Epigenome-wide association study of total nicotine equivalents in multiethnic current smokers from three prospective cohorts.

The impact of tobacco exposure on health varies by race and ethnicity and is closely tied to internal nicotine dose, a marker of carcinogen uptake. DNA methylation is strongly responsive to smoking status and may mediate health effects, but study of associations with internal dose is limited. We performed a blood leukocyte epigenome-wide association study (EWAS) of urinary total nicotine equivalents (TNEs; a measure of nicotine uptake) and DNA methylation measured using the MethylationEPIC v1.0 BeadChip (EPIC) in six racial and ethnic groups across three cohort studies. In the Multiethnic Cohort Study (discovery, n = 1994), TNEs were associated with differential methylation at 408 CpG sites across >250 genomic regions (p < 9 × 10-8). The top significant sites were annotated to AHRR, F2RL3, RARA, GPR15, PRSS23, and 2q37.1, all of which had decreasing methylation with increasing TNEs. We identified 45 novel CpG sites, of which 42 were unique to the EPIC array and eight annotated to genes not previously linked with smoking-related DNA methylation. The most significant signal in a novel gene was cg03748458 in MIR383;SGCZ. Fifty-one of the 408 discovery sites were validated in the Singapore Chinese Health Study (n = 340) and the Southern Community Cohort Study (n = 394) (Bonferroni corrected p < 1.23 × 10-4). Significant heterogeneity by race and ethnicity was detected for CpG sites in MYO1G and CYTH1. Furthermore, TNEs significantly mediated the association between cigarettes per day and DNA methylation at 15 sites (average 22.5%-44.3% proportion mediated). Our multiethnic study highlights the transethnic and ethnic-specific methylation associations with internal nicotine dose, a strong predictor of smoking-related morbidities.

Ambient Air Pollutant Exposures and COVID-19 Severity and Mortality in a Cohort of Patients with COVID-19 in Southern California.

Rationale: Ecological studies have shown air pollution associations with coronavirus disease (COVID-19) outcomes. However, few cohort studies have been conducted. Objectives: To conduct a cohort study investigating the association between air pollution and COVID-19 severity using individual-level data from the electronic medical record. Methods: This cohort included all individuals who received diagnoses of COVID-19 from Kaiser Permanente Southern California between March 1 and August 31, 2020. One-year and 1-month averaged ambient air pollutant (particulate matter ⩽2.5 µm in aerodynamic diameter [PM2.5], NO2, and O3) exposures before COVID-19 diagnosis were estimated on the basis of residential address history. Outcomes included COVID-19-related hospitalizations, intensive respiratory support (IRS), and ICU admissions within 30 days and mortality within 60 days after COVID-19 diagnosis. Covariates included socioeconomic characteristics and comorbidities. Measurements and Main Results: Among 74,915 individuals (mean age, 42.5 years; 54% women; 66% Hispanic), rates of hospitalization, IRS, ICU admission, and mortality were 6.3%, 2.4%, 1.5%, and 1.5%, respectively. Using multipollutant models adjusted for covariates, 1-year PM2.5 and 1-month NO2 average exposures were associated with COVID-19 severity. The odds ratios associated with a 1-SD increase in 1-year PM2.5 (SD, 1.5 µg/m3) were 1.24 (95% confidence interval [CI], 1.16-1.32) for COVID-19-related hospitalization, 1.33 (95% CI, 1.20-1.47) for IRS, and 1.32 (95% CI, 1.16-1.51) for ICU admission; the corresponding odds ratios associated with 1-month NO2 (SD, 3.3 ppb) were 1.12 (95% CI, 1.06-1.17) for hospitalization, 1.18 (95% CI, 1.10-1.27) for IRS, and 1.21 (95% CI, 1.11-1.33) for ICU admission. The hazard ratios for mortality were 1.14 (95% CI, 1.02-1.27) for 1-year PM2.5 and 1.07 (95% CI, 0.98-1.16) for 1-month NO2. No significant interactions with age, sex or ethnicity were observed. Conclusions: Ambient PM2.5 and NO2 exposures may affect COVID-19 severity and mortality.

Healthcare Utilization Among Patients Diagnosed with COVID-19 in a Large Integrated Health System.

BACKGROUND: The demands for healthcare resources following a COVID-19 diagnosis are substantial, but not currently quantified. OBJECTIVE: To describe trends in healthcare utilization within 180 days for patients diagnosed with COVID-19 and identify patient factors associated with increased healthcare use. DESIGN: Observational cohort study. PATIENTS: A total of 64,011 patients with a test-confirmed COVID-19 diagnosis from March to September 2020 in a large integrated healthcare system in Southern California. MAIN MEASURES: Overall healthcare utilization during the 180 days following COVID-19 diagnosis, as well as encounter types and reasons for visits during the first 30 days. Poisson regression was used to identify patient factors associated with higher utilization. Analyses were performed separately for patients who were and were not hospitalized for COVID-19. KEY RESULTS: Healthcare utilization was about twice as high for hospitalized patients compared to non-hospitalized patients in all time periods. The average number of visits was highest in the first 30 days (hospitalized: 12.3 visits/30 person-days; non-hospitalized: 6.6) and gradually decreased over time. In the first 30 days, the majority of healthcare visits were telehealth encounters (hospitalized: 9.0 visits; non-hospitalized: 5.6 visits), and the most prevalent reasons for visits were COVID-related diagnoses, COVID-related symptoms, and respiratory-related conditions. For hospitalized patients, older age (≥65: RR 1.27, 95% CI 1.15-1.41), female gender (RR 1.07, 95% CI 1.05-1.09), and higher BMI (≥40: RR 1.07, 95% CI 1.03-1.10) were associated with higher total utilization. For non-hospitalized patients, older age, female gender, higher BMI, non-white race/ethnicity, former smoking, and greater number of pre-existing comorbidities were all associated with increased utilization. CONCLUSIONS: Patients with COVID-19 seek healthcare frequently within 30 days of diagnosis, placing high demands on health systems. Identifying ways to support patients diagnosed with COVID-19 while adequately providing the usual recommended care to our communities will be important as we recover from the pandemic.

Ambient air pollution and COVID-19 incidence during four 2020-2021 case surges.

BACKGROUND: Air pollution exposure may make people more vulnerable to COVID-19 infection. However, previous studies in this area mostly focused on infection before May 2020 and long-term exposure. OBJECTIVE: To assess both long-term and short-term exposure to air pollution and COVID-19 incidence across four case surges from 03/1/2020 to 02/28/2021. METHODS: The cohort included 4.6 million members from a large integrated health care system in southern California with comprehensive electronic medical records (EMR). COVID-19 cases were identified from EMR. Incidence of COVID-19 was computed at the census tract-level among members. Prior 1-month and 1-year averaged air pollutant levels (PM2.5, NO2, and O3) at the census tract-level were estimated based on hourly and daily air quality data. Data analyses were conducted by each wave: 3/1/2020-5/31/2020, 6/1/202-9/30/2020, 10/1/2020-12/31/2020, and 1/1/2021-2/28/2021 and pooled across waves using meta-analysis. Generalized linear mixed effects models with Poisson distribution and spatial autocorrelation were used with adjustment for meteorological factors and census tract-level social and health characteristics. Results were expressed as relative risk (RR) per 1 standard deviation. RESULTS: The cohort included 446,440 COVID-19 cases covering 4609 census tracts. The pooled RRs (95% CI) of COVID-19 incidence associated with 1-year exposures to PM2.5, NO2, and O3 were 1.11 (1.04, 1.18) per 2.3 µg/m3,1.09 (1.02, 1.17) per 3.2 ppb, and 1.06 (1.00, 1.12) per 5.5 ppb respectively. The corresponding RRs (95% CI) associated with prior 1-month exposures were 1.11 (1.03, 1.20) per 5.2 µg/m3 for PM2.5, 1.09 (1.01, 1.17) per 6.0 ppb for NO2 and 0.96 (0.85, 1.08) per 12.0 ppb for O3. CONCLUSION: Long-term PM2.5 and NO2 exposures were associated with increased risk of COVID-19 incidence across all case surges before February 2021. Short-term PM2.5 and NO2 exposures were also associated. Our findings suggest that air pollution may play a role in increasing the risk of COVID-19 infection.

Machine Learning for Early Lung Cancer Identification Using Routine Clinical and Laboratory Data.

Rationale: Most lung cancers are diagnosed at an advanced stage. Presymptomatic identification of high-risk individuals can prompt earlier intervention and improve long-term outcomes. Objectives: To develop a model to predict a future diagnosis of lung cancer on the basis of routine clinical and laboratory data by using machine learning. Methods: We assembled data from 6,505 case patients with non-small cell lung cancer (NSCLC) and 189,597 contemporaneous control subjects and compared the accuracy of a novel machine learning model with a modified version of the well-validated 2012 Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial risk model (mPLCOm2012), by using the area under the receiver operating characteristic curve (AUC), sensitivity, and diagnostic odds ratio (OR) as measures of model performance. Measurements and Main Results: Among ever-smokers in the test set, a machine learning model was more accurate than the mPLCOm2012 for identifying NSCLC 9-12 months before clinical diagnosis (P < 0.00001) and demonstrated an AUC of 0.86, a diagnostic OR of 12.3, and a sensitivity of 40.1% at a predefined specificity of 95%. In comparison, the mPLCOm2012 demonstrated an AUC of 0.79, an OR of 7.4, and a sensitivity of 27.9% at the same specificity. The machine learning model was more accurate than standard eligibility criteria for lung cancer screening and more accurate than the mPLCOm2012 when applied to a screening-eligible population. Influential model variables included known risk factors and novel predictors such as white blood cell and platelet counts. Conclusions: A machine learning model was more accurate for early diagnosis of NSCLC than either standard eligibility criteria for screening or the mPLCOm2012, demonstrating the potential to help prevent lung cancer deaths through early detection.

Red meat consumption, cooking mutagens, NAT1/2 genotypes and pancreatic cancer risk in two ethnically diverse prospective cohorts.

There is limited evidence on the association between red meat consumption and pancreatic cancer among ethnic minorities. We assessed this relationship in two large prospective cohorts: the Multiethnic Cohort Study (MEC) and the Southern Community Cohort Study (SCCS). Demographic, dietary and other risk factor data were collected at cohort entry. Red meat intake was assessed using cohort-specific validated food frequency questionnaires. Incident pancreatic cancer cases were identified via linkages to state cancer registries. Cox regression was used to calculate relative risks (RRs) and 95% confidence intervals (CIs) for the association of red meat intake with pancreatic cancer risk in each cohort. We performed additional analyses to evaluate cooking methods, mutagens and effect modification by NAT1/2 genotypes. From a total of 184 542 (MEC) and 66 793 (SCCS) at-risk participants, we identified 1618 (MEC) and 266 (SCCS) incident pancreatic cancer cases. Red meat consumption was associated with pancreatic cancer risk in the MEC (RRQ4vsQ1 1.18, 95% CI 1.02-1.37) and with borderline statistical significance in the SCCS (RRQ4vsQ1 1.31, 95% CI 0.93-1.86). This association was significant in African Americans (RRQ4vsQ1 1.49, 95% CI 1.06-2.11) and Latinos (RRQ4vsQ1 1.44, 95% CI 1.02-2.04) in the MEC, and among African Americans (RRQ4vsQ1 1.55, 95% CI 1.03-2.33) in the SCCS. NAT2 genotypes appeared to modify the relationship between red meat and pancreatic cancer in the MEC (pinteraction = 0.03). Our findings suggest that the associations for red meat may be strongest in African Americans and Latinos. The mechanisms underlying the increased risk for these populations should be further investigated.

Identifying patients with symptoms suspicious for COVID-19 at elevated risk of adverse events: The COVAS score.

OBJECTIVE: Develop and validate a risk score using variables available during an Emergency Department (ED) encounter to predict adverse events among patients with suspected COVID-19. METHODS: A retrospective cohort study of adult visits for suspected COVID-19 between March 1 - April 30, 2020 at 15 EDs in Southern California. The primary outcomes were death or respiratory decompensation within 7-days. We used least absolute shrinkage and selection operator (LASSO) models and logistic regression to derive a risk score. We report metrics for derivation and validation cohorts, and subgroups with pneumonia or COVID-19 diagnoses. RESULTS: 26,600 ED encounters were included and 1079 experienced an adverse event. Five categories (comorbidities, obesity/BMI ≥ 40, vital signs, age and sex) were included in the final score. The area under the curve (AUC) in the derivation cohort was 0.891 (95% CI, 0.880-0.901); similar performance was observed in the validation cohort (AUC = 0.895, 95% CI, 0.874-0.916). Sensitivity ranging from 100% (Score 0) to 41.7% (Score of ≥15) and specificity from 13.9% (score 0) to 96.8% (score ≥ 15). In the subgroups with pneumonia (n = 3252) the AUCs were 0.780 (derivation, 95% CI 0.759-0.801) and 0.832 (validation, 95% CI 0.794-0.870), while for COVID-19 diagnoses (n = 2059) the AUCs were 0.867 (95% CI 0.843-0.892) and 0.837 (95% CI 0.774-0.899) respectively. CONCLUSION: Physicians evaluating ED patients with pneumonia, COVID-19, or symptoms suspicious for COVID-19 can apply the COVAS score to assist with decisions to hospitalize or discharge patients during the SARS CoV-2 pandemic.

New-Onset Diabetes, Longitudinal Trends in Metabolic Markers, and Risk of Pancreatic Cancer in a Heterogeneous Population.

BACKGROUND & AIMS: Observational studies of predominantly white populations have found new-onset diabetes to be associated with increased risk of pancreatic cancer. We sought to determine whether this relationship applies to other races or ethnicities and to identify metabolic profiles associated with increased risk of pancreatic cancer. METHODS: We conducted a population-based cohort study of Asian, black, Hispanic and white patients from Kaiser Permanente Southern California from 2006 through 2016 (n = 1,499,627). Patients with diabetes were identified based on glucose and hemoglobin A1c (HbA1c) measurements. We used Cox regression to assess the relationship between diabetes status and duration and pancreatic cancer. For patients with recent diagnoses of diabetes (1 year or less) we compared longitudinal changes in glucose, HbA1c, and weight, from time of diabetes diagnosis through 3 years prior to the diagnosis, in patients with vs without pancreatic cancer. RESULTS: We identified 2,002 incident cases of pancreatic cancer from nearly 7.5 million person-years of follow-up. Compared to patients without diabetes, individuals who received a recent diagnosis of diabetes had an almost 7-fold increase in risk of pancreatic cancer (relative risk, 6.91; 95% CI, 5.76-8.30). Among patients with a recent diagnosis of diabetes, those who developed pancreatic cancer had more rapid increases in levels of glucose (Δslope: cases, 37.47 mg/dL vs non-cases, 27.68 mg/dL) and HbA1c (Δslope: cases, 1.39% vs non-cases, 0.86%) in the month preceding the diagnosis of diabetes, and subtle weight loss in the prior years (slope: cases -0.18 kg/interval vs non-cases 0.33 kg/interval). These longitudinal changes in markers of metabolism were stronger for specific race and ethnic groups. CONCLUSIONS: In a study of a large ethnically diverse population, we found risk of pancreatic cancer to be increased among patients with a diagnosis of diabetes in the past year among different races and ethnicities. Weight loss and rapid development of poor glycemic control were associated with increased risk of pancreatic cancer in multiple races.

Atopic allergic conditions and pancreatic cancer risk: Results from the Multiethnic Cohort Study.

Previous case-control studies have suggested that atopic allergic conditions (AACs) are inversely associated with pancreatic cancer, but this relationship has not been supported in many prospective settings. In this study, we investigated the influence of AACs (asthma, hay fever, or allergy) and the treatment of these conditions on pancreatic cancer risk among participants of the Multiethnic Cohort Study (MEC). AACs and antihistamine use were assessed via a baseline questionnaire when participants joined the MEC in 1993-1996. Risk ratios (RRs) and 95% confidence intervals (CIs) for pancreatic cancer incidence by AACs and antihistamines were calculated using Cox regression, adjusting for age, sex, ethnicity, education, smoking status, family history of pancreatic cancer, body mass index, diabetes, and alcohol intake. We further evaluated associations among subgroups defined by age, sex, ethnicity, follow-up time, and known pancreatic cancer risk factors. During an average 16-year follow-up, 1,455 incident cases of pancreatic cancer were identified among 187,226 white, African American, Latino, Japanese American, and Native Hawaiian men and women. AACs (RR 1.00, 95% CI 0.88-1.12) and antihistamines (RR 0.92, 95% CI 0.78-1.07) were not clearly associated with pancreatic cancer incidence. While these associations were also null for most subgroups, we did observe protective associations of AACs (RR 0.74, 95% CI 0.56-0.98) and antihistamines (RR 0.66, 95% CI 0.45-0.96) among the oldest participants (70+). Our results, in agreement with past prospective studies, suggest that AACs are not associated with pancreatic cancer in general, but the observed protective associations among the oldest age group may warrant future investigation.

Polymorphisms in genes related to inflammation and obesity and colorectal adenoma risk.

We previously investigated the association between single nucleotide polymorphisms (SNPs) in genes related to obesity and inflammation and colorectal cancer in the CLUE II cohort. However, the relationships between these SNPs and colorectal adenomas have not been well evaluated. In a nested case-control study of 135 incident adenoma cases and 269 matched controls in the CLUE II cohort (1989-2000), we genotyped 17 candidate SNPs in 12 genes (PPARG, TCF7L2, ADIPOQ, LEP, IL10, CRP, TLR4, IL6, IL1B, IL8, TNF, RNASEL) and 19 tagSNPs in three genes (IL10, CRP, and TLR4). Conditional logistic regression was used to calculate odds ratios (OR) for adenomas (overall and by size, histology, location, number). Polymorphisms in the inflammatory-related genes CRP, ADIPOQ, IL6, and TLR4 were observed to be associated with adenoma risk. At rs1205 in CRP, T (minor allele) carriers had a higher risk (OR 1.67, 95%CI 1.07-2.60; reference: CC) of adenomas overall and adenomas with aggressive characteristics. At rs1201299 in ADIPOQ, the AC genotype had a higher risk (OR 1.58, 95%CI 1.00-2.49) of adenomas, while the minor AA genotype had a borderline inverse association (OR 0.44, 95%CI 0.18-1.08; reference: CC). At rs1800797 in IL6, the AA genotype had a borderline inverse association (OR 0.53, 95%CI 0.27-1.05; reference: GG). Three TLR4 tagSNPs (rs10116253, rs1927911, rs7873784) were associated with adenomas among obese participants. None of these SNPs were associated with colorectal cancer in our prior study in CLUE II, possibly suggesting a different genetic etiology for early colorectal neoplasia.

Does Providing Positive Airway Pressure for Sleep Apnea Change Health Care Utilization?

BACKGROUND: Sleep apnea is underdiagnosed and thus undertreated. If therapy for sleep apnea results in reduced health care utilization in an entire treated population, then decision-makers will have key information for allocating limited health care resources. OBJECTIVES: To determine whether positive airway pressure (PAP) for sleep apnea was associated with reduced health care utilization in an entire treated population. RESEARCH DESIGN: This was a retrospective cohort; propensity score-matched cases and noncases; pre-post analyses of individual subject utilization. SUBJECTS: Electronic health records were used to identify adult subjects diagnosed with sleep apnea and dispensed PAP therapy (cases) and those without either diagnosed sleep apnea or dispensed PAP therapy (noncases). MEASURES: Acute care hospital days and dispensed medication days supply were compared in cases and noncases. Negative binomial regression was used to model utilization for up to 5 years before and 7 years after PAP dispensation (cases) or a random date (noncases). The association of PAP with changing annual utilization was estimated. RESULTS: There were 13,271 cases and 13,271 matched noncases from 2008 to 2012 for analyses. Trends in the annual rate of acute care utilization were no different between cases and noncases (rate ratio, 0.98, P=0.543). Trends in the annual rate of medication utilization were no different between cases and noncases (rate ratio, 1.008, P=0.112). CONCLUSIONS: PAP dispensation for sleep apnea did not appear to reduce the rate of acute care and medication utilization over several years of follow-up in a large integrated health care system.

Implementation of the Canadian CT Head Rule and Its Association With Use of Computed Tomography Among Patients With Head Injury.

STUDY OBJECTIVE: Approximately 1 in 3 computed tomography (CT) scans performed for head injury may be avoidable. We evaluate the association of implementation of the Canadian CT Head Rule on head CT imaging in community emergency departments (EDs). METHODS: We conducted an interrupted time-series analysis of encounters from January 2014 to December 2015 in 13 Southern California EDs. Adult health plan members with a trauma diagnosis and Glasgow Coma Scale score at ED triage were included. A multicomponent intervention included clinical leadership endorsement, physician education, and integrated clinical decision support. The primary outcome was the proportion of patients receiving a head CT. The unit of analysis was ED encounter, and we compared CT use pre- and postintervention with generalized estimating equations segmented logistic regression, with physician as a clustering variable. Secondary analysis described the yield of identified head injuries pre- and postintervention. RESULTS: Included were 44,947 encounters (28,751 preintervention and 16,196 postintervention), resulting in 14,633 (32.6%) head CTs (9,758 preintervention and 4,875 postintervention), with an absolute 5.3% (95% confidence interval [CI] 2.5% to 8.1%) reduction in CT use postintervention. Adjusted pre-post comparison showed a trend in decreasing odds of imaging (odds ratio 0.98; 95% CI 0.96 to 0.99). All but one ED reduced CTs postintervention (0.3% to 8.7%, one ED 0.3% increase), but no interaction between the intervention and study site over time existed (P=.34). After the intervention, diagnostic yield of CT-identified intracranial injuries increased by 2.3% (95% CI 1.5% to 3.1%). CONCLUSION: A multicomponent implementation of the Canadian CT Head Rule was associated with a modest reduction in CT use and an increased diagnostic yield of head CTs for adult trauma encounters in community EDs.

Competing Risks for Mortality in Patients With Asymptomatic Pancreatic Cystic Neoplasms: Implications for Clinical Management.

OBJECTIVES: Pancreatic cystic neoplasms (PCNs) are being detected with increased frequency. Current clinical practice guidelines emphasize management based on cyst-related features. We aimed to evaluate the impact of comorbidity on mortality in PCN patients via competing risk analysis. METHODS: We analyzed a retrospective cohort of patients diagnosed between 2005-2010, with follow-up through 2015, for overall and cause-specific mortality. Comorbidities were classified by the Charlson comorbidity index. We used Cox proportional hazards regression to evaluate the independent effect of cyst features, age, gender, and comorbidities on cause-specific mortality. Subgroup analysis was performed to determine the cause-specific mortality based on four a priori clinical profiles-healthy patients with low- or high-risk cysts, and high-comorbidity patients with low- or high-risk cysts. RESULTS: A total of 1,800 patients with PCNs comprised the study cohort (median follow-up 5.7 years). A total of 402 deaths (22.3%) occurred during the study period: 43 pancreatic cancer and 359 non-pancreatic cancer deaths. Compared to healthy patients without any high-risk cyst features (reference group), patients with high comorbidity as well as high-risk cyst features had an increased risk of overall mortality (Cox hazard ratio 6.30, 95% confidence interval (CI) 4.71, 8.42, P<0.01), pancreatic cancer mortality (subdistribution hazard ratio (SHR) 51.13, 95% CI 6.35, 411.29, P<0.01), as well as non-pancreatic cancer mortality (SHR 5.24, 95% CI 3.85, 7.12, P<0.01). Meanwhile, low-risk patients with a high-risk cyst were more likely to experience pancreatic cancer mortality (SHR 68.14, 95% CI 9.27, 501.01, P<0.01) rather than non-pancreatic cancer mortality (SHR 1.22, 95% CI 0.88, 1.71, P=0.23), compared to the reference group. Similarly, compared to the reference group, high-risk patients with a low-risk cyst were more likely to experience non-pancreatic cancer mortality (SHR 3.96, 95% CI 2.98, 5.26, P<0.01) rather than pancreatic cancer mortality (SHR 2.35, 95% CI 0.14, 38.82, P=0.55). CONCLUSIONS: Most of the deaths in the study were unrelated to pancreatic cancer. This has implications for clinical management. By applying patient-related factors in conjunction with cyst features, we defined commonly encountered patient profiles to help guide PCN clinical management.

Burden of preoperative cardiovascular disease risk factors on breast cancer surgery outcomes.

BACKGROUND: Cardiovascular comorbidities have been studied sporadically in breast cancer surgery. No study has provided a comprehensive assessment of the severity and relative influence of preoperative cardiac risk factors on surgical outcomes. METHODS: 78,338 breast cancer surgery patients were identified from the 2006 to 2012 National Surgical Quality Improvement Program (NSQIP) database. We estimated the impact of chronic conditions (diabetes, hypertension, obesity, smoking), acute cardiac events (myocardial infarction, congestive heart disease, angina), and past cardiac procedures (cardiac surgery, percutaneous coronary intervention) on 30-day postoperative complications, reoperation, and readmission. RESULTS: Nearly 65% of patients had chronic conditions, <1% had acute events, and 3% had past procedures. The prevalence of outcomes was low: 5% had complications, 4% underwent reoperation, and 4% were readmitted. Over 65% of complications were wound-related. All risk factor categories were associated with complications (ORs from 1.26 to 4.18). Acute events had the strongest effect on overall (OR 3.54, CI 2.55-4.91) and medical (OR 4.18, CI 2.73-6.41) complications. Chronic conditions and past procedures also predicted reoperation and readmission (ORs from 1.57 to 2.68). The odds of all outcomes increased with the number of chronic conditions (ptrend < 0.001). CONCLUSIONS: Cardiovascular disease has a significant impact on outcomes even in minimal-risk breast cancer surgery. J. Surg. Oncol. 2016;114:144-149. © 2016 Wiley Periodicals, Inc.

Genetic Evidence for a Causal Link between Intra-Pancreatic Fat Deposition and Pancreatitis: a Mendelian Randomization Study.

Introduction: Recent associative studies have linked intra-pancreatic fat deposition (IPFD) with risk of pancreatitis, but the causal relationship remains unclear. Methods: Utilizing Mendelian randomization, we evaluated the causal association between genetically predicted IPFD and pancreatitis. This approach utilized genetic variants from genome-wide association studies of IPFD (n=25,617), acute pancreatitis (n=6,787 cases/361,641 controls), and chronic pancreatitis (n=3,875 cases/361,641 controls). Results: Genetically predicted IPFD was significantly associated with acute pancreatitis (OR per 1-SD increase: 1.40[95%CI:1.12-1.76], p=0.0032) and chronic pancreatitis (OR:1.64[95%CI:1.13-2.39], p=0.0097). Discussion: Our findings support a causal role of IPFD in pancreatitis, suggesting that reducing IPFD could lower the risk of pancreatitis.

Genetically Determined Circulating Lactase/Phlorizin Hydrolase Concentrations and Risk of Colorectal Cancer: A Two-Sample Mendelian Randomization Study.

Previous research has found that milk is associated with a decreased risk of colorectal cancer (CRC). However, it is unclear whether the milk digestion by the enzyme lactase-phlorizin hydrolase (LPH) plays a role in CRC susceptibility. Our study aims to investigate the direct causal relationship of CRC risk with LPH levels by applying a two-sample Mendelian Randomization (MR) strategy. Genetic instruments for LPH were derived from the Fenland Study, and CRC-associated summary statistics for these instruments were extracted from the FinnGen Study, PLCO Atlas Project, and Pan-UK Biobank. Primary MR analyses focused on a cis-variant (rs4988235) for LPH levels, with results integrated via meta-analysis. MR analyses using all variants were also undertaken. This analytical approach was further extended to assess CRC subtypes (colon and rectal). Meta-analysis across the three datasets illustrated an inverse association between genetically predicted LPH levels and CRC risk (OR: 0.92 [95% CI, 0.89-0.95]). Subtype analyses revealed associations of elevated LPH levels with reduced risks for both colon (OR: 0.92 [95% CI, 0.89-0.96]) and rectal cancer (OR: 0.92 [95% CI, 0.87, 0.98]). Consistency was observed across varied analytical methods and datasets. Further exploration is warranted to unveil the underlying mechanisms and validate LPH's potential role in CRC prevention.