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2. The satisfactory growth and development at 2 years of age of the INTERGROWTH-21st Fetal Growth Standards cohort support its appropriateness for constructing international standards

Author

Villar, José, Ismail, Leila Cheikh, Urias, Eleonora Staines, Giuliani, Francesca, Ohuma, Eric O, Victora, Cesar G, Papageorghiou, Aris T, Altman, Douglas G, Garza, Cutberto, Barros, Fernando C, Puglia, Fabien, Ochieng, Roseline, Jaffer, Yasmin A, Noble, Julia A, Bertino, Enrico, Purwar, Manorama, Pang, Ruyan, Lambert, Ann, Chumlea, Cameron, Stein, Alan, Fernandes, Michelle, Bhutta, Zulfiqar A, Kennedy, Stephen H, Katz, M, Bhan, MK, Garza, C, Zaidi, S, Langer, A, Rothwell, PM, Weatherall, D, Bhutta, ZA, Villar, J, Kennedy, S, Altman, DG, Barros, FC, Bertino, E, Burton, F, Carvalho, M, Ismail, L Cheikh, Chumlea, WC, Gravett, MG, Jaffer, YA, Lambert, A, Lumbiganon, P, Noble, JA, Pang, RY, Papageorghiou, AT, Purwar, M, Rivera, J, Victora, C, Shorten, M, Hoch, L, Knight, HE, Ohuma, EO, Cosgrove, C, Blakey, I, Urias, E Staines, Roseman, F, Kunnawar, N, Gu, SH, Wang, JH, Wu, MH, Domingues, M, Gilli, P, Juodvirsiene, L, Musee, N, Al-Jabri, H, Waller, S, Muninzwa, D, Yellappan, D, Carter, A, Reade, D, Miller, R, Salomon, L, Leston, A, Mitidieri, A, Al-Aamri, F, Paulsene, W, Sande, J, Al-Zadjali, WKS, Batiuk, C, Bornemeier, S, Dighe, M, Gaglioti, P, Jacinta, N, Jaiswal, S, Oas, K, Oberto, M, Olearo, E, Owende, MG, Shah, J, Sohoni, S, Todros, T, Venkataraman, M, Vinayak, S, Wang, L, Wilson, D, Wu, QQ, Zhang, Y, and Chamberlain, P

Subjects
Pediatric, Conditions Affecting the Embryonic and Fetal Periods, Infant Mortality, Clinical Research, Preterm, Low Birth Weight and Health of the Newborn, Nutrition, Prevention, Perinatal Period - Conditions Originating in Perinatal Period, 2.4 Surveillance and distribution, Aetiology, Reproductive health and childbirth, Good Health and Well Being, Brazil, Cephalometry, Child Development, China, Female, Fetal Development, Growth Charts, Health Status, Humans, India, Infant, Infant, Newborn, Italy, Kenya, Longitudinal Studies, Male, Motor Skills, Nutritional Status, Oman, Pregnancy, United Kingdom, United States, World Health Organization, International Fetal and Newborn Growth Consortium for the 21(st) Century (INTERGROWTH-21(st)), INTERGROWTH-21(st) fetal growth standards, development, postnatal growth, Paediatrics and Reproductive Medicine, Obstetrics & Reproductive Medicine
Abstract

BackgroundThe World Health Organization recommends that human growth should be monitored with the use of international standards. However, in obstetric practice, we continue to monitor fetal growth using numerous local charts or equations that are based on different populations for each body structure. Consistent with World Health Organization recommendations, the INTERGROWTH-21st Project has produced the first set of international standards to date pregnancies; to monitor fetal growth, estimated fetal weight, Doppler measures, and brain structures; to measure uterine growth, maternal nutrition, newborn infant size, and body composition; and to assess the postnatal growth of preterm babies. All these standards are based on the same healthy pregnancy cohort. Recognizing the importance of demonstrating that, postnatally, this cohort still adhered to the World Health Organization prescriptive approach, we followed their growth and development to the key milestone of 2 years of age.ObjectiveThe purpose of this study was to determine whether the babies in the INTERGROWTH-21st Project maintained optimal growth and development in childhood.Study designIn the Infant Follow-up Study of the INTERGROWTH-21st Project, we evaluated postnatal growth, nutrition, morbidity, and motor development up to 2 years of age in the children who contributed data to the construction of the international fetal growth, newborn infant size and body composition at birth, and preterm postnatal growth standards. Clinical care, feeding practices, anthropometric measures, and assessment of morbidity were standardized across study sites and documented at 1 and 2 years of age. Weight, length, and head circumference age- and sex-specific z-scores and percentiles and motor development milestones were estimated with the use of the World Health Organization Child Growth Standards and World Health Organization milestone distributions, respectively. For the preterm infants, corrected age was used. Variance components analysis was used to estimate the percentage variability among individuals within a study site compared with that among study sites.ResultsThere were 3711 eligible singleton live births; 3042 children (82%) were evaluated at 2 years of age. There were no substantive differences between the included group and the lost-to-follow up group. Infant mortality rate was 3 per 1000; neonatal mortality rate was 1.6 per 1000. At the 2-year visit, the children included in the INTERGROWTH-21st Fetal Growth Standards were at the 49th percentile for length, 50th percentile for head circumference, and 58th percentile for weight of the World Health Organization Child Growth Standards. Similar results were seen for the preterm subgroup that was included in the INTERGROWTH-21st Preterm Postnatal Growth Standards. The cohort overlapped between the 3rd and 97th percentiles of the World Health Organization motor development milestones. We estimated that the variance among study sites explains only 5.5% of the total variability in the length of the children between birth and 2 years of age, although the variance among individuals within a study site explains 42.9% (ie, 8 times the amount explained by the variation among sites). An increase of 8.9 cm in adult height over mean parental height is estimated to occur in the cohort from low-middle income countries, provided that children continue to have adequate health, environmental, and nutritional conditions.ConclusionThe cohort enrolled in the INTERGROWTH-21st standards remained healthy with adequate growth and motor development up to 2 years of age, which supports its appropriateness for the construction of international fetal and preterm postnatal growth standards.

Published
2018

4. The Adaptive designs CONSORT Extension (ACE) statement : a checklist with explanation and elaboration guideline for reporting randomised trials that use an adaptive design

Author

ACE Consensus Group, Dimairo, Munyaradzi, Pallmann, Philip, Wason, James, Todd, Susan, Jaki, Thomas, Julious, Steven A, Mander, Adrian P, Weir, Christopher J, Koenig, Franz, Walton, Marc K, Nicholl, Jon P, Coates, Elizabeth, Biggs, Katie, Hamasaki, Toshimitsu, Proschan, Michael A, Scott, John A, Ando, Yuki, Hind, Daniel, and Altman, Douglas G

Published
2020

8. Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations

Author

Greenland, Sander, Senn, Stephen J, Rothman, Kenneth J, Carlin, John B, Poole, Charles, Goodman, Steven N, and Altman, Douglas G

Subjects
Epidemiology, Health Sciences, Confidence Intervals, Data Interpretation, Statistical, Humans, Probability, Confidence intervals, Hypothesis testing, Null testing, P value, Power, Significance tests, Statistical testing, Public Health and Health Services
Abstract

Misinterpretation and abuse of statistical tests, confidence intervals, and statistical power have been decried for decades, yet remain rampant. A key problem is that there are no interpretations of these concepts that are at once simple, intuitive, correct, and foolproof. Instead, correct use and interpretation of these statistics requires an attention to detail which seems to tax the patience of working scientists. This high cognitive demand has led to an epidemic of shortcut definitions and interpretations that are simply wrong, sometimes disastrously so-and yet these misinterpretations dominate much of the scientific literature. In light of this problem, we provide definitions and a discussion of basic statistics that are more general and critical than typically found in traditional introductory expositions. Our goal is to provide a resource for instructors, researchers, and consumers of statistics whose knowledge of statistical theory and technique may be limited but who wish to avoid and spot misinterpretations. We emphasize how violation of often unstated analysis protocols (such as selecting analyses for presentation based on the P values they produce) can lead to small P values even if the declared test hypothesis is correct, and can lead to large P values even if that hypothesis is incorrect. We then provide an explanatory list of 25 misinterpretations of P values, confidence intervals, and power. We conclude with guidelines for improving statistical interpretation and reporting.

Published
2016

9. ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions

Author

Sterne, Jonathan Ac, Hernán, Miguel A, Reeves, Barnaby C, Savović, Jelena, Berkman, Nancy D, Viswanathan, Meera, Henry, David, Altman, Douglas G, Ansari, Mohammed T, Boutron, Isabelle, Carpenter, James R, Chan, An-Wen, Churchill, Rachel, Deeks, Jonathan J, Hróbjartsson, Asbjørn, Kirkham, Jamie, Jüni, Peter, Loke, Yoon K, Pigott, Theresa D, Ramsay, Craig R, Regidor, Deborah, Rothstein, Hannah R, Sandhu, Lakhbir, Santaguida, Pasqualina L, Schünemann, Holger J, Shea, Beverly, Shrier, Ian, Tugwell, Peter, Turner, Lucy, Valentine, Jeffrey C, Waddington, Hugh, Waters, Elizabeth, Wells, George A, Whiting, Penny F, and Higgins, Julian Pt

Subjects
Epidemiology, Health Sciences, Clinical Trials and Supportive Activities, Clinical Research, Prevention, Generic health relevance, Bias, Clinical Trials as Topic, Confounding Factors, Epidemiologic, Humans, Observational Studies as Topic, Pilot Projects, Risk, Statistics as Topic, Clinical Sciences, Public Health and Health Services, General & Internal Medicine, Biomedical and clinical sciences, Health sciences, Psychology
Abstract

Non-randomised studies of the effects of interventions are critical to many areas of healthcare evaluation, but their results may be biased. It is therefore important to understand and appraise their strengths and weaknesses. We developed ROBINS-I (“Risk Of Bias In Non-randomised Studies - of Interventions”), a new tool for evaluating risk of bias in estimates of the comparative effectiveness (harm or benefit) of interventions from studies that did not use randomisation to allocate units (individuals or clusters of individuals) to comparison groups. The tool will be particularly useful to those undertaking systematic reviews that include non-randomised studies.

Published
2016

11. Is the relationship among outcome variables shown in randomized trials?

Author

Schriger, David L, Cooper, Richelle J, Lopez-O’Sullivan, Ana, Wystrach, Carter, and Altman, Douglas G

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Clinical Research, Clinical Trials and Supportive Activities, Cross-Sectional Studies, Humans, Periodicals as Topic, Randomized Controlled Trials as Topic, Treatment Outcome, Journalology, Clinical trials, Reporting guidelines, Clinical outcomes, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, General & Internal Medicine, Clinical sciences, Epidemiology, Health services and systems
Abstract

BACKGROUND: Randomized controlled trials (RCTs) often have more than one primary outcome and frequently have secondary and harm outcomes. Comparison of outcomes between study arms is the primary focus of RCTs, but there are times when the relation between outcomes is important, such as determining whether an intermediate outcome and a clinical outcome have a strong association. We sought to determine how often reports of RCTs depict the relations among outcomes at the individual patient level and, for those studies that use composite outcomes, how often the relations between component elements are depicted. METHODS: We selected 20 general, specialty and subspecialty medical journals with high impact factors that publish original clinical research. We identified every RCT in the 2011 and 2012 issues and randomly selected 10 articles per journal. For each article we recorded the number of outcomes, the number of composite outcomes and how often the relations between outcomes or elements of composite outcomes were portrayed. RESULTS: All but 16 of the 200 RCTs had more than one outcome. Thus, outcomes could have been related in 92% of studies, but such relations were only reported in 2 (1%). A total of 33 (17%) investigations measured a composite outcome, 32 of which showed data for each component. None, however, showed cross-tabulation of the components. CONCLUSIONS: Readers are rarely shown the relation between outcomes. Mandatory posting of datasets or requirements for detailed appendices would allow readers to see these cross-tabulations, helping future investigators know which outcomes are redundant, which provide unique information and which are most responsive to changes in the independent variables. While not every relationship between outcomes requires depiction, at present such information is seldom portrayed.

Published
2015

14. Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD): Explanation and Elaboration. Translation into Russian

Author

Moons, Karel G.M., primary, Altman, Douglas G., additional, Reitsma, Johannes B., additional, Loannidis, John P.A., additional, Macaskill, Petra, additional, Steyerberg, Ewout W., additional, Vickers, Andrew J., additional, Ransohoff, David F., additional, and Collins, Gary S., additional

Published
2023
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15. CARE Guidelines for Case Reports: Explanation and Elaboration Document. Translation into Russian

Author

Riley, David S., primary, Barber, Melissa S., additional, Kienle, Gunver S., additional, Aronson, Jeffrey K., additional, Von Schoen-Angerer, Tido, additional, Tugwell, Peter, additional, Kiene, Helmut, additional, Helfand, Mark, additional, Altman, Douglas G., additional, Sox, Harold, additional, Werthmann, Paul G., additional, Moher, David, additional, Rison, Richard A., additional, Shamseer, Larissa, additional, Koch, Christian A., additional, Sun, Gordon H., additional, Hanaway, Patrick, additional, Sudak, Nancy L., additional, Kaszkin-Bettag, Marietta, additional, Carpenter, James E., additional, and Gagnier, Joel J., additional

Published
2023
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19. CARE guidelines for case reports: explanation and elaboration document

Author

Riley, David S., Barber, Melissa S., Kienle, Gunver S., Aronson, Jeffrey K., von Schoen-Angerer, Tido, Tugwell, Peter, Kiene, Helmut, Helfand, Mark, Altman, Douglas G., Sox, Harold, Werthmann, Paul G., Moher, David, Rison, Richard A., Shamseer, Larissa, Koch, Christian A., Sun, Gordon H., Hanaway, Patrick, Sudak, Nancy L., Kaszkin-Bettag, Marietta, Carpenter, James E., and Gagnier, Joel J.

Published
2017
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22. Accuracy in detecting inadequate research reporting by early career peer reviewers using an online CONSORT-based peer-review tool (COBPeer) versus the usual peer-review process: a cross-sectional diagnostic study

Author

Chauvin, Anthony, Ravaud, Philippe, Moher, David, Schriger, David, Hopewell, Sally, Shanahan, Daniel, Alam, Sabina, Baron, Gabriel, Regnaux, Jean-Philippe, Crequit, Perrine, Martinez, Valeria, Riveros, Carolina, Le Cleach, Laurence, Recchioni, Alessandro, Altman, Douglas G., and Boutron, Isabelle

Published
2019
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23. Prognostic factor research

Author

Riley, Richard D, additional, Moons, Karel GM, additional, Hayden, Jill A, additional, Sauerbrei, Willi, additional, and Altman, Douglas G, additional

Published
2019
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25. Prognostic model research

Author

Riley, Richard D, additional, Moons, Karel GM, additional, Debray, Thomas PA, additional, Snell, Kym IE, additional, Steyerberg, Ewout W, additional, Altman, Douglas G, additional, and Collins, Gary S, additional

Published
2019
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26. CONSORT 2010 raporu: randomize paralel grup çalışmalarının raporlanmasında güncellenmiş kılavuzlar

Author

Sunay, Didem, Şengezer, Tijen, Oral, Meltem, Aktürk, Zekeriya, Schulz, Kenneth F., Altman, Douglas G., and Moher, David

Subjects
ddc:610
Abstract

CONSORT (Çalışmaların Raporlanmasında Birleştirilmiş Standartlar) raporu randomize, kontrollü çalışmaların raporlamasının geliştirilmesinde tüm dünyada yaygın olarak kullanılmaktadır. Schulz ve arkadaşları, raporlama kılavuzunu yeni metodolojik kanıt ve birikmiş tecrübeye dayalı olarak güncelleyen en son sürüm CONSORT 2010’u tanımladılar. Randomize, kontrollü çalışmalar, uygun bir şekilde tasarlanıp, yürütüldüğünde ve raporlandığında sağlık hizmeti girişimlerini değerlendirmede altın standart yerine geçer. Ancak, metodolojik titizlik eksikliğinde randomize çalışmalar önyargılı sonuçlar verebilir (1). Yayınlanmış bir raporun okuyucuları, bir çalışmayı doğru olarak değerlendirmek için metodolojisi ve bulguları ile ilgili eksiksiz, tam ve net bilgilere ihtiyaç duyarlar. Ne yazık ki bu hassas bilgilerin net ve eksiksiz tanımlarını sağlamak birçok çalışma raporunun yazarları tarafından ihmal edildiği için değerlendirme girişimleri çoğu kez başarısız olmaktadır (2-4). Uygun raporlamadaki bu eksiklik 1996’da orijinal CONSORT (Çalışmaların Raporlanmasında Birleştirilmiş Standartlar) raporunun (5) ve 5 yıl sonraki revizyonunun geliştirilmesini teşvik etmiştir (6-8). Bu raporlar bazı randomize, kontrollü çalışmalar için raporlama kalitesini geliştirirken (9,10), birçok çalışma raporları hala yetersiz kalmaktadır (2). Ayrıca 2001’deki son revizyondan beri yeni metodolojik kanıt ve ek tecrübe birikmiştir. Bu nedenle 2001 raporunu güncellemek için bir CONSORT grup toplantısı düzenledik (6-8). Burada bu sürecin sonucunu, CONSORT 2010’u tanıtıyoruz.

Published
2023

30. CONSORT extension for reporting N-of-1 trials (CENT) 2015 Statement

Author

Altman, Douglas G., Bukutu, Cecilia, Clark, Jocalyn, Cogo, Elise, Gabler, Nicole B., Guyatt, Gordon, Kravitz, Richard, Janosky, Janine, Johnston, Bradley C., Li, Bob, Mahon, Jeff, Marles, Robin, Moher, David, Nikles, Jane, Sampson, Margaret, Schmid, Christopher H., Shadish, William R., Shamseer, Larissa, Tate, Robyn, Vohra, Sunita, and Zucker, Deborah R.

Published
2016
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37. Postnatal growth standards for preterm infants: the Preterm Postnatal Follow-up Study of the INTERGROWTH-21st Project

Author

Villar, José, Giuliani, Francesca, Bhutta, Zulfiqar A, Bertino, Enrico, Ohuma, Eric O, Ismail, Leila Cheikh, Barros, Fernando C, Altman, Douglas G, Victora, Cesar, Noble, Julia A, Gravett, Michael G, Purwar, Manorama, Pang, Ruyan, Lambert, Ann, Papageorghiou, Aris T, Ochieng, Roseline, Jaffer, Yasmin A, and Kennedy, Stephen H

Published
2015
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45. Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration. Translation in to Russian

Author

Moons, Karel G.M., primary, Altman, Douglas G., additional, Reitsma, Johannes B., additional, Loannidis, John P.A., additional, Macaskill, Petra, additional, Steyerberg, Ewout W., additional, Vickers, Andrew J., additional, Ransohoff, David F., additional, and Collins, Gary S., additional

Published
2022
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