Dataset Information

Co-occurring defect analysis: A platform for analyzing birth defect co-occurrence in registries.

ABSTRACT:

Background

Few studies have systematically evaluated birth defect co-occurrence patterns, perhaps, in part, due to the lack of software designed to implement large-scale, complex analytic methods.

Methods

We created an R-based platform, "co-occurring defect analysis" (CODA), designed to implement analyses of birth defect co-occurrence patterns in birth defect registries. CODA uses an established algorithm for calculating the observed-to-expected ratio of a given birth defect combination, accounting for the known tendency of birth defects to co-occur nonspecifically. To demonstrate CODA's feasibility, we evaluated the computational time needed to assess 2- to 5-way combinations of major birth defects in the Texas Birth Defects Registry (TBDR) (1999-2014). We report on two examples of pairwise patterns, defects co-occurring with trisomy 21 or with non-syndromic spina bifida, to demonstrate proof-of-concept.

Results

We evaluated combinations of 175 major birth defects among 206,784 infants in the TBDR. CODA performed efficiently in the data set, analyzing 1.5 million 5-way combinations in 18?hr. As anticipated, we identified large observed-to-expected ratios for the birth defects that co-occur with trisomy 21 or spina bifida.

Conclusions

CODA is available for application to birth defect data sets and can be used to better understand co-occurrence patterns. Co-occurrence patterns elucidated by using CODA may be helpful for identifying new birth defect associations and may provide etiological insights regarding potentially shared pathogenic mechanisms. CODA may also have wider applications, such as assessing patterns of additional types of co-occurrence patterns in other large data sets (e.g., medical records).

SUBMITTER: Benjamin RH

PROVIDER: S-EPMC7814855 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Co-occurring defect analysis: A platform for analyzing birth defect co-occurrence in registries.

Benjamin Renata H RH Yu Xiao X Navarro Sanchez Maria Luisa ML Chen Han H Mitchell Laura E LE Langlois Peter H PH Canfield Mark A MA Swartz Michael D MD Scheuerle Angela E AE Scott Daryl A DA Northrup Hope H Schaaf Christian P CP Ray Joseph W JW McLean Scott D SD Lupo Philip J PJ Agopian A J AJ

Birth defects research 20190716 18

<h4>Background</h4>Few studies have systematically evaluated birth defect co-occurrence patterns, perhaps, in part, due to the lack of software designed to implement large-scale, complex analytic methods.<h4>Methods</h4>We created an R-based platform, "co-occurring defect analysis" (CODA), designed to implement analyses of birth defect co-occurrence patterns in birth defect registries. CODA uses an established algorithm for calculating the observed-to-expected ratio of a given birth defect combi ...[more]

PMID: 31313535

Similar Datasets

Project description:BackgroundThe population-level landscape of co-occurring birth defects among infants without a syndromic diagnosis is not well understood.MethodsWe analyzed data from 40,771 infants with two or more major birth defects in the Texas Birth Defects Registry (TBDR; 1999-2014). We calculated adjusted observed-to-expected (O/E) ratios for all two, three, four, and five-way combinations of 138 major defects.ResultsAmong 530 patterns with the highest adjusted O/E ratios (top 5% of 10,595 patterns), 66% included only defects co-occurring within one organ system and 28% were suggestive of known patterns (e.g., midline developmental defects). Of the remaining patterns, the combination of defects with the highest O/E ratio (193.8) encompassed the diaphragm, spine, spleen, and heart defects. Fourteen patterns involved heart and spine defects with or without rib defects. Ten additional patterns primarily involved two hallmark components of VACTERL association (specifically, vertebral defects, anal atresia, cardiac defects, renal, or limb defects, but not tracheoesophageal fistula).ConclusionsOur analyses provide a description of the birth defect co-occurrence patterns in a multi-ethnic, population-based sample, and revealed several patterns of interest. This work complements prior work that has suggested etiologic connections between select defects (e.g., diaphragmatic hernia and heart and spleen anomalies; heart and spine defects).ImpactIn this large-scale, population-based study of birth defect co-occurrence patterns, we found several birth defect combinations of potential interest that warrant further investigation: congenital diaphragmatic hernia, heart, spine, and spleen defects and scimitar syndrome with vertebral defects. The majority of patterns of co-occurring defects observed more frequently than expected involved multiple defects within the same system and combinations suggestive of known associations. Nearly all of the top patterns (beyond the same system and those suggestive of known associations) involved organ systems that are components of the VACTERL association, with heart, spine, and rib defect patterns being the most common.

Project description:BackgroundDifferent approaches have been used in case-control studies to estimate maternal exposure to medications and the risk of birth defects. However, the performance of these approaches and how they affect the odds ratio (OR) estimates have not been evaluated using birth-defect surveillance programmes. The aim of this study was to evaluate the scope and limitations of three case-control approaches to assess the teratogenic risk of birth defects in mothers exposed to antiepileptic medications, insulin, or acetaminophen.Methodology/principal findingsWe studied 110,814 non-malformed newborns and 58,514 live newborns with birth defects registered by the Latin American Collaborative Study of Congenital Anomalies (ECLAMC) between 1967 and 2008. Four controls were randomly selected for each case in the same hospital and period, and three different control groups were used: non-malformed newborns (HEALTHY), malformed newborns (SICK), and a subgroup of SICK, only-exposed cases (OECA). Associations were evaluated using OR and Pearson's chi-square (P<0.01). There were no concordance correlations between the HEALTHY and OECA designs, and the average OR differences ranged from 3.0 to 11.5 for the three evaluated medicines. The overestimations observed for HEALTHY design were increased as higher OR values were given, with a high and statistically significant correlation between the difference and the mean. On the contrary, the concordance correlations obtained between the SICK and OECA designs were quite good, with no significant differences in the average risks.ConclusionsThe HEALTHY design estimates the true population OR, but shows a high rate of false-positive results presumably caused by differential misclassification bias. This bias decreases with the increase of the proportion of exposed controls. SICK and OECA odds ratios cannot be considered a direct estimate of the true population OR except under certain conditions. However, the SICK and OECA designs could provide practical information to generate hypotheses about potential teratogens.

Project description:IntroductionHypospadias, one of the most common male genital birth defects, occurs in 1 out of every 200 male births in the United States and is increasing in prevalence globally.ObjectiveThis study aimed to characterize the combinations of birth defects that co-occur with hypospadias more often than expected by chance, while accounting for the complex clustering patterns of congenital defects.Study designWe analyzed cases with hypospadias and at least one additional co-occurring defect from the Texas Birth Defect Registry born between 1999 and 2014. For each combination, we calculated adjusted observed-to-expected (O/E) ratios, using Co-Occurring Defect Analysis (CODA).ResultsAmong 16,442 cases with hypospadias and without known syndromes, 2,084 (12.7%) had at least one additional defect. Many of the birth defect combinations within the highest adjusted O/E ratios included cardiac, musculoskeletal, and additional urogenital defects. For example, a top combination with an adjusted O/E of 139.0 included renal agenesis and dysgenesis, reduction defects of the upper limb, and other anomalies of upper limb (including shoulder girdle). High adjusted O/E ratios were also observed in combinations that included defects outside of the urogenital developmental field. For instance, the combination with the highest O/E ratio included buphthalmos, and congenital cataract and lens anomalies (adjusted O/E ratio: 192.9). Similar results were obtained when we restricted our analyses to cases with second- or third-degree hypospadias.DiscussionMany combinations in the top results were expected (e.g., multiple urogenital defects); however, some combinations with seemingly unrelated patterns of defects may suggest the presence of some etiologic mechanisms yet to be identified.ConclusionIn summary, this study described patterns of co-occurring defect combinations with hypospadias that can inform further study and may provide insights for screening and diagnostic practices.

Project description:Although many cancer patients experience multiple concurrent symptoms, most studies have either focused on the analysis of single symptoms, or have used methods such as factor analysis that make a priori assumptions about how the data is structured. This article addresses both limitations by first visually exploring the data to identify patterns in the co-occurrence of multiple symptoms, and then using those insights to select and develop quantitative measures to analyze and validate the results.We used networks to visualize how 665 cancer patients reported 18 symptoms, and then quantitatively analyzed the observed patterns using degree of symptom overlap between patients, degree of symptom clustering using network modularity, clustering of symptoms based on agglomerative hierarchical clustering, and degree of nestedness of the symptoms based on the most frequently co-occurring symptoms for different sizes of symptom sets. These results were validated by assessing the statistical significance of the quantitative measures through comparison with random networks of the same size and distribution.The cancer symptoms tended to co-occur in a nested structure, where there was a small set of symptoms that co-occurred in many patients, and progressively larger sets of symptoms that co-occurred among a few patients.These results suggest that cancer symptoms co-occur in a nested pattern as opposed to distinct clusters, thereby demonstrating the value of exploratory network analyses to reveal complex relationships between patients and symptoms. The research also extends methods for exploring symptom co-occurrence, including methods for quantifying the degree of symptom overlap and for examining nested co-occurrence in co-occurrence data. Finally, the analysis also suggested implications for the design of systems that assist in symptom assessment and management. The main limitation of the study was that only one dataset was considered, and future studies should attempt to replicate the results in new data.

Dataset Information

Co-occurring defect analysis: A platform for analyzing birth defect co-occurrence in registries.

Background

Methods

Results

Conclusions

Publications

Co-occurring defect analysis: A platform for analyzing birth defect co-occurrence in registries.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets