Background

Patau syndrome, or Trisomy 13, is a condition where an infant is born with an extra chromosome. Chromosomes are small packages of genetic material responsible for inherited traits. They determine how an infant’s body forms and grows during pregnancy and how it will function after birth. Typically, an infant is born with 23 pairs of chromosomes, half from each parent. An infant with Patau syndrome has an extra copy of chromosome 13.[1] Patau syndrome is also referred to as Trisomy 13 because an infant with the condition has three copies of chromosome 13. The extra copy of chromosome 13 changes how the infant’s body and brain develops, causing severe intellectual disability and physical abnormalities. Babies with Patau syndrome often have defects in their heart, brain, or spinal cord, poorly developed eyes, extra fingers or toes, a cleft lip, and weak muscle tone. Usually the baby does not survive past birth; those that do often experience developmental delays and serious health problems. Due to the severity of these medical problems only 5-10% of babies with this condition live past their first year.[2] Many cases of Patau syndrome are diagnosed prenatally using ultrasounds that can detect commonly seen signs of Patau syndrome.[3]

Most cases of Patau syndrome are “spontaneous”; they occur when the mother’s eggs or father’s sperm cells are developing for no obvious reason. It is still unknown whether there are any environmental or genetic risk factors for the condition, but like other Trisomies mothers over 35 may be at greater risk of having a child with Patau syndrome.[4]

Epidemiology

Alaska Birth Defects Registry (ABDR) registers birth defects as reported from health care providers using International Classification of Disease (ICD) billing codes. The use of these ICD codes can lead to misclassification of diagnosed conditions. Prior to this report, all prevalence estimates were based on the number of unique children reported to ABDR with an ICD code representing a specified condition regardless of case confirmation status.

The estimates in this report were derived by conducting medical record review and case confirmation of a random sample of cases of the condition reported to ABDR. The confirmation probability from the sample was used to develop informed estimates of the actual diagnosed defect prevalence. See Defect prevalence calculation.

For explanations of table columns see Column descriptions.

Prevalence

Patau syndrome occurs in about 0.63 out of every 10,000 live births in the United States. This results in about 528 babies diagnosed with Patau syndrome each year.[5]

In Alaska, during 2007-2016, the prevalence of Patau syndrome was 0.4 per 10,000 live births.
Reports Defects Births Prevalence (95% CI)
Total 9 4.5 113183 0.4 (0.1, 0.9)
Notes: 95% CI = 95% Confidence Interval

Trend

Prevalence per 10,000 births of Patau syndrome during 2007-2016 by five-year moving averages, with 95% confidence interval band and Poisson estimated fitted line.
Reports Defects Births Prevalence (95% CI) Predicted Prevalence†
2007-2011 1.4 0.7 11337.4 0.6 (0, 4.2) 0.8
2008-2012 1.8 0.9 11361.8 0.8 (0, 4.5) 0.6
2009-2013 1.0 0.5 11365.0 0.4 (0, 3.9) 0.4
2010-2014 0.6 0.3 11380.8 0.3 (0, 3.6) 0.3
2011-2015 0.6 0.3 11345.4 0.3 (0, 3.6) 0.3
2012-2016 0.4 0.2 11299.2 0.2 (0, 3.6) 0.2
Notes: Each row is based on five-year moving averages; Prevalence reported per 10,000 live births; 95% CI=95% Confidence Interval

† Estimated rate based on Poisson model
The p-value test for trend detected a significant decrease in the number of live births with Patau syndrome during 2007-2016. See p-value estimate
Estimate Std. Error t value Pr(>|t|)
-0.27840 0.06877 -4.04802 0.01550

Regional Distribution

Distribution of Patau syndrome in Alaska by Public Health Region of maternal residence at the time of birth.A description of regional breakdowns can be found here. Data suppressed for # of reports < 6.
Reports Defects Births Prevalence (95% CI)
Anchorage - - 46323 -
Gulf Coast - - 7048 -
Interior - - 20523 -
Mat-Su - - 13587 -
Northern - - 7812 -
Southeast - - 7012 -
Southwest - - 10878 -
Notes:Prevalence reported per 10,000 live births; Data suppressed for # of reports < 6; 95% CI = 95% Confidence Interval

Demographics

Some subgroups may be more at risk for having a baby with Patau syndrome. This section provides the descriptive epidemiology of specified maternal, birth, and child characteristics identified from the birth certificate.

Reports Defects Births Prevalence (95% CI)
Sex
  Female - - 54900 -
  Male - - 58283 -
Birth weight (grams)
  <2500 - - 6582 -
  2500+ - - 106420 -
Maternal age
  12-19 - - 8664 -
  20-24 - - 30607 -
  25-29 - - 34376 -
  30-34 - - 25418 -
  35-39 - - 11311 -
  40+ - - 2778 -
Maternal race
  Alaska Native/American Indian - - 28829 -
  Asian/Pacific Islander - - 10598 -
  Black - - 4581 -
  White 7 3.5 67675 0.5 (0.2, 1.3)
Maternal education (years)
  <12 - - 10904 -
  12 - - 40057 -
  12+ - - 58944 -
Marital status
  Married - - 71658 0.4 (0.1, 1.2)
  Unmarried - - 41006 -
Maternal smoking use
  Reported smoking - - 15727 -
  Reported not smoking - - 95579 0.5 (0.2, 1.1)
Medicaid (mother or child)
  Medicaid - - 57258 0.6 (0.2, 1.5)
  non-Medicaid - - 55806 -
Father on birth certificate
  None - - 5634 -
  Present - - 107549 0.4 (0.1, 0.9)
Notes: Prevalence reported per 10,000 live births; Data suppressed for # of reports < 6; 95% CI = 95% Confidence Interval

Technical notes

Column descriptions

# Reports: Unless otherwise noted, the number of unique reports of the defect received by ABDR during the specified birth year(s). Each report represents a unique child with the specified defect.

# Defects: The estimated true number of reports that are diagnosed defects based on medical record review and case confirmation.

# Births: The number of live births among Alaskan residents that occurred in Alaska during the specified birth year(s).

Prevalence (95% CI): The estimated diagnosed prevalence of the condition and corresponding 95% Confidence Interval. (For information on how the defect prevalence was estimated see below).

Defect prevalence calculation

The estimated defect prevalence was calculated using a Bayesian approach based on the reported prevalence, PPV and 1-NPV (see formula below).

Through medical records review and case confirmation of a random sample of reported cases, the defect prevalence is calculated as:

\[PPV (Positive Predictive Value) = p(defect|report)\] \[NPV (Negative Predictive Value) = p(\overline{defect}|\overline{report})\]

\[p(defect) \approx [p(report)\cdot PPV]+[p(\overline{report})\cdot (1-NPV)]\]

Defect prevalence estimates are a more accurate estimation of the actual diagnosed prevalance of birth defects compared to the reported prevalance estimates in Alaska. ABDR obtains reports from medical providers using International Classification of Disease (ICD) codes that are extracted from individual systems which when aggregated may not reflect true diagnostics. Caution should be used when interpreting and comparing the reported prevalence estimates with national estimates.

See Data analysis methods for more information.

P-value estimate

To evaluate the trend over time and account for under/over-dispersion we constructed a quasi-Poisson regression model. This model assumes the variance is a linear function of the mean and models the estimated number of annual defects by year with a natural log (ln) offset of the annual births. P-values < 0.05 are considered significant, which indicates that the predicted slope is significantly different from a slope of zero.

Data suppression

For region and demographic data tables, values are suppressed based on the number of reports received during the observation period. Counts less than 6 are suppressed (as indicated by ‘-’ in the table). For regions or demographics with only one cell count suppressed a second is suppressed to eliminate the ability to back-calculate the estimate.

References

[1] NIH U.S. National Library of Medicine. Genetics Home Reference: Trisomy 13, https://ghr.nlm.nih.gov/condition/trisomy-13.pdf; 2017 [accessed 02.27.2017]

[2] NIH National Center for Advancing Translational Sciences. Genetic and Rare Diseases Information Center: Trisomy 13, https://rarediseases.info.nih.gov/diseases/7341/trisomy-13; 2015 [accessed 02.28.2017]

[3] Witters I, Van Robays J, Willekes C et al. Trisomy 12,18, 21, Triploidy and Turner syndrome: the 5T’s. Look at the hands. Facts, Views & Vision in ObGyn 2011; 3(1): 15-21.

[4] Loane M, Morris J et al. Twenty-year trends in the prevalence of Down syndrome and other trisomies in Europe: impact of maternal age and prenatal screening. European Journal of Human Genetics. 2013; 21: 27-33

[5] Centers for Disease Control and Prevention, Birth Defects Data and Statistics, https://www.cdc.gov/ncbddd/birthdefects/data.html; 2016 [accessed 02.27.2017]

Suggested Citation

State of Alaska Department of Health and Social Services, Division of Public Health, Section of Women’s, Children’s, and Family Health. Alaska Birth Defects Registry Condition Report: Trisomy 13, Alaska, 2007-2016. Updated July 23, 2020. Available at: http://rpubs.com/AK_ABDR/Trisomy13_07_16.

Contact

Alaska Birth Defects Registry (ABDR)
3601 C Street, Suite 358
Anchorage, AK 99503
(907) 269-3400 phone
(907) 754-3529 fax

Updated: July 23, 2020
Code source: R:\ABDR\Analysis_New\ABDR_CASECONF\cond_reports\Published_reports\Trisomy13_07_16.Rmd