The Distribution of Clinical Phenotypes of Preterm Birth Syndrome: Implications for Prevention | Global Health | JAMA Pediatrics | JAMA Network
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Liu  L, Johnson  HL, Cousens  S,  et al; Child Health Epidemiology Reference Group of WHO and UNICEF.  Global, regional, and national causes of child mortality: an updated systematic analysis for 2010 with time trends since 2000.  Lancet. 2012;379(9832):2151-2161.PubMedGoogle ScholarCrossref
Blencowe  H, Cousens  S, Oestergaard  MZ,  et al.  National, regional, and worldwide estimates of preterm birth rates in the year 2010 with time trends since 1990 for selected countries: a systematic analysis and implications.  Lancet. 2012;379(9832):2162-2172.PubMedGoogle ScholarCrossref
Barros  FC, Barros  AJ, Villar  J, Matijasevich  A, Domingues  MR, Victora  CG.  How many low birthweight babies in low- and middle-income countries are preterm?  Rev Saude Publica. 2011;45(3):607-616.PubMedGoogle ScholarCrossref
Organization  WH.  Born Too Soon: The Global Action Report on Preterm Birth. Geneva, Switzerland: World Health Organization; 2012.
Goldenberg  RL, Culhane  JF, Iams  JD, Romero  R.  Epidemiology and causes of preterm birth.  Lancet. 2008;371(9606):75-84.PubMedGoogle ScholarCrossref
Muglia  LJ, Katz  M.  The enigma of spontaneous preterm birth.  N Engl J Med. 2010;362(6):529-535.PubMedGoogle ScholarCrossref
Villar  J, Abalos  E, Carroli  G,  et al; World Health Organization Antenatal Care Trial Research Group.  Heterogeneity of perinatal outcomes in the preterm delivery syndrome.  Obstet Gynecol. 2004;104(1):78-87.PubMedGoogle ScholarCrossref
Romero  R, Espinoza  J, Kusanovic  JP,  et al.  The preterm parturition syndrome.  BJOG. 2006;113(suppl 3):17-42.PubMedGoogle ScholarCrossref
Chang  HH, Larson  J, Blencowe  H,  et al; Born Too Soon Preterm Prevention Analysis Group.  Preventing preterm births: analysis of trends and potential reductions with interventions in 39 countries with very high human development index.  Lancet. 2013;381(9862):223-234.PubMedGoogle ScholarCrossref
Kramer  MS, Papageorghiou  A, Culhane  J,  et al.  Challenges in defining and classifying the preterm birth syndrome.  Am J Obstet Gynecol. 2012;206(2):108-112.PubMedGoogle ScholarCrossref
Goldenberg  RL, Gravett  MG, Iams  J,  et al.  The preterm birth syndrome: issues to consider in creating a classification system.  Am J Obstet Gynecol. 2012;206(2):113-118.PubMedGoogle ScholarCrossref
Villar  J, Papageorghiou  AT, Knight  HE,  et al.  The preterm birth syndrome: a prototype phenotypic classification.  Am J Obstet Gynecol. 2012;206(2):119-123.PubMedGoogle ScholarCrossref
Villar  J, Altman  DG, Purwar  M,  et al; International Fetal and Newborn Growth Consortium for the 21st Century.  The objectives, design and implementation of the INTERGROWTH-21st Project.  BJOG. 2013;120(suppl 2):9-26, v.PubMedGoogle ScholarCrossref
Villar  J, Papageorghiou  AT, Pang  R,  et al; International Fetal and Newborn Growth Consortium for the 21st Century (INTERGROWTH-21(st)).  The likeness of fetal growth and newborn size across non-isolated populations in the INTERGROWTH-21(st) Project: the Fetal Growth Longitudinal Study and Newborn Cross-Sectional Study.  Lancet Diabetes Endocrinol. 2014;2(10):781-792.PubMedGoogle ScholarCrossref
Villar  J, Cheikh Ismail  L, Victora  CG,  et al; International Fetal and Newborn Growth Consortium for the 21st Century (INTERGROWTH-21st).  International standards for newborn weight, length, and head circumference by gestational age and sex: the Newborn Cross-Sectional Study of the INTERGROWTH-21st Project.  Lancet. 2014;384(9946):857-868.PubMedGoogle ScholarCrossref
Papageorghiou  AT, Kennedy  SH, Salomon  LJ,  et al; for the International Fetal and Newborn Growth Consortium for the 21st Century (INTERGROWTH-21st).  International standards for early fetal size and pregnancy dating based on ultrasound measurement of crown-rump length in the first trimester of pregnancy [published online July 8, 2014].  Ultrasound Obstet Gynecol. doi:10.1002/uog.13448.PubMedGoogle Scholar
Costeloe  KL, Hennessy  EM, Haider  S, Stacey  F, Marlow  N, Draper  ES.  Short term outcomes after extreme preterm birth in England: comparison of two birth cohorts in 1995 and 2006 (the EPICure studies).  BMJ. 2012;345:e7976.PubMedGoogle ScholarCrossref
Ohuma  EO, Hoch  L, Cosgrove  C,  et al; International Fetal and Newborn Growth Consortium for the 21st Century.  Managing data for the international, multicentre INTERGROWTH-21st Project.  BJOG. 2013;120(suppl 2):64-70, v.PubMedGoogle ScholarCrossref
de Onis  M, Onyango  AW, Van den Broeck  J, Chumlea  WC, Martorell  R.  Measurement and standardization protocols for anthropometry used in the construction of a new international growth reference.  Food Nutr Bull. 2004;25(1)(suppl):S27-S36.PubMedGoogle Scholar
Cheikh Ismail  L, Knight  HE, Bhutta  Z, Chumlea  WC; International Fetal and Newborn Growth Consortium for the 21st Century.  Anthropometric protocols for the construction of new international fetal and newborn growth standards: the INTERGROWTH-21st Project.  BJOG. 2013;120(suppl 2):42-47, v.PubMedGoogle ScholarCrossref
Cheikh Ismail  L, Knight  HE, Ohuma  EO, Hoch  L, Chumlea  WC; International Fetal and Newborn Growth Consortium for the 21st Century.  Anthropometric standardisation and quality control protocols for the construction of new, international, fetal and newborn growth standards: the INTERGROWTH-21st Project.  BJOG. 2013;120(suppl 2):48-55, v.PubMedGoogle ScholarCrossref
Bhutta  ZA, Giuliani  F, Haroon  A,  et al; International Fetal and Newborn Growth Consortium for the 21st Century.  Standardisation of neonatal clinical practice.  BJOG. 2013;120(suppl 2):56-63, v.PubMedGoogle ScholarCrossref
Banfield  JD, Raftery  AE.  Model-based Gaussian and non-Gaussian clustering.  Biometrics. 1993;49:803-821. doi:10.2307/2532201.Google ScholarCrossref
Meila  M, Heckerman  D.  An Experimental Comparison of Several Clustering and Initialization Methods: Microsoft Research Technical Report MSR-TR-98-06. Redmond, Washington: Microsoft Research; 1998.
SPSS. White paper - technical report: The SPSS TwoStep Cluster Component: a scalable component enabling more efficient customer segmentation. Accessed October 5, 2014.
Kent  P, Jensen  RK, Kongsted  A.  A comparison of three clustering methods for finding subgroups in MRI, SMS or clinical data: SPSS TwoStep Cluster analysis, Latent Gold and SNOB.  BMC Med Res Methodol. 2014;14:113.PubMedGoogle ScholarCrossref
Conry  MC, Morgan  K, Curry  P,  et al.  The clustering of health behaviours in Ireland and their relationship with mental health, self-rated health and quality of life.  BMC Public Health. 2011;11:692.PubMedGoogle ScholarCrossref
Helm  D, Eis  D.  Subgrouping outpatients of an environmental medicine unit using SCL-90-R and cluster analysis.  Int J Hyg Environ Health. 2007;210(6):701-713.PubMedGoogle ScholarCrossref
Rompré  PH, Daigle-Landry  D, Guitard  F, Montplaisir  JY, Lavigne  GJ.  Identification of a sleep bruxism subgroup with a higher risk of pain.  J Dent Res. 2007;86(9):837-842.PubMedGoogle ScholarCrossref
Pikwer  M, Nilsson  JA, Bergström  U, Jacobsson  LT, Turesson  C.  Early menopause and severity of rheumatoid arthritis in women older than 45 years.  Arthritis Res Ther. 2012;14(4):R190.PubMedGoogle ScholarCrossref
Kaufman  L, Rousseuy  PJ.  Finding Groups in Data: An Introduction to Cluster Analysis. Hoboken, NJ: John Wiley and Sons; 2005.
Iams  JD, Cebrik  D, Lynch  C, Behrendt  N, Das  A.  The rate of cervical change and the phenotype of spontaneous preterm birth.  Am J Obstet Gynecol. 2011;205(2):130.e1-6. PubMedGoogle ScholarCrossref
Kramer  MS, Platt  RW, Wen  SW,  et al; Fetal/Infant Health Study Group of the Canadian Perinatal Surveillance System.  A new and improved population-based Canadian reference for birth weight for gestational age.  Pediatrics. 2001;108(2):E35.PubMedGoogle ScholarCrossref
Morais  M, Mehta  C, Murphy  K,  et al.  How often are late preterm births the result of non-evidence based practices: analysis from a retrospective cohort study at two tertiary referral centres in a nationalised healthcare system.  BJOG. 2013;120(12):1508-1514.PubMedGoogle Scholar
Zeitlin  J, Szamotulska  K, Drewniak  N,  et al; Euro-Peristat Preterm Study Group.  Preterm birth time trends in Europe: a study of 19 countries.  BJOG. 2013;120(11):1356-1365.PubMedGoogle ScholarCrossref
Conde-Agudelo  A, Papageorghiou  AT, Kennedy  SH, Villar  J.  Novel biomarkers for the prediction of the spontaneous preterm birth phenotype: a systematic review and meta-analysis.  BJOG. 2011;118(9):1042-1054.PubMedGoogle ScholarCrossref
Original Investigation
March 2015

The Distribution of Clinical Phenotypes of Preterm Birth Syndrome: Implications for Prevention

Author Affiliations
  • 1Programa de Pós-Graduação em Saúde e Comportamento, Universidade Católica de Pelotas, Pelotas, Rio Grande do Sul, Brazil
  • 2Programa de Pós-Graduação em Epidemiologia, Universidade Federal de Pelotas, Pelotas, Rio Grande do Sul, Brazil
  • 3Nuffield Department of Obstetrics & Gynaecology and Oxford Maternal & Perinatal Health Institute, Green Templeton College, University of Oxford, Oxford, England
  • 4Department of Engineering Science, University of Oxford, Oxford, England
  • 5School of Public Health, Peking University, Beijing, China
  • 6Department of Obstetrics and Gynecology, Ohio State University, Columbus, Ohio
  • 7Department of Obstetrics and Gynecology, Columbia University, New York, New York
  • 8Department of Pediatrics and Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
  • 9Faculty of Health Sciences, Aga Khan University, Nairobi, Kenya
  • 10Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland
  • 11Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services, Detroit, Michigan
  • 12Department of Family and Community Health, Ministry of Health, Muscat, Sultanate of Oman
  • 13Dipartimento di Scienze Pediatriche e dell’Adolescenza, Cattedradi Neonatologia, Università degli Studi di Torino, Torino, Italy
  • 14University of Washington School of Medicine, Seattle
  • 15Centre for Statistics in Medicine, University of Oxford Botnar Research Centre, Oxford, England
  • 16Nagpur INTERGROWTH-21st Research Centre, Ketkar Hospital, Nagpur, India
  • 17Center for Perinatal Studies, Swedish Medical Center, Seattle, Washington
  • 18Center of Excellence in Women and Child Health, The Aga Khan University, Karachi, Pakistan
  • 19Center for Global Child Health, Hospital for Sick Children, Toronto, Ontario, Canada
JAMA Pediatr. 2015;169(3):220-229. doi:10.1001/jamapediatrics.2014.3040

Importance  Preterm birth has been difficult to study and prevent because of its complex syndromic nature.

Objective  To identify phenotypes of preterm delivery syndrome in the Newborn Cross-Sectional Study of the INTERGROWTH-21st Project.

Design, Setting, and Participants  A population-based, multiethnic, cross-sectional study conducted at 8 geographically demarcated sites in Brazil, China, India, Italy, Kenya, Oman, the United Kingdom, and the United States. A total of 60 058 births over a 12-month fixed period between April 27, 2009, and March 2, 2014. Of these, 53 871 had an ultrasonography estimate of gestational age, among which 5828 were preterm births (10.8%). Pregnancies were prospectively studied using a standardized data collection and online data management system. Newborns had anthropometric and clinical examinations using standardized methods and identical equipment and were followed up until hospital discharge.

Main Outcomes and Measures  The main study outcomes were clusters of preterm phenotypes and for each cluster, we analyzed signs of presentation at hospital admission, admission rates for neonatal intensive care for 7 days or more, and neonatal mortality rates.

Results  Twelve preterm birth clusters were identified using our conceptual framework. Eleven consisted of combinations of conditions known to be associated with preterm birth, 10 of which were dominated by a single condition. However, the most common single cluster (30.0% of the total preterm cases; n = 1747) was not associated with any severe maternal, fetal, or placental condition that was clinically detectable based on the information available; within this cluster, many cases were caregiver initiated. Only 22% (n = 1284) of all the preterm births occurred spontaneously without any of these severe conditions. Maternal presentation on hospital admission, newborn anthropometry, and risk for death before hospital discharge or admission for 7 or more days to a neonatal intensive care unit, none of which were used to construct the clusters, also differed according to the identified phenotypes. The prevalence of preterm birth ranged from 8.2% in Muscat, Oman, and Oxford, England, to 16.6% in Seattle, Washington.

Conclusions and Relevance  We identified 12 preterm birth phenotypes associated with different patterns of neonatal outcomes. In 22% of all preterm births, parturition started spontaneously and was not associated with any of the phenotypic conditions considered. We believe these results contribute to an improved understanding of this complex syndrome and provide an empirical basis to focus research on a more homogenous set of phenotypes.