds of being both a less-than-daily (OR = 0.64, 95%CI: 0.48-0.86; OR = 0.80, 95%CI: 0.66-0.95) and daily smoker (OR = 0.59, 95%CI: 0.39-0.89; OR = 0.76, 95%CI: 0.58-0.99), while a weak campus tobacco control policy was associated with higher odds of being a daily smoker (OR = 2.08, 95%CI: 1.31-3.30) (but unrelated to less-than-daily smoking). Longer exposure to the municipal by-law (OR = 0.93; 95%CI: 0.90-0.96) was also related to smoking status. Conclusions. Students' smoking prevalence was associated with the strength of the restrictions in university, and with campus-specific tobacco control policies. Lessthan- daily smoking was not as strongly associated with policy measures as daily smoking was. University campuses may wish to adopt more progressive campus policies and support clean air restrictions in the broader community. More research is needed to determine the direction of influence between tobacco control policies and students' smoking.

The relationship between body mass index and breast cancer recurrence/progression and breast cancer-specific death

The aim of this study was to describe the nonlinear association between body mass index (BMI) and breast cancer outcomes and to determine whether BMI improves prediction of outcomes. A cohort of906 breast cancer patients diagnosed at Henry Ford Health System, Detroit (1985-1990) were studied. The median follow-up was 10 years. Multivariate logistic regression was used to model breast cancer recurrence/progression and breast cancer-specific death. Restricted cubic splines were used to model nonlinear effects. Receiver operator characteristic areas under the curves (ROC AUC) were used to evaluate prediction. BMI was nonlinearly associated with recurrence/progression and death (p= 0.0230 and 0.0101). Probability of outcomes increased with increase or decrease ofBMI away from 25. BMI splines were suggestive of improved prediction of death. The ROC AUCs for nested models with and without BMI were 0.8424 and 0.8331 (p= 0.08). I f causally associated, modifying patients BMI towards 25 may improve outcomes.