CONSORT 2010 statement: extension checklist for reporting within person randomised trials.

Evidence shows that the quality of reporting of randomised controlled trials (RCTs) is not optimal. The lack of transparent reporting impedes readers from judging the reliability and validity of trial findings and researchers from extracting information for systematic reviews and results in research waste. The Consolidated Standards of Reporting Trials (CONSORT) statement was developed to improve the reporting of RCTs. Within person trials are used for conditions that can affect two or more body sites, and are a useful and efficient tool because the comparisons between interventions are within people. Such trials are most commonly conducted in ophthalmology, dentistry, and dermatology. The reporting of within person trials has, however, been variable and incomplete, hindering their use in clinical decision making and by future researchers. This document presents the CONSORT extension to within person trials. It aims to facilitate the reporting of these trials. It extends 16 items of the CONSORT 2010 checklist and introduces a modified flowchart and baseline table to enhance transparency. Examples of good reporting and evidence based rationale for CONSORT within person checklist items are provided.

The antepartum stillbirth syndrome: risk factors and pregnancy conditions identified from the INTERGROWTH-21st Project.

OBJECTIVES: To identify risk factors for antepartum stillbirth, including fetal growth restriction, among women with well-dated pregnancies and access to antenatal care. DESIGN: Population-based, prospective, observational study. SETTING: Eight international urban populations. POPULATION: Pregnant women and their babies enrolled in the Newborn Cross-Sectional Study of the INTERGROWTH-21st Project. METHODS: Cox proportional hazard models were used to compare risks among antepartum stillborn and liveborn babies. MAIN OUTCOME MEASURES: Antepartum stillbirth was defined as any fetal death after 16 weeks' gestation before the onset of labour. RESULTS: Of 60 121 babies, 553 were stillborn (9.2 per 1000 births), of which 445 were antepartum deaths (7.4 per 1000 births). After adjustment for site, risk factors were low socio-economic status, hazard ratio (HR): 1.6 (95% CI, 1.2-2.1); single marital status, HR 2.0 (95% CI, 1.4-2.8); age ≥40 years, HR 2.2 (95% CI, 1.4-3.7); essential hypertension, HR 4.0 (95% CI, 2.7-5.9); HIV/AIDS, HR 4.3 (95% CI, 2.0-9.1); pre-eclampsia, HR 1.6 (95% CI, 1.1-3.8); multiple pregnancy, HR 3.3 (95% CI, 2.0-5.6); and antepartum haemorrhage, HR 3.3 (95% CI, 2.5-4.5). Birth weight <3rd centile was associated with antepartum stillbirth [HR, 4.6 (95% CI, 3.4-6.2)]. The greatest risk was seen in babies not suspected to have been growth restricted antenatally, with an HR of 5.0 (95% CI, 3.6-7.0). The population-attributable risk of antepartum death associated with small-for-gestational-age neonates diagnosed at birth was 11%. CONCLUSIONS: Antepartum stillbirth is a complex syndrome associated with several risk factors. Although small babies are at higher risk, current growth restriction detection strategies only modestly reduced the rate of stillbirth. TWEETABLE ABSTRACT: International stillbirth study finds individual risks poor predictors of death but combinations promising.

Quality control of ultrasound for fetal biometry: results from the INTERGROWTH-21st Project.

OBJECTIVE: To assess a comprehensive package of ultrasound quality control in the Fetal Growth Longitudinal Study of the INTERGROWTH-21st Project, a large multicenter study of fetal growth. METHODS: Quality control (QC) measures were performed for 20 313 ultrasound scan images obtained prospectively from 4321 fetuses at 14-41 weeks' gestation in eight geographical locations. At the time of each ultrasound examination, three fetal biometric variables (head circumference (HC), abdominal circumference (AC) and femur length (FL)) were measured in triplicate on separately generated images. All measurements were taken in a blinded fashion. QC had two elements: (1) qualitative QC: visual assessment by sonographers at each study site of their images based on specific criteria, with 10% of images being re-assessed at the Oxford-based Ultrasound Quality Unit (compared using an adjusted kappa statistic); and (2) quantitative QC: assessment of measurement data by comparing the first, second and third measurements (intraobserver variability), remeasurement of caliper replacement in 10% (interobserver variability), both by Bland-Altman plots and plotting frequency histograms of the SD of triplicate measurements and assessing how many were above or below 2 SD of the expected distribution. The system allowed the sonographers' performances to be monitored regularly. RESULTS: A high level of agreement between self- and external scoring was demonstrated for all measurements (κ = 0.99 (95% CI, 0.98-0.99) for HC, 0.98 (95% CI, 0.97-0.99) for AC and 0.96 (95% CI, 0.95-0.98) for FL). Intraobserver 95% limits of agreement (LoA) of ultrasound measures for HC, AC and FL were ± 3.3%, ± 5.6% and ± 6.2%, respectively; the corresponding values for interobserver LoA were ± 4.4%, ± 6.0% and ± 5.6%. The SD distribution of triplicate measurements for all biometric variables showed excessive variability for three of 31 sonographers, allowing prompt identification and retraining. CONCLUSIONS: Qualitative and quantitative QC monitoring was feasible and highly reproducible in a large multicenter research study, which facilitated the production of high-quality ultrasound images. We recommend that the QC system we developed is implemented in future research studies and clinical practice. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.

International estimated fetal weight standards of the INTERGROWTH-21st Project.

OBJECTIVE: Estimated fetal weight (EFW) and fetal biometry are complementary measures used to screen for fetal growth disturbances. Our aim was to provide international EFW standards to complement the INTERGROWTH-21st Fetal Growth Standards that are available for use worldwide. METHODS: Women with an accurate gestational-age assessment, who were enrolled in the prospective, international, multicenter, population-based Fetal Growth Longitudinal Study (FGLS) and INTERBIO-21st Fetal Study (FS), two components of the INTERGROWTH-21st Project, had ultrasound scans every 5 weeks from 9-14 weeks' until 40 weeks' gestation. At each visit, measurements of fetal head circumference (HC), biparietal diameter, occipitofrontal diameter, abdominal circumference (AC) and femur length (FL) were obtained blindly by dedicated research sonographers using standardized methods and identical ultrasound machines. Birth weight was measured within 12 h of delivery by dedicated research anthropometrists using standardized methods and identical electronic scales. Live babies without any congenital abnormality, who were born within 14 days of the last ultrasound scan, were selected for inclusion. As most births occurred at around 40 weeks' gestation, we constructed a bootstrap model selection and estimation procedure based on resampling of the complete dataset under an approximately uniform distribution of birth weight, thus enriching the sample size at extremes of fetal sizes, to achieve consistent estimates across the full range of fetal weight. We constructed reference centiles using second-degree fractional polynomial models. RESULTS: Of the overall population, 2404 babies were born within 14 days of the last ultrasound scan. Mean time between the last scan and birth was 7.7 (range, 0-14) days and was uniformly distributed. Birth weight was best estimated as a function of AC and HC (without FL) as log(EFW) = 5.084820 - 54.06633 × (AC/100)3 - 95.80076 × (AC/100)3 × log(AC/100) + 3.136370 × (HC/100), where EFW is in g and AC and HC are in cm. All other measures, gestational age, symphysis-fundus height, amniotic fluid indices and interactions between biometric measures and gestational age, were not retained in the selection process because they did not improve the prediction of EFW. Applying the formula to FGLS biometric data (n = 4231) enabled gestational age-specific EFW tables to be constructed. At term, the EFW centiles matched those of the INTERGROWTH-21st Newborn Size Standards but, at < 37 weeks' gestation, the EFW centiles were, as expected, higher than those of babies born preterm. Comparing EFW cross-sectional values with the INTERGROWTH-21st Preterm Postnatal Growth Standards confirmed that preterm postnatal growth is a different biological process from intrauterine growth. CONCLUSIONS: We provide an assessment of EFW, as an adjunct to routine ultrasound biometry, from 22 to 40 weeks' gestation. However, we strongly encourage clinicians to evaluate fetal growth using separate biometric measures such as HC and AC, as well as EFW, to avoid the minimalist approach of focusing on a single value. © 2016 Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Systematic review of the methodological and reporting quality of case series in surgery.

BACKGROUND: Case series are an important and common study type. No guideline exists for reporting case series and there is evidence of key data being missed from such reports. The first step in the process of developing a methodologically sound reporting guideline is a systematic review of literature relevant to the reporting deficiencies of case series. METHODS: A systematic review of methodological and reporting quality in surgical case series was performed. The electronic search strategy was developed by an information specialist and included MEDLINE, Embase, Cochrane Methods Register, Science Citation Index and Conference Proceedings Citation index, from the start of indexing to 5 November 2014. Independent screening, eligibility assessments and data extraction were performed. Included articles were then analysed for five areas of deficiency: failure to use standardized definitions, missing or selective data (including the omission of whole cases or important variables), transparency or incomplete reporting, whether alternative study designs were considered, and other issues. RESULTS: Database searching identified 2205 records. Through the process of screening and eligibility assessments, 92 articles met inclusion criteria. Frequencies of methodological and reporting issues identified were: failure to use standardized definitions (57 per cent), missing or selective data (66 per cent), transparency or incomplete reporting (70 per cent), whether alternative study designs were considered (11 per cent) and other issues (52 per cent). CONCLUSION: The methodological and reporting quality of surgical case series needs improvement. The data indicate that evidence-based guidelines for the conduct and reporting of case series may be useful.

Ultrasound-based gestational-age estimation in late pregnancy.

OBJECTIVE: Accurate gestational-age (GA) estimation, preferably by ultrasound measurement of fetal crown-rump length before 14 weeks' gestation, is an important component of high-quality antenatal care. The objective of this study was to determine how GA can best be estimated by fetal ultrasound for women who present for the first time late in pregnancy with uncertain or unknown menstrual dates. METHODS: INTERGROWTH-21st was a large, prospective, multicenter, population-based project performed in eight geographically defined urban populations. One of its principal components, the Fetal Growth Longitudinal Study, aimed to develop international fetal growth standards. Each participant had their certain menstrual dates confirmed by first-trimester ultrasound examination. Fetal head circumference (HC), biparietal diameter (BPD), occipitofrontal diameter (OFD), abdominal circumference (AC) and femur length (FL) were measured every 5 weeks from 14 weeks' gestation until delivery. For each participant, a single, randomly selected ultrasound examination was used to explore all candidate biometric variables and permutations to build models to predict GA. Regression equations were ranked based upon minimization of the mean prediction error, goodness of fit and model complexity. An automated machine learning algorithm, the Genetic Algorithm, was adapted to evaluate > 64 000 potential polynomial equations as predictors. RESULTS: Of the 4607 eligible women, 4321 (94%) had a pregnancy without major complications and delivered a live singleton without congenital malformations. After other exclusions (missing measurements in GA window and outliers), the final sample comprised 4229 women. Two skeletal measures, HC and FL, produced the best GA prediction, given by the equation loge (GA) = 0.03243 × (loge (HC))2 + 0.001644 × FL × loge (HC) + 3.813. When FL was not available, the best equation based on HC alone was loge (GA) = 0.05970 × (loge (HC))2 + 0.000000006409 × (HC)3 + 3.3258. The estimated uncertainty of GA prediction (half width 95% interval) was 6-7 days at 14 weeks' gestation, 12-14 days at 26 weeks' gestation and > 14 days in the third trimester. The addition of FL to the HC model led to improved prediction intervals compared with using HC alone, but no further improvement in prediction was afforded by adding AC, BPD or OFD. Equations that included other measurements (BPD, OFD and AC) did not perform better. CONCLUSIONS: Among women initiating antenatal care late in pregnancy, a single set of ultrasound measurements combining HC and FL in the second trimester can be used to estimate GA with reasonable accuracy. We recommend this tool for underserved populations but considerable efforts should be implemented to improve early initiation of antenatal care worldwide. © 2016 Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

[Better Reporting of Interventions: Template for Intervention Description and Replication (TIDieR) Checklist and Guide]. / Die TIDieR Checkliste und Anleitung - ein Instrument für eine verbesserte Interventionsbeschreibung und Replikation.

Without a complete published description of interventions, clinicians and patients cannot reliably implement interventions that are shown to be useful, and other researchers cannot replicate or build on research findings. The quality of description of interventions in publications, however, is remarkably poor. To improve the completeness of reporting, and ultimately the replicability, of interventions, an international group of experts and stakeholders developed the Template for Intervention Description and Replication (TIDieR) checklist and guide. The process involved a literature review for relevant checklists and research, a Delphi survey of an international panel of experts to guide item selection, and a face-to-face panel meeting. The resultant 12-item TIDieR checklist (brief name, why, what (materials), what (procedure), who intervened, how, where, when and how much, tailoring, modifications, how well (planned), how well (actually carried out)) is an extension of the CONSORT 2010 statement (item 5) and the SPIRIT 2013 statement (item 11). While the emphasis of the checklist is on trials, the guidance is intended to apply across all evaluative study designs. This paper presents the TIDieR checklist and guide, with a detailed explanation of each item, and examples of good reporting. The TIDieR checklist and guide should improve the reporting of interventions and make it easier for authors to structure the accounts of their interventions, reviewers and editors to assess the descriptions, and readers to use the information.

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement.

Prediction models are developed to aid health-care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health-care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).

Obesity and the outcome of young breast cancer patients in the UK: the POSH study.

BACKGROUND: Obese breast cancer patients have a poorer prognosis than non-obese patients. We examined data from a large prospective cohort study to explore the associations of obesity with tumour pathology, treatment and outcome in young British breast cancer patients receiving modern oncological treatments. PATIENTS AND METHODS: A total of 2956 patients aged ≤40 at breast cancer diagnosis were recruited from 126 UK hospitals from 2001 to 2007. Height and weight were measured at registration. Tumour pathology and treatment details were collected. Follow-up data were collected at 6, 12 months, and annually. RESULTS: A total of 2843 eligible patients (96.2%) had a body mass index (BMI) recorded: 1526 (53.7%) were under/healthy-weight (U/H, BMI <25 kg/m(2)), 784 (27.6%) were overweight (ov, BMI ≥25 to <30), and 533 (18.7%) were obese (ob, BMI ≥30). The median tumour size was significantly higher in obese and overweight patients than U/H patients (Ob 26 mm versus U/H 20 mm, P < 0.001; Ov 24 mm versus U/H 20 mm, P < 0.001). Obese and overweight patients had significantly more grade 3 tumours (63.9% versus 59.0%, P = 0.048; Ov 63.6% versus U/H 59.0% P = 0.034) and node-positive tumours (Ob 54.6% versus U/H 49.0%, P = 0.027; Ov 54.2% versus U/H 49%, P = 0.019) than U/H patients. Obese patients had more ER/PR/HER2-negative tumours than healthy-weight patients (25.0% versus 18.3%, P = 0.001). Eight-year overall survival (OS) and distant disease-free interval (DDFI) were significantly lower in obese patients than healthy-weight patients [OS: hazard ratio (HR) 1.65, P < 0.001; DDFI: HR 1.44, P < 0.001]. Multivariable analyses adjusting for tumour grade, size, nodal, and HER2 status indicated that obesity was a significant independent predictor of OS and DDFI in patients with ER-positive disease. CONCLUSIONS: Young obese breast cancer patients present with adverse tumour characteristics. Despite adjustment for this, obesity still independently predicts DDFI and OS.

Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): the TRIPOD Statement.

BACKGROUND: Prediction models are developed to aid healthcare providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision-making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. METHODS: An extensive list of items based on a review of the literature was created, which was reduced after a web-based survey and revised during a 3-day meeting in June 2011 with methodologists, healthcare professionals and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. RESULTS: The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. CONCLUSION: The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. A complete checklist is available at http://www.tripod-statement.org.

Family history and outcome of young patients with breast cancer in the UK (POSH study).

BACKGROUND: Young patients presenting to surgical clinics with breast cancer are usually aware of their family history and frequently believe that a positive family history may adversely affect their prognosis. Tumour pathology and outcomes were compared in young British patients with breast cancer with and without a family history of breast cancer. METHODS: Prospective Outcomes in Sporadic versus Hereditary breast cancer (POSH) is a large prospective cohort study of women aged less than 41 years with breast cancer diagnosed and treated in the UK using modern oncological management. Personal characteristics, tumour pathology, treatment and family history of breast/ovarian cancer were recorded. Follow-up data were collected annually. RESULTS: Family history data were available for 2850 patients. No family history was reported by 65·9 per cent, and 34·1 per cent reported breast/ovarian cancer in at least one first- or second-degree relative. Patients with a family history were more likely to have grade 3 tumours (63·3 versus 58·9 per cent) and less likely to have human epidermal growth factor receptor 2-positive tumours (24·7 versus 28·8 per cent) than those with no family history. In multivariable analyses, there were no significant differences in distant disease-free intervals for patients with versus those without a family history, either for the whole cohort (hazard ratio (HR) 0·89, 95 per cent c.i. 0·76 to 1·03; P = 0·120) or when stratified by oestrogen receptor (ER) status (ER-negative: HR 0·80, 0·62 to 1·04, P = 0·101; ER-positive: HR 0·95, 0·78 to 1·15, P = 0·589). CONCLUSION: Young British patients presenting to breast surgical clinics with a positive family history can be reassured that this is not a significant independent risk factor for breast cancer outcome.

Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement.

Prediction models are developed to aid healthcare providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision-making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) initiative developed a set of recommendations for the reporting of studies developing, validating or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a web-based survey and revised during a 3-day meeting in June 2011 with methodologists, healthcare professionals and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study, regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement.

Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).

Ethnicity and outcome of young breast cancer patients in the United Kingdom: the POSH study.

BACKGROUND: Black ethnic groups have a higher breast cancer mortality than Whites. American studies have identified variations in tumour biology and unequal health-care access as causative factors. We compared tumour pathology, treatment and outcomes in three ethnic groups in young breast cancer patients treated in the United Kingdom. METHODS: Women aged ≤ 40 years at breast cancer diagnosis were recruited to the POSH national cohort study (MREC: 00/06/69). Personal characteristics, tumour pathology and treatment data were collected at diagnosis. Follow-up data were collected annually. Overall survival (OS) and distant relapse-free survival (DRFS) were assessed using Kaplan-Meier curves, and multivariate analyses were performed using Cox regression. RESULTS: Ethnicity data were available for 2915 patients including 2690 (91.0%) Whites, 118 (4.0%) Blacks and 87 (2.9%) Asians. Median tumour diameter at presentation was greater in Blacks than Whites (26.0 mm vs 22.0 mm, P=0.0103), and multifocal tumours were more frequent in both Blacks (43.4%) and Asians (37.0%) than Whites (28.9%). ER/PR/HER2-negative tumours were significantly more frequent in Blacks (26.1%) than Whites (18.6%, P=0.043). Use of chemotherapy was similarly high in all ethnic groups (89% B vs 88.6% W vs 89.7% A). A 5-year DRFS was significantly lower in Blacks than Asians (62.8% B vs 77.0% A, P=0.0473) or Whites (62.8 B% vs 77.0% W, P=0.0053) and a 5-year OS for Black patients, 71.1% (95% CI: 61.0-79.1%), was significantly lower than that of Whites (82.4%, 95% CI: 80.8-83.9%, W vs B: P=0.0160). In multivariate analysis, Black ethnicity had an effect on DRFS in oestrogen receptor (ER)-positive patients that is independent of body mass index, tumour size, grade or nodal status, HR: 1.60 (95% CI: 1.03-2.47, P=0.035). CONCLUSION: Despite equal access to health care, young Black women in the United Kingdom have a significantly poorer outcome than White patients. Black ethnicity is an independent risk factor for reduced DRFS particularly in ER-positive patients.

International standards for early fetal size and pregnancy dating based on ultrasound measurement of crown-rump length in the first trimester of pregnancy.

OBJECTIVES: There are no international standards for relating fetal crown-rump length (CRL) to gestational age (GA), and most existing charts have considerable methodological limitations. The INTERGROWTH-21(st) Project aimed to produce the first international standards for early fetal size and ultrasound dating of pregnancy based on CRL measurement. METHODS: Urban areas in eight geographically diverse countries that met strict eligibility criteria were selected for the prospective, population-based recruitment, between 9 + 0 and 13 + 6 weeks' gestation, of healthy well-nourished women with singleton pregnancies at low risk of fetal growth impairment. GA was calculated on the basis of a certain last menstrual period, regular menstrual cycle and lack of hormonal medication or breastfeeding in the preceding 2 months. CRL was measured using strict protocols and quality-control measures. All women were followed up throughout pregnancy until delivery and hospital discharge. Cases of neonatal and fetal death, severe pregnancy complications and congenital abnormalities were excluded from the study. RESULTS: A total of 4607 women were enrolled in the Fetal Growth Longitudinal Study, one of the three main components of the INTERGROWTH-21(st) Project, of whom 4321 had a live singleton birth in the absence of severe maternal conditions or congenital abnormalities detected by ultrasound or at birth. The CRL was measured in 56 women at < 9 + 0 weeks' gestation; these were excluded, resulting in 4265 women who contributed data to the final analysis. The mean CRL and SD increased with GA almost linearly, and their relationship to GA is given by the following two equations (in which GA is in days and CRL in mm): mean CRL = -50.6562 + (0.815118 × GA) + (0.00535302 × GA(2) ); and SD of CRL = -2.21626 + (0.0984894 × GA). GA estimation is carried out according to the two equations: GA = 40.9041 + (3.21585 × CRL(0.5) ) + (0.348956 × CRL); and SD of GA = 2.39102 + (0.0193474 × CRL). CONCLUSIONS: We have produced international prescriptive standards for early fetal linear size and ultrasound dating of pregnancy in the first trimester that can be used throughout the world.

Statistical considerations for the development of prescriptive fetal and newborn growth standards in the INTERGROWTH-21st Project.

The INTERGROWTH-21(st) Project has in its mandate to develop prescriptive standards for fetal, neonatal and preterm post-neonatal growth. The project comprises three components: the Fetal Growth Longitudinal Study (FGLS), the Preterm Postnatal Follow-up Study (PPFS), and the Newborn Cross-Sectional Study (NCSS). We consider here the statistical aspects of the three components as they relate to the construction of these standards, in particular the sample size, and outline the principles that will guide the planned main analyses.

Standardisation and quality control of ultrasound measurements taken in the INTERGROWTH-21st Project.

Meticulous standardisation and ongoing monitoring of adherence to measurement protocols during data collection are essential to ensure consistency and to minimise systematic error in multicentre studies. Strict ultrasound fetal biometric measurement protocols are used in the INTERGROWTH-21(st) Project so that data of the highest quality from different centres can be compared and potentially pooled. A central Ultrasound Quality Unit (USQU) has been set up to oversee this process. After initial training and standardisation, the USQU monitors the performance of all ultrasonographers involved in the project by continuously assessing the quality of the images and the consistency of the measurements produced. Ultrasonographers are identified when they exceed preset maximum allowable differences. Corrective action is then taken in the form of retraining or simply advice regarding changes in practice. This paper describes the procedures used, which can form a model for research settings involving ultrasound measurements.

The objectives, design and implementation of the INTERGROWTH-21st Project.

INTERGROWTH-21(st) is a multicentre, multiethnic, population-based project, being conducted in eight geographical areas (Brazil, China, India, Italy, Kenya, Oman, UK and USA), with technical support from four global specialised units, to study growth, health and nutrition from early pregnancy to infancy. It aims to produce prescriptive growth standards, which conceptually extend the World Health Organization (WHO) Multicentre Growth Reference Study (MGRS) to cover fetal and newborn life. The new international standards will describe: (1) fetal growth assessed by clinical and ultrasound measures; (2) postnatal growth of term and preterm infants up to 2 years of age; and (3) the relationship between birthweight, length and head circumference, gestational age and perinatal outcomes. As the project has selected healthy cohorts with no obvious risk factors for intrauterine growth restriction, these standards will describe how all fetuses and newborns should grow, as opposed to traditional charts that describe how some have grown at a given place and time. These growth patterns will be related to morbidity and mortality to identify levels of perinatal risk. Additional aims include phenotypic characterisation of the preterm and impaired fetal growth syndromes and development of a prediction model, based on multiple ultrasound measurements, to estimate gestational age for use in pregnant women without access to early/frequent antenatal care.

Managing data for the international, multicentre INTERGROWTH-21st Project.

The INTERGROWTH-21(st) Project data management was structured incorporating both a centralised and decentralised system for the eight study centres, which all used the same database and standardised data collection instruments, manuals and processes. Each centre was responsible for the entry and validation of their country-specific data, which were entered onto a centralised system maintained by the Data Coordinating Unit in Oxford. A comprehensive data management system was designed to handle the very large volumes of data. It contained internal validations to prevent incorrect and inconsistent values being captured, and allowed online data entry by local Data Management Units, as well as real-time management of recruitment and data collection by the Data Coordinating Unit in Oxford. To maintain data integrity, only the Data Coordinating Unit in Oxford had access to all the eight centres' data, which were continually monitored. All queries identified were raised with the relevant local data manager for verification and correction, if necessary. The system automatically logged an audit trail of all updates to the database with the date and name of the person who made the changes. These rigorous processes ensured that the data collected in the INTERGROWTH-21(st) Project were of exceptionally high quality.

A rapid questionnaire assessment of environmental exposures to pregnant women in the INTERGROWTH-21st Project.

Impaired fetal growth and preterm birth are the leading causes of neonatal and infant mortality worldwide and there is a growing scientific literature suggesting that environmental exposures during pregnancy may play a causal role in these outcomes. Our purpose was to assess the environmental exposure of the Fetal Growth Longitudinal Study (FGLS) participants in the multinational INTERGROWTH-21(st) Project. First, we developed a tool that could be used internationally to screen pregnant women for such exposures and administered it in eight countries on a subsample (n = 987) of the FGLS participants. The FGLS is a study of fetal growth among healthy pregnant women living in relatively affluent areas, at low risk of adverse pregnancy outcomes and environmental exposures. We confirmed that most women were not exposed to major environmental hazards that could affect pregnancy outcomes according to the protocol's entry criteria. However, the instrument was able to identify some women that reported various environmental concerns in their homes such as peeling paint, high residential density (>1 person per room), presence of rodents or cockroaches (hence the use of pesticides), noise pollution and safety concerns. This screening tool was therefore useful for the purposes of the project and can be used to ascertain environmental exposures in studies in which the primary aim is not focused on environmental exposures. The instrument can be used to identify subpopulations for more in-depth assessment, (e.g. environmental and biological laboratory markers) to pinpoint areas requiring education, intervention or policy change.