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AbstractObjective:To assess the utility of an automated, statistically-based outbreak detection system to identify clusters of hospital-acquired microorganisms.Design:Multicenter retrospective cohort study.Setting:The study included 43 hospitals using a common infection prevention surveillance system.Methods:A space–time permutation scan statistic was applied to hospital microbiology, admission, discharge, and transfer data to identify clustering of microorganisms within hospital locations and services. Infection preventionists were asked to rate the importance of each cluster. A convenience sample of 10 hospitals also provided information about clusters previously identified through their usual surveillance methods.Results:We identified 230 clusters in 43 hospitals involving Gram-positive and -negative bacteria and fungi. Half of the clusters progressed after initial detection, suggesting that early detection could trigger interventions to curtail further spread. Infection preventionists reported that they would have wanted to be alerted about 81% of these clusters. Factors associated with clusters judged to be moderately or highly concerning included high statistical significance, large size, and clusters involving Clostridioides difficileor multidrug-resistant organisms. Based on comparison data provided by the convenience sample of hospitals, only 9 (18%) of 51 clusters detected by usual surveillance met statistical significance, and of the 70 clusters not previously detected, 58 (83%) involved organisms not routinely targeted by the hospitals’ surveillance programs. All infection prevention programs felt that an automated outbreak detection tool would improve their ability to detect outbreaks and streamline their work.Conclusions:Automated, statistically-based outbreak detection can increase the consistency, scope, and comprehensiveness of detecting hospital-associated transmission.

Supplemental Digital Content is available in the text.The tree-based scan statistic is a statistical data mining tool that has been used for signal detection with a self-controlled design in vaccine safety studies. This disproportionality statistic adjusts for multiple testing in evaluation of thousands of potential adverse events. However, many drug safety questions are not well suited for self-controlled analysis. We propose a method that combines tree-based scan statistics with propensity score–matched analysis of new initiator cohorts, a robust design for investigations of drug safety. We conducted plasmode simulations to evaluate performance. In multiple realistic scenarios, tree-based scan statistics in cohorts that were propensity score matched to adjust for confounding outperformed tree-based scan statistics in unmatched cohorts. In scenarios where confounding moved point estimates away from the null, adjusted analyses recovered the prespecified type 1 error while unadjusted analyses inflated type 1 error. In scenarios where confounding moved point estimates toward the null, adjusted analyses preserved power, whereas unadjusted analyses greatly reduced power. Although complete adjustment of true confounders had the best performance, matching on a moderately mis-specified propensity score substantially improved type 1 error and power compared with no adjustment. When there was true elevation in risk of an adverse event, there were often co-occurring signals for clinically related concepts. TreeScan with propensity score matching shows promise as a method for screening and prioritization of potential adverse events. It should be followed by clinical review and safety studies specifically designed to quantify the magnitude of effect, with confounding control targeted to the outcome of interest.

Since 2010, four oral anticoagulants have been approved for marketing in addition to warfarin for treatment of thromboembolic disease. Limited head-to-head data exist comparing these treatments, leaving patients and clinicians with little guidance for selecting a strategy that balances recurrence reduction with bleeding risk. In the dabigatran, apixaban, rivaroxban, edoxaban and warfarin comparative effectiveness research study, we compare all five currently available oral anticoagulant agents for the extended treatment of deep venous thrombosis and pulmonary embolism, as well as no extended treatment, and evaluate whether results differ in specific sub-populations. As our population includes Medicare novel anticoagulant users and large numbers of commercially insured and Medicaid patients, our results will likely be transportable to the majority of US patients experiencing a DVT or pulmonary embolism. Clinical Trials registration: NCT03271450.

Big datais a term used for any collection of datasets whose size and complexity exceeds the capabilities of traditional data processing applications. Big data repositories, including those for molecular, clinical, and epidemiology data, offer unprecedented research opportunities to help guide scientific advancement. Advantages of big data can include ease and low cost of collection, ability to approach prospectively and retrospectively, utility for hypothesis generation in addition to hypothesis testing, and the promise of precision medicine. Limitations include cost and difficulty of storing and processing data; need for advanced techniques for formatting and analysis; and concerns about accuracy, reliability, and security. We discuss sources of big data and tools for its analysis to help inform the treatment and management of dermatologic diseases.

ABSTRACTTo assess the relationship between human papillomavirus (HPV) vaccination and occurrence of optic neuritis (ON) and to evaluate a claims-based algorithm for identification of ON. Females of 9–26 year olds in the HealthCore's Integrated Research Database (HIRDSM) with and without claims evidence of HPV vaccination between 2007 and 2012 were included in this study. Potential ON cases were identified using the claims-based algorithm, positive predictive value (PPV) was determined using medical chart review. For the claims analysis, two study designs, a self-controlled temporal scan statistic and a retrospective matched cohort analysis, were used. ON was defined based on an algorithm developed using diagnosis and procedure codes from the medical claims. The PPV for ON cases using charts that had enough information for reviewers to make a determination was 62.5% (95% CI: 49.5%–74.3%). With the self-controlled temporal scan statistic, the primary analysis restricting on recommended vaccination schedule timing showed an increased risk of potential ON after second dose (RR = 3.39; p = 0.03), this finding was not confirmed for any of the additional analyses performed for individual or combined doses. With the cohort design, there was no increased risk of potential ON following vaccination in either individual or combined dose analyses. The risk of potential ON was higher among participants with a history of prior autoimmune diseases. In conclusion, identifying confirmed ON cases through administrative claims data proved challenging. The claims-based analysis in this study did not provide evidence for an association of ON with HPV vaccination.

IMPORTANCE: Rates of skin cancer, including basal cell carcinoma (BCC), the most common cancer, have been increasing over the past 3 decades. A better understanding of geographic clustering of BCCs can help target screening and prevention efforts. OBJECTIVE: Present a methodology to identify spatial clusters of BCC and identify such clusters in a northern California population. DESIGN, SETTING, AND PARTICIPANTS: This retrospective study used a BCC registry to determine rates of BCC by census block group, and used spatial scan statistics to identify statistically significant geographic clusters of BCCs, adjusting for age, sex, and socioeconomic status. The study population consisted of white, non-Hispanic members of Kaiser Permanente Northern California during years 2011 and 2012. MAIN OUTCOMES AND MEASURES: Statistically significant geographic clusters of BCC as determined by spatial scan statistics. RESULTS: Spatial analysis of 28 408 individuals who received a diagnosis of at least 1 BCC in 2011 or 2012 revealed distinct geographic areas with elevated BCC rates. Among the 14 counties studied, BCC incidence ranged from 661 to 1598 per 100 000 person-years. After adjustment for age, sex, and neighborhood socioeconomic status, a pattern of 5 discrete geographic clusters emerged, with a relative risk ranging from 1.12 (95% CI, 1.03-1.21; P = .006) for a cluster in eastern Sonoma and northern Napa Counties to 1.40 (95% CI, 1.15-1.71; P < .001) for a cluster in east Contra Costa and west San Joaquin Counties, compared with persons residing outside that cluster. CONCLUSIONS AND RELEVANCE: In this study of a northern California population, we identified several geographic clusters with modestly elevated incidence of BCC. Knowledge of geographic clusters can help inform future research on the underlying etiology of the clustering including factors related to the environment, health care access, or other characteristics of the resident population, and can help target screening efforts to areas of highest yield.

AbstractBackground:The Massachusetts Childhood Obesity Research Demonstration (MA-CORD) project is a 2-year, multilevel, multisector community intervention to prevent and control obesity among children 2–12 years of age from two predominantly low-income communities in Massachusetts. MA-CORD includes evidence-based interventions in multiple sectors, including community health centers, early care and education centers, schools, afterschool programs, the Special Supplemental Nutrition Program for Women, Infants and Children, and the broader community. Currently, implementation of MA-CORD is complete and the final year of data collection is in progress. Here, the MA-CORD evaluation plan is described and baseline data are presented.Methods/Design:The impact of MA-CORD on children's BMI, lifestyle behaviors, obesity-related care, and quality of life will be assessed using sector-specific, pre/post, time-series, and quasi-experimental designs. Change in the primary outcomes will be compared for intervention and comparison communities. Additionally, change in mean BMI and obesity prevalence in intervention school districts will be compared to similar districts throughout the state.Results:At baseline in 2012, approximately 16% of preschool-aged and 25% of school-aged children were obese. Moreover, 15–40% of children consumed no vegetables on the previous day, 25–75% drank a sugar-sweetened beverage on the previous day, up to 87% had insufficient physical activity, 50–75% had a television in the room where they slept, and 50–80% obtained insufficient sleep.Conclusions:There is ample room for improvement in BMI and health behaviors in children in MA-CORD communities. If successful, MA-CORD may serve as a model for multilevel, multisector approaches to childhood obesity prevention and control.

Objectives. We compared an electronic health record-based influenza-like illness (ILI) surveillance system with manual sentinel surveillance and virologic data to evaluate the utility of the automated system for routine ILI surveillance.Methods. We obtained weekly aggregate ILI reports from the Electronic medical record Support for Public Health (ESP) disease-detection and reporting system, which used an automated algorithm to identify ILI visits among a patient population of about 700,000 in Eastern Massachusetts. The percentage of total visits for ILI (“percent ILI”) in ESP, percent ILI in the Massachusetts Department of Public Health's sentinel surveillance system, and percentage of laboratory specimens submitted to participating Massachusetts laboratories that tested positive for influenza were compared for the period October 2007–September 2011. We calculated Spearman's correlation coefficients and compared ESP and sentinel surveillance systems qualitatively, in terms of simplicity, flexibility, data quality, acceptability, timeliness, and usefulness.Results. ESP and sentinel surveillance percent ILI always peaked within one week of each other. There was 80% correlation between the two and 71%–73% correlation with laboratory data. Sentinel surveillance percent ILI was higher than ESP percent ILI during influenza seasons. The amplitude of variation in ESP percent ILI was greatest for 5- to 49-year-olds and typically peaked for the 5- to 24-year-old age group before the others.Conclusions. The ESP system produces percent ILI data of similar quality to sentinel surveillance and offers the advantages of shifting disease reporting burden from clinicians to information systems, allowing tracking of disease by age group, facilitating efficient surveillance for very large populations, and producing consistent and timely reports.

Large linked database networks, like the US Food and Drug Administration’s Sentinel System, are being built for medical product surveillance. One use of these networks is for “near real-time” sequential database surveillance of prespecified medical product–adverse event pairs, which may result in a “safety signal” when a statistical excess risk is detected. Sequential database surveillance requires the investigator to manage surveillance in both information time (ie, how sample size accrues) and calendar time. Calendar time is important because people external to the surveillance population may be affected by the speed with which a safety signal is detected or ruled out. Optimal design and analysis aspects of sequential database surveillance are not well developed, but are gaining in importance as observational database networks grow. Using information time concepts, we show how to calculate sample sizes when performing sequential database surveillance, illustrating the relationships between statistical power, the time to detect a signal, and the maximum sample size for various true effect sizes. Then, using a vaccine example, we demonstrate a four-step planning process that allows investigators to translate information time into calendar time. Given the calendar time for surveillance, the process focuses on choosing observational database configurations consistent with the investigator’s preferences for timeliness and statistical power. Although the planning process emphasizes sample size considerations, the influence of secondary database attributes such as delay times, measurement error, and cost are also discussed. Appropriate planning allows the most efficient use of public health dollars dedicated to medical product surveillance efforts.

A distributed research network (DRN) of electronic health care databases, in which data reside behind the firewall of each data partner, can support a wide range of comparative effectiveness research (CER) activities. An essential component of a fully functional DRN is the capability to perform robust statistical analyses to produce valid, actionable evidence without compromising patient privacy, data security, or proprietary interests.

AbstractBackground:Passive reporting and laboratory testing delays may limit gastrointestinal (GI) disease outbreak detection. Healthcare systems routinely collect clinical data in electronic medical records (EMRs) that could be used for surveillance. This study's primary objective was to identify data streams from EMRs that may perform well for GI outbreak detection. Methods:Zip code-specific daily episode counts in 2009 were generated for 22 syndromic and laboratory-based data streams from Kaiser Permanente Northern California EMRs, covering 3.3 million members. Data streams included outpatient and inpatient diagnosis codes, antidiarrheal medication dispensings, stool culture orders, and positive microbiology tests for six GI pathogens. Prospective daily surveillance was mimicked using the space-time permutation scan statistic in single and multi-stream analyses, and space-time clusters were identified. Serotype relatedness was assessed for isolates in two Salmonellaclusters. Results:Potential outbreaks included a cluster of 18 stool cultures ordered over 5 days in one zip code and a Salmonellacluster in three zip codes over 9 days, in which at least five of six cases had the same rare serotype. In all, 28 potential outbreaks were identified using single stream analyses, with signals in outpatient diagnosis codes most common. Multi-stream analyses identified additional potential outbreaks and in one example, improved the timeliness of detection. Conclusions:GI disease-related data streams can be used to identify potential outbreaks when generated from EMRs with extensive regional coverage. This process can supplement traditional GI outbreak reports to health departments, which frequently consist of outbreaks in well-defined settings (e.g., day care centers and restaurants) with no laboratory-confirmed pathogen. Data streams most promising for surveillance included microbiology test results, stool culture orders, and outpatient diagnoses. In particular, clusters of microbiology tests positive for specific pathogens could be identified in EMRs and used to prioritize further testing at state health departments, potentially improving outbreak detection.

Objectives. We evaluated a real-time ambulatory care-based syndromic surveillance system in four metropolitan areas of the United States.Methods. Health-care organizations and health departments in California, Massachusetts, Minnesota, and Texas participated during 2007–2008. Syndromes were defined using International Classification of Diseases, Ninth Revision diagnostic codes in electronic medical records. Health-care organizations transmitted daily counts of new episodes of illness by syndrome, date, and patient zip code. A space-time permutation scan statistic was used to detect unusual clustering. Health departments followed up on e-mailed alerts. Distinct sets of related alerts (“signals”) were compared with known outbreaks or clusters found using traditional surveillance.Results. The 62 alerts generated corresponded to 17 distinct signals of a potential outbreak. The signals had a median of eight cases (range: 3–106), seven zip code areas (range: 1–88), and seven days (range: 3–14). Two signals resulted from true clusters of varicella; six were plausible but unconfirmed indications of disease clusters, six were considered spurious, and three were not investigated. The median investigation time per signal by health departments was 50 minutes (range: 0–8 hours). Traditional surveillance picked up 124 clusters of illness in the same period, with a median of six ill per cluster (range: 2–75). None was related to syndromic signals.Conclusions. The system was able to detect two true clusters of illness, but none was of public health interest. Possibly due to limited population coverage, the system did not detect any of 124 known clusters, many of which were small. The number of false alarms was reasonable.

A pentavalent, bovine-derived rotavirus vaccine (RotaTeq, Merck) was licensed in 2006 for use in infants. A previously licensed rotavirus vaccine was withdrawn due to elevated risk of intussusception. We prospectively evaluated the risk of intussusception and other pre-specified adverse events among RotaTeq recipients in the Vaccine Safety Datalink.

Rapid safety assessment of novel vaccines, especially those targeted against pandemic influenza, is a public health priority.

Methods using gambling teams and martingales are developed and applied to find formulae for the expected value and the generating function of the waiting time to observation of an element of a finite collection of patterns in a sequence generated by a two-state Markov chain of first, or higher, order.

Non-Hodgkin Lymphoma (NHL) incidence has risen dramatically over past decades, but the reasons for most of this increase are not known. Meat cooked well-done using high-temperature cooking techniques produces heterocyclic amines (HCAs) and polycyclic aromatic hydrocarbons (PAHs) such as benzo[a]pyrene (B[a]P). This study was conducted as a population-based case–control study in Iowa, Detroit, Seattle and Los Angeles and was designed to determine whether meat, meat-cooking methods, HCAs or PAHs from meat were associated with NHL risk. This study consisted of 458 NHL cases, diagnosed between 1998 and 2000, and 383 controls. Participants completed a 117-item food frequency questionnaire (FFQ), with graphical aids to assess the meat-cooking method and doneness level, which was linked to a HCA and B[a]P database. Logistic regression, comparing the fourth to the first quartile, found no association between red meat or processed meat intake and risk for NHL [odds ratio (OR) and 95% confidence interval (CI): 1.10 (0.67–1.81) and 1.18 (0.74–1.89), respectively]. A marginally significant elevated risk for NHL was associated with broiled meat [OR and 95% CI: 1.32 (0.99–1.77); P trend = 0.09], comparing those who consumed broiled meat with those who did not. The degree to which meat was cooked was not associated with the risk for NHL, although one of the HCAs, DiMeIQx (2-amino-3,4,8-trimethylimidazo[4,5-f]quinoxaline), was associated with an inverse risk. Fat intake was associated with a significantly elevated risk for NHL [OR and 95% CI: 1.60 (1.05–2.45); P trend = 0.12]; in contrast, animal protein was inversely associated with risk for NHL [OR and 95% CI: 0.39 (0.22–0.70); P trend = 0.004]. Overall, our study suggests that consumption of meat, whether or not it is well-done, does not increase the risk of NHL. Furthermore, neither HCAs nor B[a]P from meat increase the risk of NHL.

Abstract: Scan statistics are commonly used in biology, medicine, engineering and other fields where interest is in the probability of observing clusters of events in a window at an unknown location. Due to the dependent nature of the number of events in a large number of overlapping window locations, even approximate solutions for the simplest scan statistics may require elaborate calculations. We propose a new martingale method which allows one to approximate the distribution for a wide variety of scan statistics, including some for which analytical results are computationally infeasible.

Reported habits of red meat consumption, particularly red meat that has been cooked to the degree termed ‘well-done’, is a positive risk factor for colorectal cancer. Under high, pyrolytic temperatures, heterocyclic amines (HCA) and benzo[a]pyrene (BP) molecules can form inside and on the surface of red meat, respectively. These compounds are precursors that are metabolically converted to compounds known to act as mutagens and carcinogens in animal models, yet their role in human colorectal carcinogenesis remains to be clarified. We investigated whether intake of these compounds is associated with risk of colorectal adenoma in the context of a polyp-screening study conducted in Southern California. Using a database of individual HCAs and BP in meats of various types and subjected to specified methods and degrees of cooking, we estimated nanogram consumption of 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine, 2-amino-3,4,8-trimethylimidazo[4,5-f] quinoxaline, 2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline and benzo[a]pyrene (BP). We observed a 6% increased risk of large (>1 cm) adenoma per 10 ng/day consumption of BP [OR = 1.06 (95% CI, 1.00–1.12), P (trend) = 0.04]. A major source of BP is red meat exposed to a naked flame, as occurs during the barbecuing process. Consistent with this finding an incremental increase of 10 g of barbecued red meat per day was associated with a 29% increased risk of large adenoma [OR = 1.29 (95% CI, 1.02–1.63), P (trend) = 0.04]. Individuals in the top quintile of barbecued red meat intake were at increased risk of large adenoma [OR = 1.90 (95% CI, 1.04–3.45)], compared with never consuming barbecued red meat. The consumption of oven-broiled red meat was inversely related to adenoma risk compared with non-consumers [OR = 0.49 (95% CI, 0.28–0.85)]. We did not identify any association with consumption of individual HCAs and colorectal adenoma risk. These results support the hypothesis that BP contributes to colorectal carcinogenesis.

Meat cooked at high temperatures contains potential carcinogenic compounds, such as heterocyclic amines (HCAs) and polycyclic aromatic hydrocarbons (PAHs). Samples from a 2‐week controlled feeding study were used to examine the relationship between the intake of mutagenicity from meat fried at different temperatures and the levels of mutagenicity subsequently detected in urine, as well as the influence of the genotype of drug metabolizing enzymes on urinary mutagenicity. Sixty subjects consumed ground beef patties fried at low temperature (100°C) for 1 week, followed by ground beef patties fried at high temperature (250°C) the second week. Mutagenicity in the meat was assayed in Salmonella typhimuriumTA98 (+S9), and urinary mutagenicity was determined using Salmonella YG1024 (+S9). Genotypes for NAT1, NAT2, GSTM1, and UGT1A1were analyzed using blood samples from the subjects. Meat fried at 100°C was not mutagenic, whereas meat fried at 250°C was mutagenic (1023 rev/g). Unhydrolyzed and hydrolyzed urine samples were 22× and 131× more mutagenic, respectively, when subjects consumed red meat fried at 250°C compared with red meat fried at 100°C. We found that hydrolyzed urine was ∼8× more mutagenic than unhydrolyzed urine, likely due to the deconjugation of mutagens from glucuronide. The intake of meat cooked at high temperature correlated with the mutagenicity of unhydrolyzed urine (r = 0.32, P= 0.01) and hydrolyzed urine (r = 0.34, P= 0.008). Mutagenicity in unhydrolyzed urine was not influenced by NAT1, NAT2, or GSTM1genotypes. However, a UGT1A1*28polymorphism that reduced UGT1A1expression and conjugation modified the effect of intake of meat cooked at high temperature on mutagenicity of unhydrolyzed urine (Pfor interaction = 0.04). These mutagenicity data were also compared with previously determined levels of HCAs (measured as MeIQx, DiMeIQx, and PhIP) and polycyclic aromatic hydrocarbons (PAHs) in the meat, levels of HCAs in the urine, and CYP1A2 and NAT2 phenotypes. The levels of mutagenicity in the meat fried at low and high temperatures correlated with levels of HCAs, but not levels of PAHs, in the meat. Also, levels of mutagenicity in unhydrolyzed urine correlated with levels of MeIQx in unhydrolyzed urine (r = 0.36; P= 0.01), and the levels of mutagenicity of hydrolyzed urine correlated with levels of MeIQx (r = 0.34; P= 0.01) and PhIP (r = 0.43; P= 0.001) of hydrolyzed urine. Mutagenicity in unhydrolyzed urine was not influenced by either the CYP1A2 or NAT2 phenotype. The data from this study indicate that urinary mutagenicity correlates with mutagenic exposure from cooked meat and can potentially be used as a marker in etiological studies on cancer. Environ. Mol. Mutagen. 43:53–74, 2004. Published 2004 Wiley‐Liss, Inc.

Meat cooked at high temperatures contains potential carcinogenic compounds, such as heterocyclic amines (HCAs) and polycyclic aromatic hydrocarbons (PAHs). Samples from a 2-week controlled feeding study were used to examine the relationship between the intake of mutagenicity from meat fried at different temperatures and the levels of mutagenicity subsequently detected in urine, as well as the influence of the genotype of drug metabolizing enzymes on urinary mutagenicity. Sixty subjects consumed ground beef patties fried at low temperature (100°C) for 1 week, followed by ground beef patties fried at high temperature (250°C) the second week. Mutagenicity in the meat was assayed in Salmonella typhimurium TA98 (+S9), and urinary mutagenicity was determined using Salmonella YG1024 (+S9). Genotypes for NAT1, NAT2, GSTM1, and UGT1A1 were analyzed using blood samples from the subjects. Meat fried at 100°C was not mutagenic, whereas meat fried at 250°C was mutagenic (1023 rev/g). Unhydrolyzed and hydrolyzed urine samples were 22× and 131× more mutagenic, respectively, when subjects consumed red meat fried at 250°C compared with red meat fried at 100°C. We found that hydrolyzed urine was ~8× more mutagenic than unhydrolyzed urine, likely due to the deconjugation of mutagens from glucuronide. The intake of meat cooked at high temperature correlated with the mutagenicity of unhydrolyzed urine (r = 0.32, P = 0.01) and hydrolyzed urine (r = 0.34, P = 0.008). Mutagenicity in unhydrolyzed urine was not influenced by NAT1, NAT2, or GSTM1 genotypes. However, a UGT1A1*28 polymorphism that reduced UGT1A1 expression and conjugation modified the effect of intake of meat cooked at high temperature on mutagenicity of unhydrolyzed urine (P for interaction = 0.04). These mutagenicity data were also compared with previously determined levels of HCAs (measured as MeIQx, DiMeIQx, and PhIP) and polycyclic aromatic hydrocarbons (PAHs) in the meat, levels of HCAs in the urine, and CYP1A2 and NAT2 phenotypes. The levels of mutagenicity in the meat fried at low and high temperatures correlated with levels of HCAs, but not levels of PAHs, in the meat. Also, levels of mutagenicity in unhydrolyzed urine correlated with levels of MeIQx in unhydrolyzed urine (r = 0.36; P = 0.01), and the levels of mutagenicity of hydrolyzed urine correlated with levels of MeIQx (r = 0.34; P = 0.01) and PhIP (r = 0.43; P = 0.001) of hydrolyzed urine. Mutagenicity in unhydrolyzed urine was not influenced by either the CYP1A2 or NAT2 phenotype. The data from this study indicate that urinary mutagenicity correlates with mutagenic exposure from cooked meat and can potentially be used as a marker in etiological studies on cancer. Environ. Mol. Mutagen. 43:53–74, 2004. Published 2004 Wiley-Liss, Inc.

Heterocyclic amines (HCAs), and polycyclic aromatic hydrocarbons (PAHs), formed in temperature and time-dependent manners during cooking of meat, may increase the risk of certain cancers. As these compounds could be carcinogenic for the pancreas, we assessed meat intake, preparation methods, and doneness preferences as risk factors for exocrine pancreatic cancer. In a case-control study ( cases =193 , controls =674 ), subjects provided information on their usual meat intake and how it was cooked, e.g. fried, grilled or barbecued (BBQ), etc. Meat doneness preferences were measured using photographs that showed internal doneness and external brownness with a numerical scale. Data were analyzed with unconditional logistic regression. Odds ratios (ORs) increased with increased intake of grilled/BBQ red meat in an analysis adjusted for age, sex, smoking, education, race, and diabetes. Based on amount of BBQ meat consumed, the OR and 95% confidence interval (CI) for the fifth quintile relative to the reference group (quintiles 1 and 2) was 2.19 (1.4, 3.4). Findings were not substantively changed by further adjustment for calories, total fat, fruit and vegetables, or alcohol consumption (from a food frequency questionnaire (FFQ)). Other meat variables did not show statistically significant associations with risk nor did they substantively alter the findings for BBQ. These included total meat, processed meat, total red meat, total white meat, total broiled meat, total fried meat, or total meat cooked by means other than grilling. We conclude that grilled red meat intake is a risk factor for pancreatic cancer and that method of meat preparation in addition to total intake is important in assessing the effects of meat consumption in epidemiologic studies.

The recently published atlas of cancer mortality in the United States revealed that prostate cancer mortality rates were elevated among white men in the Northwest, the Rocky Mountain states, the north-central area, New England and the South Atlantic area, and among black men in the South Atlantic area. Here we determine whether the elevated regional rates were statistically different from rates in the rest of the country and whether the pattern can be explained by selected regional characteristics. A spatial scan statistic was applied to county-based mortality data from 1970 through 1989 to identify geographic clusters of the elevated rates for prostate cancer. Five clusters of elevated mortality were detected in white men (p < 0.005) and 3 in black men (p = 0.0001–0.056). For white men, the primary cluster was in the northwestern quadrant, followed by clusters in New England, the eastern part of the north-central area, the mid-Atlantic states and the South Atlantic area, whereas for black men the primary cluster was in the South Atlantic area, followed by clusters in Alabama and the eastern part of the north-central area. Further analyses of these clusters revealed several significant subclusters (p < 0.05). None of the selected demographic and socioeconomic factors, separately or collectively, accounted for the primary clusters in the U.S. white and black populations. The patterns observed could not be attributed to selected demographic or socioeconomic characteristics but should provide leads for further study into the risk factors and the medical or reporting practices that may contribute to geographic variation in mortality from prostate cancer. © 2002 Wiley-Liss, Inc.

To evaluate geographical variation of invasive and in situ breast cancer incidence rates using precise geographical coordinates for place of residence at diagnosis, latitude-longitude coordinates pertaining to 10,601 invasive and 1,814 in situ breast cancers for Connecticut women, 1991–95, were linked to US Census information on the 2,905State census block groups. A spatial scan statistic was used to detect geographic excess or deficits in incidence and test the statistical significance of results, without prior assumptions about the size or location of such areas. The age adjusted invasive cancer incidence rate was 165.3/100,000 women/year. The spatial scan statistic identified 3 places with significantly low incidence rates and 4 places where rates were significantly high. The most probable location of low incidence was rural northeastern Connecticut where risk of disease, relative to elsewhere around the state, was 0.70 (p = 0.0001); the most probable place of elevated incidence was north central Connecticut where a relative risk of 1.34 (p = 0.002) was observed. Incidence of in situ disease was estimated to be significantly high for north central Connecticut (RR = 1.84; p = 0.0001). Geographic differences of invasive and in situ breast cancer incidence were observed. Examining cancer events at the lowest available level of data aggregation is beneficial in highlighting localized rate variations. Such information may enable public health officials to target additional resources for promoting breast cancer screening to specific locations. © 2002 Wiley-Liss, Inc.

High red meat intake has been linked with an increased risk of colorectal cancer and adenomas. During high temperature cooking of red meats, heterocyclic amines (HCAs) are generated; however, to be carcinogenic, they must be metabolized by enzymes including cytochrome P450 1A2 (CYP1A2) and N-acetyltransferase 1 (NAT1) and/or N-acetyltransferase 2 (NAT2). We have conducted a clinic-based case–control study of colorectal adenomas that focused on assessment of exposure to HCAs (estimated by use of a HCA database and meat cooking module) and modification of these exposures by genetic factors. We have previously reported that intake of MeIQx was associated with an increased risk of colorectal adenomas overall association at 80th percentile, >27.00 ng/day odds ratio (OR) 2.68, 95 confidence interval (CI) 1.58–4.55. Here, we report our evaluation of whether variation in CYP1A2, NAT1 and/or NAT2 modify the association between HCAs and colorectal adenoma formation in 146 cases and 228 frequency-matched controls. The NAT110allele was associated with a nonsignificant increased risk of colorectal adenomas (OR 1.43; 95 CI 0.86–2.36). Further, when we analysed 2-amino-3,8-dimethylimidazo4,5-fquinoxaline (MeIQx) intake as a categorical variable, we observed a six-fold increase in adenoma risk among rapid NAT1 acetylators who consumed more than 27 ng a day (OR 6.50; 95 CI 2.16–19.7), whereas among slow NAT1 acetylators, the increase in risk was two-fold (OR 2.32; 95 CI 1.12–4.81). While suggestive, the results were not significantly different from each other on either an additive or multiplicative scale. In contrast, NAT2genotype and CYP1A2 and NAT2 hepatic activity measured by caffeine urinary metabolites were not associated with adenoma risk, although an increase in risk with rapid CYP1A2 activity could not be ruled out (OR 1.46; 95 CI 0.76–2.81). Moreover, there was no evidence that the effect of MeIQx was enhanced among subjects in any subgroup defined by variation in these measures. These results are compatible with the hypothesis that high HCA exposure is associated with an increased risk of colorectal adenomas, particularly in genetically susceptible subgroups. Further study of larger populations is needed to confirm and extend these observations.

Heterocyclic amines (HCAs), and polycyclic aromatic hydrocarbons (PAHs), formed in temperature and time-dependent manners during cooking of meat, may increase the risk of certain cancers. As these compounds could be carcinogenic for the pancreas, we assessed meat intake, preparation methods, and doneness preferences as risk factors for exocrine pancreatic cancer. In a case-control study ( cases =193 , controls =674 ), subjects provided information on their usual meat intake and how it was cooked, e.g. fried, grilled or barbecued (BBQ), etc. Meat doneness preferences were measured using photographs that showed internal doneness and external brownness with a numerical scale. Data were analyzed with unconditional logistic regression. Odds ratios (ORs) increased with increased intake of grilled/BBQ red meat in an analysis adjusted for age, sex, smoking, education, race, and diabetes. Based on amount of BBQ meat consumed, the OR and 95% confidence interval (CI) for the fifth quintile relative to the reference group (quintiles 1 and 2) was 2.19 (1.4, 3.4). Findings were not substantively changed by further adjustment for calories, total fat, fruit and vegetables, or alcohol consumption (from a food frequency questionnaire (FFQ)). Other meat variables did not show statistically significant associations with risk nor did they substantively alter the findings for BBQ. These included total meat, processed meat, total red meat, total white meat, total broiled meat, total fried meat, or total meat cooked by means other than grilling. We conclude that grilled red meat intake is a risk factor for pancreatic cancer and that method of meat preparation in addition to total intake is important in assessing the effects of meat consumption in epidemiologic studies.

Spatial filters have been used as an easy and intuitive way to create smoothed disease maps. Birth weight data from New York State for 1994 and 1995 are used to compare the traditional filter type of fixed geographical size with a filter size of constant or nearly constant population size. The latter are more appropriate for mapping disease in geographic areas with widely varying population density, such as New York State. Issues such as the choice of population size for the filter, the scale of smoothing, the ability to detect true spatial variation and the ability to smooth over random spatial noise are evaluated and discussed. Copyright © 2000 John Wiley & Sons, Ltd.

Spatial filters have been used as an easy and intuitive way to create smoothed disease maps. Birth weight data from New York State for 1994 and 1995 are used to compare the traditional filter type of fixed geographical size with a filter size of constant or nearly constant population size. The latter are more appropriate for mapping disease in geographic areas with widely varying population density, such as New York State. Issues such as the choice of population size for the filter, the scale of smoothing, the ability to detect true spatial variation and the ability to smooth over random spatial noise are evaluated and discussed. Copyright © 2000 John Wiley & Sons, Ltd.

Clinical trials are often underpowered to detect serious but rare adverse events of a new medication. We applied a novel data mining tool to detect potential adverse events of canagliflozin, the first sodium glucose co‐transporter 2 (SGLT2 inhibitor) in the United States, using real‐world data from shortly after its market entry and before public awareness of its potential safety concerns. In a U. S. commercial claims dataset (29 March 2013–30 Sept 2015), two pairwise cohorts of patients over 18 years of age with type 2 diabetes (T2D) who were newly dispensed canagliflozin or an active comparator, that is a dipeptidyl peptidase 4 inhibitor (DPP4) or a glucagon‐like peptide 1 receptor agonist (GLP1), were identified and propensity score‐matched. We used variable ratio matching with up to four people receiving a DPP4 or GLP1 for each person receiving canagliflozin. We identified potential safety signals using a hierarchical tree‐based scan statistic data mining method with the hierarchical outcome tree constructed based on international classification of disease coding. We screened for incident adverse events where there were more outcomes observed among canagliflozin vs. comparator initiators than expected by chance, after adjusting for multiple testing. We identified two pairwise propensity score variable ratio matched cohorts of 44,733 canagliflozin vs. 99,458 DPP4 initiators, and 55,974 canagliflozin vs. 74,727 GLP1 initiators. When we screened inpatient and emergency room diagnoses, diabetic ketoacidosis was the only severe adverse event associated with canagliflozin initiation with p< .05 in both cohorts. When outpatient diagnoses were also considered, signals for female and male genital infections emerged in both cohorts (p< .05). In a large population‐based study, we identified known but no other adverse events associated with canagliflozin, providing reassurance on its safety among adult patients with T2D and suggesting the tree‐based scan statistic method is a useful post‐marketing safety monitoring tool for newly approved medications. Clinical trials are often underpowered to detect serious but rare adverse events of a new medication. We applied a novel data mining tool to detect potential adverse events of canagliflozin, the first SGLT2 inhibitor in the United States, using real‐world data from shortly after its market entry and before public awareness of its potential safety concerns. In a large population‐based study, we identified known but no other adverse events associated with canagliflozin, providing reassurance on its safety among adult patients with T2D and suggesting the tree‐based scan statistic is a useful post‐marketing safety monitoring tool for newly approved medications.

Summary. The Knox method, as well as other tests for space‐time interaction, are biased when there are geographical population shifts, i.e., when there are different percent population growths in different regions. In this paper, the size of the population shift bias is investigated for the Knox test, and it is shown that it can be a considerable problem. A Monte Carlo method for constructing unbiased space‐time interaction tests is then presented and illustrated on the Knox test as well as for a combined Knox test. Practical implications are discussed in terms of the interpretation of past results and the design of future studies.

Incidence patterns, trends, and spatial and/or temporal clustering of childhood brain tumors were analyzed in the population-based national cancer registry of Sweden. Temporal trends were analyzed by a logistic regression procedure in which the average annual percentages of change in incidence rates and the corresponding 95% confidence intervals (CIs) were calculated. Spatial and/or temporal clustering were investigated by using a geographic information system and analyzed with a modified version of the Knox test and a spatial scan statistic. Primary brain tumors in 1223 children ages 0–15 years were registered during 1973–1992. In 80% of cases, the tumor was classified as malignant. Conclusive histopathology was classified in 1142 cases. The age-adjusted incidence rate for all subtypes of brain tumors was 35.9 cases per million children, and for malignant brain tumors 28.6. A statistically significant increasing temporal trend was observed for the group of malignant brain tumors as a whole (P = 0.0001) and the astrocytoma subgroup (P = 0.0001). The annual average increases were 2.6% (95% CI = 1.5–3.8) and 3.0%, respectively (95% CI = 1.6–4.4). The increase in astrocytoma cases was significantly larger for girls than for boys (P = 0.021) and was most striking for girls ages 6–15 years, with an annual average increase of 4.7%. Rates had not increased for the primitive neuroectodermal tumor (PNET)/medulloblastoma or ependymoma subgroups. The geographic distribution of astrocytoma cases was homogenous. No statistically significant space–time interaction or local clusters in space and/or time were found for astrocytomas only or when astrocytomas were grouped with PNETs/medulloblastomas and ependymomas. The results show statistically increased incidence rates of childhood astroglial tumors, predominantly for girls, in Sweden during the period 1973–1992, but no clustering in space or time. Cancer 1999;85:2077–90. © 1999 American Cancer Society.

The scan statistic is commonly used to test if a one dimensional point process is purely random, or if any clusters can be detected. Here it is simultaneously extended in three directions:(i) a spatial scan statistic for the detection of clusters in a multi-dimensional point process is proposed, (ii) the area of the scanning window is allowed to vary, and (iii) the baseline process may be any inhomogeneous Poisson process or Bernoulli process with intensity pro-portional to some known function. The main interest is in detecting clusters not explained by the baseline process. These methods are illustrated on an epidemiological data set, but there are other potential areas of application as well.

Objective: Some epidemiological studies suggest that diets high in fat, saturated fat, or cholesterol are associated with increased risk of lung cancer. Since meat consumption is correlated with the intake of saturated fat and cholesterol, we investigated the role of meat intake and cooking practices in relation to lung cancer risk. Methods: A population-based case-control study of both non-smoking and smoking women was conducted in Missouri. A 100-item food frequency questionnaire (FFQ) with detailed questions on meat consumption was completed by 593 cases and 623 frequency matched controls. We estimated quantity of meat eaten (grams/day) according to cooking method, and doneness level. Odds ratios (ORs) and 95% confidence intervals (C.I.s) were calculated using logistic regression. Multivariate models included age, packyears of smoking, body mass index (BMI, kg/m2), education, and intake of calories, fat, fruit/fruit juices, and vegetables. Results: When comparing 90th and 10th percentiles, lung cancer risk increased for total meat consumption (OR=1.6, C.I. 1.1-2.4), red meat (OR=1.8, C.I., 1.2-2.7), well-done red meat (OR=1.5, C.I.s, 1.1-2.1) and fried red meat (OR=1.5, C.I., 1.1-2.0). The odds ratios for 5th vs. 1st quintiles using the categorical variable for well-done red meat and fried red meat were essentially the same as reported above; however, the increase in risk was associated mainly with the 5th quintile. The ORs for a 10-gram increase in consumption were, 1.04 for total meat, 1.06 for red meat, 1.08 for well done red meat, and 1.09 for fried red meat. Conclusions: Consumption of red meat, especially fried and/or well-done red meat, was associated with increased risk of lung cancer.

Abstract: In a population-based case-control study of women in Missouri (United States), most of whom were smokers, we obtained information on adult diet to evaluate the effects of dietary fats in relation to lung cancer risk. All newly diagnosed, primary lung cancer cases among women 35 to 84 years of age reported to the Missouri Cancer Registry from 1 January 1993 to 31 January1994 were invited to participate, as were population-based controls. The analysis focused on interviews obtained from 624 controls and 587 cases. In-person interviews were obtained from 99.0 percent of controls and 60.6percent of cases. Age and energy-adjusted relative risks suggested a direct relation between risk of lung cancer and intake of dietary fats (e.g., total fat, saturated fat) and frequency of meat consumption. After adjusting for confounders, dietary fats were no longer associated with risk, but the adverse effect of frequent consumption of meat persisted. Risk was elevated about 90 percent (95 per cent confidence interval = 1.2-3.0) among women in the highest quintile of red meat intake compared with those in the lowest quintile. Risk estimates associated with red meat consumption, however, were dependent on interview status; the effect was restricted to cases whose dietary information was provided by proxy. In summary, after adjusting for potential confounders and removing data obtained from proxy respondents, dietary fats and consumption of red meat were not associated with lung cancer risk among women in Missouri.

The EMPA‐REG OUTCOME trial showed that empagliflozin reduced the risk of cardiovascular death and hospitalization for heart failure (HHF) in diabetic patients with cardiovascular disease. EMPRISE is a study programme on the effectiveness, safety and healthcare utilization of empagliflozin in routine care, leveraging real‐world data from two commercial and one federal US data sources from 2014 to 2019. To describe rationale and design of EMPRISE, assess ability to minimize confounding and evaluate the time to reach sufficient statistical power for a key study outcome, HHF, using baseline information from the first year of EMPRISE. In 3 claims data sets, we identified a 1:1 propensity score (PS)‐matched cohort of diabetic patients ≥18 years initiating empagliflozin or a dipeptidyl peptidase‐4 inhibitor (DPP4i), resulting in 6643 total pairs. The PS model included >140 baseline covariates. We measured covariate balance via standardized differences (SD) and postmatching c‐statistic. We computed the incidence rate (IR) of HHF, predicted exposure accrual over time and calculated expected power. After PS matching, patient characteristics were balanced with SD <0.1 and c‐statistic between 0.54 and 0.59. The population IR of HHF was 4.4 per 1000 person‐years using a specific HHF definition and 14.8 using a broader HHF definition. In our projection, 80%‐powered analyses would require a minimum of 169 HHF events, expected to accumulate by year 3 (specific definition) or year 2 (broader definition). Baseline information from EMPRISE provided evidence of solid confounding control and adequate exposure accrual with expected powered analyses for the primary outcomes. The EMPagliflozin compaRative effectIveness and SafEty (EMPRISE) programme of studies aims to assess the comparative effectiveness, safety and impact on healthcare utilization of empagliflozin, based on real‐world data from two commercial and Medicare databases from 2014 to 2019 in the United States. In three claims data sets, we identified a 1:1 propensity score‐matched cohort of diabetic patients ≥18 years initiating empagliflozin or a dipeptidyl peptidase‐4 inhibitor from August 2014 to September 2015 (the first year of EMPRISE), resulting in 6643 total pairs. We demonstrated solid confounding control, as measured by the superior balance across treatment groups in a wide range of potential confounding factors and their proxies after propensity score matching and confirmed that we will reach adequate patient accrual rates for the achievement of powered interim analyses for all primary outcomes.

Sequential analysis can be used as an early warning system about potential unintended consequences of health policy decisions, generating follow-up investigations, but it should not be used as causal evidence.

Supplemental Digital Content is available in the text.

In a recent BMJarticle, the authors conducted a meta-analysis to compare estimated treatment effects from randomized trials with those derived from observational studies based on routinely collected data (RCD). They calculated a pooled relative odds ratio (ROR) of 1.31 (95 % confidence interval [CI]: 1.03–1.65) and concluded that RCD studies systematically over-estimated protective effects. However, their meta-analysis inverted results for some clinical questions to force all estimates from RCD to be below 1. We evaluated the statistical properties of this pooled ROR, and found that the selective inversion rule employed in the original meta-analysis can positively bias the estimate of the ROR. We then repeated the random effects meta-analysis using a different inversion rule and found an estimated ROR of 0.98 (0.78–1.23), indicating the ROR is highly dependent on the direction of comparisons. As an alternative to the ROR, we calculated the observed proportion of clinical questions where the RCD and trial CIs overlap, as well as the expected proportion assuming no systematic difference between the studies. Out of 16 clinical questions, 50 % CIs overlapped for 8 (50 %; 25 to 75 %) compared with an expected overlap of 60 % assuming no systematic difference between RCD studies and trials. Thus, there was little evidence of a systematic difference in effect estimates between RCD and RCTs. Estimates of pooled RORs across distinct clinical questions are generally not interpretable and may be misleading.