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.

GRIPP2 reporting checklists: tools to improve reporting of patient and public involvement in research.

BACKGROUND: While the patient and public involvement (PPI) evidence base has expanded over the past decade, the quality of reporting within papers is often inconsistent, limiting our understanding of how it works, in what context, for whom, and why. OBJECTIVE: To develop international consensus on the key items to report to enhance the quality, transparency, and consistency of the PPI evidence base. To collaboratively involve patients as research partners at all stages in the development of GRIPP2. METHODS: The EQUATOR method for developing reporting guidelines was used. The original GRIPP (Guidance for Reporting Involvement of Patients and the Public) checklist was revised, based on updated systematic review evidence. A three round Delphi survey was used to develop consensus on items to be included in the guideline. A subsequent face-to-face meeting produced agreement on items not reaching consensus during the Delphi process. RESULTS: One hundred forty-three participants agreed to participate in round one, with an 86% (123/143) response for round two and a 78% (112/143) response for round three. The Delphi survey identified the need for long form (LF) and short form (SF) versions. GRIPP2-LF includes 34 items on aims, definitions, concepts and theory, methods, stages and nature of involvement, context, capture or measurement of impact, outcomes, economic assessment, and reflections and is suitable for studies where the main focus is PPI. GRIPP2-SF includes five items on aims, methods, results, outcomes, and critical perspective and is suitable for studies where PPI is a secondary focus. CONCLUSIONS: GRIPP2-LF and GRIPP2-SF represent the first international evidence based, consensus informed guidance for reporting patient and public involvement in research. Both versions of GRIPP2 aim to improve the quality, transparency, and consistency of the international PPI evidence base, to ensure PPI practice is based on the best evidence. In order to encourage its wide dissemination this article is freely accessible on The BMJ and Research Involvement and Engagement journal websites.

GRIPP2 reporting checklists: tools to improve reporting of patient and public involvement in research.

Background While the patient and public involvement (PPI) evidence base has expanded over the past decade, the quality of reporting within papers is often inconsistent, limiting our understanding of how it works, in what context, for whom, and why.Objective To develop international consensus on the key items to report to enhance the quality, transparency, and consistency of the PPI evidence base. To collaboratively involve patients as research partners at all stages in the development of GRIPP2.Methods The EQUATOR method for developing reporting guidelines was used. The original GRIPP (Guidance for Reporting Involvement of Patients and the Public) checklist was revised, based on updated systematic review evidence. A three round Delphi survey was used to develop consensus on items to be included in the guideline. A subsequent face-to-face meeting produced agreement on items not reaching consensus during the Delphi process.Results 143 participants agreed to participate in round one, with an 86% (123/143) response for round two and a 78% (112/143) response for round three. The Delphi survey identified the need for long form (LF) and short form (SF) versions. GRIPP2-LF includes 34 items on aims, definitions, concepts and theory, methods, stages and nature of involvement, context, capture or measurement of impact, outcomes, economic assessment, and reflections and is suitable for studies where the main focus is PPI. GRIPP2-SF includes five items on aims, methods, results, outcomes, and critical perspective and is suitable for studies where PPI is a secondary focus.Conclusions GRIPP2-LF and GRIPP2-SF represent the first international evidence based, consensus informed guidance for reporting patient and public involvement in research. Both versions of GRIPP2 aim to improve the quality, transparency, and consistency of the international PPI evidence base, to ensure PPI practice is based on the best evidence. In order to encourage its wide dissemination this article is freely accessible on The BMJ and Research Involvement and Engagement journal websites.

The COMET Initiative database: progress and activities update (2015).

This letter describes the substantial activity on the Core Outcome Measure in Effectiveness Trials (COMET) website in 2015, updating our earlier progress reports for the period from the launch of the COMET website and database in August 2011 to December 2014. As in previous years, 2015 saw further increases in the annual number of visits to the website, the number of pages viewed and the number of searches undertaken. The sustained growth in use of the website and database suggests that COMET is continuing to gain interest and prominence, and that the resources are useful to people interested in the development of core outcome sets.

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.

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 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).

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.

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).

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).

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.

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.

Towards a framework for analysis of eye-tracking studies in the three dimensional environment: a study of visual search by experienced readers of endoluminal CT colonography.

OBJECTIVE: Eye tracking in three dimensions is novel, but established descriptors derived from two-dimensional (2D) studies are not transferable. We aimed to develop metrics suitable for statistical comparison of eye-tracking data obtained from readers of three-dimensional (3D) "virtual" medical imaging, using CT colonography (CTC) as a typical example. METHODS: Ten experienced radiologists were eye tracked while observing eight 3D endoluminal CTC videos. Subsequently, we developed metrics that described their visual search patterns based on concepts derived from 2D gaze studies. Statistical methods were developed to allow analysis of the metrics. RESULTS: Eye tracking was possible for all readers. Visual dwell on the moving region of interest (ROI) was defined as pursuit of the moving object across multiple frames. Using this concept of pursuit, five categories of metrics were defined that allowed characterization of reader gaze behaviour. These were time to first pursuit, identification and assessment time, pursuit duration, ROI size and pursuit frequency. Additional subcategories allowed us to further characterize visual search between readers in the test population. CONCLUSION: We propose metrics for the characterization of visual search of 3D moving medical images. These metrics can be used to compare readers' visual search patterns and provide a reproducible framework for the analysis of gaze tracking in the 3D environment. ADVANCES IN KNOWLEDGE: This article describes a novel set of metrics that can be used to describe gaze behaviour when eye tracking readers during interpretation of 3D medical images. These metrics build on those established for 2D eye tracking and are applicable to increasingly common 3D medical image displays.