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1.  International standards for early fetal size and pregnancy dating based on ultrasound measurement of crown–rump length in the first trimester of pregnancy 
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-21st Project aimed to produce the first international standards for early fetal size and ultrasound dating of pregnancy based on CRL measurement.
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.
A total of 4607 women were enrolled in the Fetal Growth Longitudinal Study, one of the three main components of the INTERGROWTH-21st 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 × GA2); and SD of CRL = −2.21626 + (0.0984894 × GA). GA estimation is carried out according to the two equations: GA = 40.9041 + (3.21585 × CRL0.5) + (0.348956 × CRL); and SD of GA = 2.39102 + (0.0193474 × CRL).
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. © 2014 Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
PMCID: PMC4286014  PMID: 25044000
crown–rump length; dating; gestational age; global health; growth; pregnancy
2.  Ethnicity and outcome of young breast cancer patients in the United Kingdom: the POSH study 
British Journal of Cancer  2013;110(1):230-241.
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.
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.
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).
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.
PMCID: PMC3887284  PMID: 24149174
breast cancer; prognosis; ethnicity
3.  Identifying patients with undetected colorectal cancer: an independent validation of QCancer (Colorectal) 
British Journal of Cancer  2012;107(2):260-265.
Early identification of colorectal cancer is an unresolved challenge and the predictive value of single symptoms is limited. We evaluated the performance of QCancer (Colorectal) prediction model for predicting the absolute risk of colorectal cancer in an independent UK cohort of patients from general practice records.
A total of 2.1 million patients registered with a general practice surgery between 01 January 2000 and 30 June 2008, aged 30-84 years (3.7 million person-years) with 3712 colorectal cancer cases were included in the analysis. Colorectal cancer was defined as incident diagnosis of colorectal cancer during the 2 years after study entry.
The results from this independent and external validation of QCancer (Colorectal) prediction model demonstrated good performance data on a large cohort of general practice patients. QCancer (Colorectal) had very good discrimination with an area under the ROC curve of 0.92 (women) and 0.91 (men), and explained 68% (women) and 66% (men) of the variation. QCancer (Colorectal) was well calibrated across all tenths of risk and over all age ranges with predicted risks closely matching observed risks.
QCancer (Colorectal) appears to be a useful tool for identifying undetected cases of undiagnosed colorectal cancer in primary care in the United Kingdom.
PMCID: PMC3394989  PMID: 22699822
colorectal cancer; diagnosis; risk prediction; QCancer; validation
4.  The benefits and harms of breast cancer screening: an independent review 
British Journal of Cancer  2013;108(11):2205-2240.
PMCID: PMC3693450  PMID: 23744281
5.  Frequency and reasons for outcome reporting bias in clinical trials: interviews with trialists 
Objectives To provide information on the frequency and reasons for outcome reporting bias in clinical trials.
Design Trial protocols were compared with subsequent publication(s) to identify any discrepancies in the outcomes reported, and telephone interviews were conducted with the respective trialists to investigate more extensively the reporting of the research and the issue of unreported outcomes.
Participants Chief investigators, or lead or coauthors of trials, were identified from two sources: trials published since 2002 covered in Cochrane systematic reviews where at least one trial analysed was suspected of being at risk of outcome reporting bias (issue 4, 2006; issue 1, 2007, and issue 2, 2007 of the Cochrane library); and a random sample of trial reports indexed on PubMed between August 2007 and July 2008.
Setting Australia, Canada, Germany, the Netherlands, New Zealand, the United Kingdom, and the United States.
Main outcome measures Frequency of incomplete outcome reporting—signified by outcomes that were specified in a trial’s protocol but not fully reported in subsequent publications—and trialists’ reasons for incomplete reporting of outcomes.
Results 268 trials were identified for inclusion (183 from the cohort of Cochrane systematic reviews and 85 from PubMed). Initially, 161 respective investigators responded to our requests for interview, 130 (81%) of whom agreed to be interviewed. However, failure to achieve subsequent contact, obtain a copy of the study protocol, or both meant that final interviews were conducted with 59 (37%) of the 161 trialists. Sixteen trial investigators failed to report analysed outcomes at the time of the primary publication, 17 trialists collected outcome data that were subsequently not analysed, and five trialists did not measure a prespecified outcome over the course of the trial. In almost all trials in which prespecified outcomes had been analysed but not reported (15/16, 94%), this under-reporting resulted in bias. In nearly a quarter of trials in which prespecified outcomes had been measured but not analysed (4/17, 24%), the “direction” of the main findings influenced the investigators’ decision not to analyse the remaining data collected. In 14 (67%) of the 21 randomly selected PubMed trials, there was at least one unreported efficacy or harm outcome. More than a quarter (6/21, 29%) of these trials were found to have displayed outcome reporting bias.
Conclusion The prevalence of incomplete outcome reporting is high. Trialists seemed generally unaware of the implications for the evidence base of not reporting all outcomes and protocol changes. A general lack of consensus regarding the choice of outcomes in particular clinical settings was evident and affects trial design, conduct, analysis, and reporting.
PMCID: PMC3016816  PMID: 21212122
6.  Prognostic markers in cancer: the evolution of evidence from single studies to meta-analysis, and beyond 
British Journal of Cancer  2009;100(8):1219-1229.
In oncology, prognostic markers are clinical measures used to help elicit an individual patient's risk of a future outcome, such as recurrence of disease after primary treatment. They thus facilitate individual treatment choice and aid in patient counselling. Evidence-based results regarding prognostic markers are therefore very important to both clinicians and their patients. However, there is increasing awareness that prognostic marker studies have been neglected in the drive to improve medical research. Large protocol-driven, prospective studies are the ideal, with appropriate statistical analysis and clear, unbiased reporting of the methods used and the results obtained. Unfortunately, published prognostic studies rarely meet such standards, and systematic reviews and meta-analyses are often only able to draw attention to the paucity of good-quality evidence. We discuss how better-quality prognostic marker evidence can evolve over time from initial exploratory studies, to large protocol-driven primary studies, and then to meta-analysis or even beyond, to large prospectively planned pooled analyses and to the initiation of tumour banks. We highlight articles that facilitate each stage of this process, and that promote current guidelines aimed at improving the design, analysis, and reporting of prognostic marker research. We also outline why collaborative, multi-centre, and multi-disciplinary teams should be an essential part of future studies.
PMCID: PMC2676559  PMID: 19367280
prognosis; prognostic tumour marker; biomarker; primary studies; evidence synthesis; guidelines
7.  Reporting of prognostic studies of tumour markers: a review of published articles in relation to REMARK guidelines 
British Journal of Cancer  2009;102(1):173-180.
Poor reporting compromises the reliability and clinical value of prognostic tumour marker studies. We review articles to assess the reporting of patients and events using REMARK guidelines, at the time of guideline publication.
We sampled 50 prognostic tumour marker studies from higher impact cancer journals between 2006 and 2007. The inclusion criteria were cancer; focus on single biological tumour marker; survival analysis; multivariable analysis; and not gene array or proteomic data. Articles were assessed for the REMARK profile and other REMARK guideline items. We propose a reporting aid, the REMARK profile, motivated by the CONSORT flowchart.
In 50 studies assessed for the REMARK profile, the number of eligible patients (56% of articles), excluded patients (54%) and patients in analyses (98%) was reported. Only 50% of articles reported the number of outcome events. In multivariable analyses, 54% and 30% of articles reported patient and event numbers for all variables. Of the studies, 66% used archival samples, indicating a potentially biased patient selection. Only 36% of studies reported clearly defined outcomes.
Good reporting is critical for the interpretability and clinical applicability of prognostic studies. Current reporting of key information, such as the number of outcome events in all patients and subgroups, is poor. Use of the REMARK profile would greatly improve reporting and enhance prognostic research.
PMCID: PMC2795163  PMID: 19997101
prognostic; REMARK; survival analysis; tumour marker; reporting guideline
8.  Modelling prognostic factors in advanced pancreatic cancer 
British Journal of Cancer  2008;99(6):883-893.
Pancreatic cancer is the fifth most common cause of cancer death. Identification of defined patient groups based on a prognostic index may improve the prediction of survival and selection of therapy. Many prognostic factors have been identified often based on retrospective, underpowered studies with unclear analyses. Data from 653 patients were analysed. Continuous variables are often simplified assuming a linear relationship with log hazard or introducing a step function (dichotomising). Misspecification may lead to inappropriate conclusions but has not been previously investigated in pancreatic cancer studies. Models based on standard assumptions were compared with a novel approach using nonlinear fractional polynomial (FP) transformations. The model based on FP-transformed covariates was most appropriate and confirmed five previously reported prognostic factors: albumin, CA19-9, alkaline phosphatase, LDH and metastases, and identified three additional factors not previously reported: WBC, AST and BUN. The effects of CA19-9, alkaline phosphatase, AST and BUN may go unrecognised due to simplistic assumptions made in statistical modelling. We advocate a multivariable approach that uses information contained within continuous variables appropriately. The functional form of the relationship between continuous covariates and survival should always be assessed. Our model should aid individual patient risk stratification and the design and analysis of future trials in pancreatic cancer.
PMCID: PMC2538756  PMID: 19238630
12.  School meals and the nutrition of schoolchildren. 
The contribution of school meals to the nutrition of 778 primary and secondary schoolchildren attending schools in Kent was assessed using information collected during a survey made in 1968-70 which included a weighed diet record, a socioeconomic questionnaire, and a medical examination. Younger children, those from larger families, those without fathers, and those whose mothers worked were more likely to take school meals. Significantly more children from lower social classes and without fathers received them free. School meals made an important contribution to the nutrition of schoolchildren. Children who took them had higher weekday lunchtime nutrient intake during term-time. Children in lower social classes, larger families, and without fathers who took school meals obtained a higher proportion of their weekday intake of nutrients from lunchtime than other children. This applied in particular to nutrients important for growth. School meals consumed by children in the study broadly met the standard set by the Department of Education and Science. The mean energy and protein content of school meals consumed in the study was slightly lower and the mean fat content higher than the standard set for the meal. The mean sugar content was about one-third higher than the suggested amount of sugar to be included in a school meal. There was no evidence that children who took school meals were taller, heavier, had greater skinfold thickness, or were more likely to be assessed as obese than other children.
PMCID: PMC478912  PMID: 1191886
13.  Influence of some social and environmental factors on the nutrient intake and nutritional status of schoolchildren. 
Only children had significantly higher intakes of many nutrients and nutrients/1000 kcal than other children. A higher proportion of only children was found to be obese. There were no significant differences according to birthrank in intakes by children. There were more obese children among the fatherless than those with fathers, in particular among those whose mothers were widowed. However, this was not accounted for by the present dietary findings, since fatherless children had lower intakes of carbohydrate and added sugar. There were no differences in nutrient intake or intake/1000 kcal by mother's country of origin or her level of education, or by disposable income.
PMCID: PMC478900  PMID: 1182353
14.  A nutritional surveillance study. 
PMCID: PMC1645038  PMID: 4800203
15.  REporting recommendations for tumour MARKer prognostic studies (REMARK) 
British Journal of Cancer  2005;93(4):387-391.
Despite years of research and hundreds of reports on tumour markers in oncology, the number of markers that have emerged as clinically useful is pitifully small. Often initially reported studies of a marker show great promise, but subsequent studies on the same or related markers yield inconsistent conclusions or stand in direct contradiction to the promising results. It is imperative that we attempt to understand the reasons that multiple studies of the same marker lead to differing conclusions. A variety of methodological problems have been cited to explain these discrepancies. Unfortunately, many tumour marker studies have not been reported in a rigorous fashion, and published articles often lack sufficient information to allow adequate assessment of the quality of the study or the generalisability of the study results. The development of guidelines for the reporting of tumour marker studies was a major recommendation of the US National Cancer Institute and the European Organisation for Research and Treatment of Cancer (NCI-EORTC) First International Meeting on Cancer Diagnostics in 2000. Similar to the successful CONSORT initiative for randomised trials and the STARD statement for diagnostic studies, we suggest guidelines to provide relevant information about the study design, preplanned hypotheses, patient and specimen characteristics, assay methods, and statistical analysis methods. In addition, the guidelines suggest helpful presentations of data and important elements to include in discussions. The goal of these guidelines is to encourage transparent and complete reporting so that the relevant information will be available to others to help them to judge the usefulness of the data and understand the context in which the conclusions apply.
PMCID: PMC2361579  PMID: 16106245
tumour marker; guidelines; REMARK; NCI; EORTC; prognostic
16.  Estimating sample sizes for binary, ordered categorical, and continuous outcomes in two group comparisons. 
BMJ : British Medical Journal  1995;311(7013):1145-1148.
Sample size calculations are now mandatory for many research protocols, but the ones useful in common situations are not all easily accessible. This paper outlines the ways of calculating sample sizes in two group studies for binary, ordered categorical, and continuous outcomes. Formulas and worked examples are given. Maximum power is usually achieved by having equal numbers in the two groups. However, this is not always possible and calculations for unequal group sizes are given.
PMCID: PMC2551061  PMID: 7580713
18.  Missing covariate data within cancer prognostic studies: a review of current reporting and proposed guidelines 
British Journal of Cancer  2004;91(1):4-8.
PMCID: PMC2364743  PMID: 15188004
missing covariate data; reporting; prognostic models; guidelines; survival
19.  Microcytosis, iron deficiency, and thalassaemia in preschool children. 
Archives of Disease in Childhood  1990;65(6):610-614.
To investigate the possible causes of an increased incidence of red cell microcytosis in Asian children, 204 Gujarati Asian children and 88 European children attending community infant welfare clinics underwent initial screening tests for determination of red cell indices. Seventy six Asian (37%) and nine European (12%) children had microcytic red cells (mean corpuscular volume less than 74 fl). Further investigation showed that 16 of the Asian children (21%) with microcytosis had thalassaemia trait (eight were heterozygous for alpha thalassaemia and eight for beta thalassaemia), and 50 (66%) had suspected iron deficiency (confirmed by a response to oral iron in 41 cases): the remaining 'microcytic' children were aged less than 2 years, when mean corpuscular volume between 70 and 74 fl may be normal. Increased values for serum total iron binding capacity were more sensitive in detecting iron deficiency than reduced serum ferritin concentrations. Enthusiastic screening for microcytic anaemia in young children may mean that a substantial minority with thalassaemia genes are given unnecessary iron supplements. The response to a short course of oral iron should therefore be carefully monitored, and the possibility of thalassaemia trait as well as non-compliance with treatment should be reconsidered in all those in whom there is little or no response.
PMCID: PMC1792064  PMID: 2378518
21.  Need for confidence intervals in reporting clinical trials 
Gut  1987;28(11):1549.
PMCID: PMC1433684  PMID: 18668887
22.  Survival Analysis Part IV: Further concepts and methods in survival analysis 
British Journal of Cancer  2003;89(5):781-786.
PMCID: PMC2394469  PMID: 12942105
survival analysis; missing data; validation; repeated events
23.  Survival Analysis Part III: Multivariate data analysis – choosing a model and assessing its adequacy and fit 
British Journal of Cancer  2003;89(4):605-611.
PMCID: PMC2376927  PMID: 12915864
survival analysis; Cox model; AFT model; model checking; choice of coavriates; goodness of fit
24.  Survival Analysis Part II: Multivariate data analysis – an introduction to concepts and methods 
British Journal of Cancer  2003;89(3):431-436.
PMCID: PMC2394368  PMID: 12888808
survival analysis; Cox model; AFT model; model selection
25.  Survival Analysis Part I: Basic concepts and first analyses 
British Journal of Cancer  2003;89(2):232-238.
PMCID: PMC2394262  PMID: 12865907
survival analysis; statistical methods; Kaplan-Meier

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