Peter C Gøtzsche

Bio: Peter C Gøtzsche is an academic researcher from Cochrane Collaboration. The author has contributed to research in topics: Systematic review & Placebo. The author has an hindex of 90, co-authored 413 publications receiving 147009 citations. Previous affiliations of Peter C Gøtzsche include University of Copenhagen & Copenhagen University Hospital.

Placebo effects. Concept of placebo should be discarded.

Abstract: EDITOR,--E Ernst and K L Resch state that the true placebo effect can be measured in trials that compare an untreated group with a placebo group1 They assume that non-specific effects other than the true placebo effect produce the same response in the two arms of a trial …

Increased incidence of invasive breast cancer after the introduction of service screening with mammography in Sweden.

Abstract: Dear Sir, Jonsson et al. find considerable overdiagnosis after introduction of service screening with mammography in Sweden. Even after adjustment for lead time, they find relative risks of 1.54 for the age group 50–59 years and 1.21 for 60–69 years. The authors analyzed the stabilized phase which they defined as the incidence from year 7 and forward after introduction of screening, and compared with the period before screening. I agree with their approach but wonder why the authors write that the randomized screening trials cannot be used for estimation of the level of overdiagnosis. They argue that the time before the control group was invited to screening was too short in the trials in Sweden and elsewhere. However, according to their own criteria, this is not correct. There are data from the trials in Canada and Malm€o after 7 and 8.8 years of followup where the control group had not been invited to screening. We have reported a relative risk of 1.30 (95% CI 1.20– 1.40) for number of cancers and a similar increase in number of mastectomies and tumorectomies. We have also analyzed the other Swedish trials, looking only at the period before the control group was invited to screening, and found similar results, relative risk 1.33 (1.24–1.44). We are aware that even after 7–9 years, some minor effect of lead time would remain in the trials, but opportunistic screening in the control group is a bias that goes in the opposite direction. We therefore think that our findings are reasonably reliable and that Jonsson et al. have confirmed them with epidemiological data.

Benefits and harms of the human papillomavirus (HPV) vaccines: systematic review with meta-analyses of trial data from clinical study reports.

Abstract: To assess the benefits and harms of the human papillomavirus (HPV) vaccines. Clinical study reports obtained from the European Medicines Agency and GlaxoSmithKline from 2014 to 2017. Randomised trials that compared an HPV vaccine with a placebo or active comparator in healthy participants of all ages. Two researchers extracted data and judged risk of bias with the Cochrane tool (version 2011). Risk ratio (RR) estimates were pooled using random-effects meta-analysis. Clinically relevant outcomes in intention to treat populations—including HPV-related cancer precursors irrespective of involved HPV types, treatment procedures and serious and general harms. Twenty-four of 50 eligible clinical study reports were obtained with 58,412 pages of 22 trials and 2 follow-up studies including 95,670 participants: 79,102 females and 16,568 males age 8–72; 393,194 person-years; and 49 months mean weighted follow-up. We judged all 24 studies to be at high risk of bias. Serious harms were incompletely reported for 72% of participants (68,610/95,670). Nearly all control participants received active comparators (48,289/48,595, 99%). No clinical study report included complete case report forms. At 4 years follow-up, the HPV vaccines reduced HPV-related carcinoma in situ (367 in the HPV vaccine group vs. 490 in the comparator group, RR 0.73 [95% confidence interval, CI, 0.53 to 1.00], number needed to vaccinate [NNV] 387, P = 0.05, I2 = 67%) and HPV-related treatment procedures (1018 vs. 1416, RR 0.71 [95% CI 0.63 to 0.80], NNV 75, P < 0.00001, I2 = 45%). The HPV vaccines increased serious nervous system disorders (exploratory analysis: 72 vs. 46, RR 1.49 [1.02 to 2.16], number needed to harm [NNH] 1325, P = 0.040, I2 = 0%) and general harms (13,248 vs. 12,394, RR 1.07 [95% CI 1.03 to 1.11], NNH 51, P = 0.0002, I2 = 77%) but did not significantly increase fatal harms (45 vs. 38, RR 1.19 [95% CI 0.65 to 2.19], P = 0.58, I2 = 30%) or serious harms (1404 vs. 1357, RR 1.01 [95% CI 0.94 to 1.08], P = 0.79, I2 = 0%). At 4 years follow-up, the HPV vaccines decreased HPV-related cancer precursors and treatment procedures but increased serious nervous system disorders (exploratory analysis) and general harms. As the included trials were primarily designed to assess benefits and were not adequately designed to assess harms, the extent to which the HPV vaccines’ benefits outweigh their harms is unclear. Limited access to clinical study reports and trial data with case report forms prevented a thorough assessment. CRD42017056093. Our systematic review protocol was registered on PROSPERO in January 2017: https://www.crd.york.ac.uk/PROSPEROFILES/56093_PROTOCOL_20170030.pdf. Two protocol amendments were registered on PROSPERO on November 2017: https://www.crd.york.ac.uk/PROSPEROFILES/56093_PROTOCOL_20171116.pdf. Our index of the HPV vaccine studies was published in Systematic Reviews in January 2018: https://doi.org/10.1186/s13643-018-0675-z. A description of the challenges obtaining the data was published in September 2018: https://doi.org/10.1136/bmj.k3694.

Who evaluates public health programmes? A review of the NHS Breast Screening Programme

Abstract: Breast screening with mammography was introduced in the UK in 1988, and the Annual Review 2008 from the NHS Breast Cancer Screening Programme (NHS BSP) summarizes the 20-year experience. Twenty years is a long time and it seems reasonable to ask what might be expected from such a review from a public health institution. First and foremost, one would expect to see an analysis that shows that screening has lowered breast cancer mortality in the UK. Secondly, one would wish to see a comparison of this benefit with a quantification of the most important harms, as this would allow the readers to judge for themselves whether the programme has been worth its large cost. If the screening programme had lived up to the expected mortality reduction that was the basis for its introduction, it should have been easy for the NHS Breast Cancer Screening Programme to demonstrate this for the politicians and other interested parties. This is not what the 26-page publication does, however. It celebrates 20 years of breast screening, as one of the headlines says. As with all good birthdays, it is the qualities of the celebrated that are mentioned, not the shortcomings. In line with the positive framing, the first sentence in the Review refers to the 20th anniversary as a ‘momentous occasion’. The Review exaggerates the benefit, omits the harms, and looks like propaganda aimed at persuasion. It comes wrapped in a beautiful layout that would pride any marketing department if it had been a sales brochure for a drug (Figure 1). The first words on the cover page are: ‘Saving lives through screening’, and the symbolism is strong. Most of the cover space is taken up by a picture of a delicate rose in the distinctive pink colour that has become iconic for the fight against breast cancer. The rose is transparent, symbolizing the scientific illumination and radiological technique through which the programme operates.

Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement

Abstract: David Moher and colleagues introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses

Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement.

Abstract: Systematic reviews and meta-analyses have become increasingly important in health care. Clinicians read them to keep up to date with their field,1,2 and they are often used as a starting point for developing clinical practice guidelines. Granting agencies may require a systematic review to ensure there is justification for further research,3 and some health care journals are moving in this direction.4 As with all research, the value of a systematic review depends on what was done, what was found, and the clarity of reporting. As with other publications, the reporting quality of systematic reviews varies, limiting readers' ability to assess the strengths and weaknesses of those reviews. Several early studies evaluated the quality of review reports. In 1987, Mulrow examined 50 review articles published in 4 leading medical journals in 1985 and 1986 and found that none met all 8 explicit scientific criteria, such as a quality assessment of included studies.5 In 1987, Sacks and colleagues6 evaluated the adequacy of reporting of 83 meta-analyses on 23 characteristics in 6 domains. Reporting was generally poor; between 1 and 14 characteristics were adequately reported (mean = 7.7; standard deviation = 2.7). A 1996 update of this study found little improvement.7 In 1996, to address the suboptimal reporting of meta-analyses, an international group developed a guidance called the QUOROM Statement (QUality Of Reporting Of Meta-analyses), which focused on the reporting of meta-analyses of randomized controlled trials.8 In this article, we summarize a revision of these guidelines, renamed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses), which have been updated to address several conceptual and practical advances in the science of systematic reviews (Box 1). Box 1 Conceptual issues in the evolution from QUOROM to PRISMA

Bias in meta-analysis detected by a simple, graphical test

Abstract: Objective: Funnel plots (plots of effect estimates against sample size) may be useful to detect bias in meta-analyses that were later contradicted by large trials. We examined whether a simple test of asymmetry of funnel plots predicts discordance of results when meta-analyses are compared to large trials, and we assessed the prevalence of bias in published meta-analyses. Design: Medline search to identify pairs consisting of a meta-analysis and a single large trial (concordance of results was assumed if effects were in the same direction and the meta-analytic estimate was within 30% of the trial); analysis of funnel plots from 37 meta-analyses identified from a hand search of four leading general medicine journals 1993-6 and 38 meta-analyses from the second 1996 issue of the Cochrane Database of Systematic Reviews . Main outcome measure: Degree of funnel plot asymmetry as measured by the intercept from regression of standard normal deviates against precision. Results: In the eight pairs of meta-analysis and large trial that were identified (five from cardiovascular medicine, one from diabetic medicine, one from geriatric medicine, one from perinatal medicine) there were four concordant and four discordant pairs. In all cases discordance was due to meta-analyses showing larger effects. Funnel plot asymmetry was present in three out of four discordant pairs but in none of concordant pairs. In 14 (38%) journal meta-analyses and 5 (13%) Cochrane reviews, funnel plot asymmetry indicated that there was bias. Conclusions: A simple analysis of funnel plots provides a useful test for the likely presence of bias in meta-analyses, but as the capacity to detect bias will be limited when meta-analyses are based on a limited number of small trials the results from such analyses should be treated with considerable caution. Key messages Systematic reviews of randomised trials are the best strategy for appraising evidence; however, the findings of some meta-analyses were later contradicted by large trials Funnel plots, plots of the trials9 effect estimates against sample size, are skewed and asymmetrical in the presence of publication bias and other biases Funnel plot asymmetry, measured by regression analysis, predicts discordance of results when meta-analyses are compared with single large trials Funnel plot asymmetry was found in 38% of meta-analyses published in leading general medicine journals and in 13% of reviews from the Cochrane Database of Systematic Reviews Critical examination of systematic reviews for publication and related biases should be considered a routine procedure