Stephen Burgess
@stevesphd.bsky.social
Medical statistician, work with genetic data to disentangle causation from correlation. Author of book on Mendelian randomization.
Thanks to Susanna, @amymariemason.bsky.social, @siddharthakar.bsky.social, Toinét, Emily, and Giovana. Also to @paulpharoah.bsky.social who inspired / challenged us to take up this work, and the 2 million+ volunteers whose data are represented in the analysis.
December 16, 2025 at 9:55 AM
Thanks to Susanna, @amymariemason.bsky.social, @siddharthakar.bsky.social, Toinét, Emily, and Giovana. Also to @paulpharoah.bsky.social who inspired / challenged us to take up this work, and the 2 million+ volunteers whose data are represented in the analysis.
Overall, we saw evidence that alcohol increases cancer risk, but *only for parts of the body that alcohol comes into contact with when consumed*. For other cancer types, evidence for a harmful effect was either inconsistent or absent.
December 16, 2025 at 9:55 AM
Overall, we saw evidence that alcohol increases cancer risk, but *only for parts of the body that alcohol comes into contact with when consumed*. For other cancer types, evidence for a harmful effect was either inconsistent or absent.
... difficulties in distinguishing those who died “from cancer” and those who died “with cancer”, between the effects of light drinking versus heavy drinking, and the impact of different types of alcohol.
December 16, 2025 at 9:55 AM
... difficulties in distinguishing those who died “from cancer” and those who died “with cancer”, between the effects of light drinking versus heavy drinking, and the impact of different types of alcohol.
Limitations of this work include uncertainty in the extent to which the genetic variants tell us specifically about the impact of alcohol consumption, the potential for alcohol consumption to affect cancer discovery rather than cancer risk, ...
December 16, 2025 at 9:55 AM
Limitations of this work include uncertainty in the extent to which the genetic variants tell us specifically about the impact of alcohol consumption, the potential for alcohol consumption to affect cancer discovery rather than cancer risk, ...
Oddly, for kidney cancer, endometrial cancer, non-Hodgkin's lymphoma, and myeloma, we saw evidence for a protective effect of alcohol consumption. Some of these associations mirror those seen in conventional observational analyses.
December 16, 2025 at 9:55 AM
Oddly, for kidney cancer, endometrial cancer, non-Hodgkin's lymphoma, and myeloma, we saw evidence for a protective effect of alcohol consumption. Some of these associations mirror those seen in conventional observational analyses.
For lung cancer, we saw evidence for a causal effect in the genome-wide analysis, but this attenuated to null on adjustment for smoking behaviour, and was not seen in the ADH1B analysis - suggesting either pleiotropy or mediated effect via smoking.
December 16, 2025 at 9:55 AM
For lung cancer, we saw evidence for a causal effect in the genome-wide analysis, but this attenuated to null on adjustment for smoking behaviour, and was not seen in the ADH1B analysis - suggesting either pleiotropy or mediated effect via smoking.
For other cancers, we saw no consistent evidence for a harmful effect, including breast cancer, which had a null estimate even for 50k+ biobank cases and 130k+ consortium cases. However, we did see evidence for an effect of alcohol consumption on cancer mortality.
December 16, 2025 at 9:55 AM
For other cancers, we saw no consistent evidence for a harmful effect, including breast cancer, which had a null estimate even for 50k+ biobank cases and 130k+ consortium cases. However, we did see evidence for an effect of alcohol consumption on cancer mortality.
For several cancers with strong prior evidence, we observed evidence supporting a harmful effect of alcohol consumption: combined head/neck, colorectal, and oesophageal. For liver cancer, we only saw evidence in the Million Veteran Program (high alcohol consumption cohort).
December 16, 2025 at 9:55 AM
For several cancers with strong prior evidence, we observed evidence supporting a harmful effect of alcohol consumption: combined head/neck, colorectal, and oesophageal. For liver cancer, we only saw evidence in the Million Veteran Program (high alcohol consumption cohort).
We conducted analyses in four biobanks comprising 1.4 million individuals: UK Biobank, FinnGen, All of US, and Million Veteran Program, plus various cancer-specific consortia, considering evidence for effects of alcohol on 20 cancer types.
December 16, 2025 at 9:55 AM
We conducted analyses in four biobanks comprising 1.4 million individuals: UK Biobank, FinnGen, All of US, and Million Veteran Program, plus various cancer-specific consortia, considering evidence for effects of alcohol on 20 cancer types.
Our work had three co-primary analyses: a genome-wide analysis based on 95 variants, a multivariable analysis based on the same 95 variants but with adjustment for smoking behaviour, and a focused analysis based on a single variant in the ADH1B locus.
December 16, 2025 at 9:55 AM
Our work had three co-primary analyses: a genome-wide analysis based on 95 variants, a multivariable analysis based on the same 95 variants but with adjustment for smoking behaviour, and a focused analysis based on a single variant in the ADH1B locus.
Mendelian randomization is a non-experimental technique - we do not intervene on alcohol levels. However, by comparing those with and without genetic variants that associate with alcohol consumption, we get closer to the like-with-like comparison needed to make causal claims.
December 16, 2025 at 9:55 AM
Mendelian randomization is a non-experimental technique - we do not intervene on alcohol levels. However, by comparing those with and without genetic variants that associate with alcohol consumption, we get closer to the like-with-like comparison needed to make causal claims.
Thanks to Will Bickford Smith for co-leading this, and the people at Policy Exchange for commissioning this work. Great to see this work published! Policy document: policyexchange.org.uk/publication/..., Statistical report: policyexchange.org.uk/wp-content/u....
From School To The Skilled Workforce - Policy Exchange
Download Publication Independent Analysis Online Reader This new report by Policy Exchange makes the case that University Technical Colleges (UTCs) can play a vital role in addressing the UK’s profoun...
policyexchange.org.uk
November 14, 2025 at 10:30 AM
Thanks to Will Bickford Smith for co-leading this, and the people at Policy Exchange for commissioning this work. Great to see this work published! Policy document: policyexchange.org.uk/publication/..., Statistical report: policyexchange.org.uk/wp-content/u....
Based on student attainment data, UTC students perform less well at English at age 16, but equally well at maths (and potentially better at maths for disadvantaged students).
November 14, 2025 at 10:30 AM
Based on student attainment data, UTC students perform less well at English at age 16, but equally well at maths (and potentially better at maths for disadvantaged students).
Based on leaver data, UTC students were more likely to go into apprenticeships, potentially more likely to go into employment, and no more likely (and possibly less likely) to have no sustained outcome.
November 14, 2025 at 10:30 AM
Based on leaver data, UTC students were more likely to go into apprenticeships, potentially more likely to go into employment, and no more likely (and possibly less likely) to have no sustained outcome.
Differences in overall education participation were maintained across surveys, but differences in further education participation appeared to attenuate to zero over time.
November 14, 2025 at 10:30 AM
Differences in overall education participation were maintained across surveys, but differences in further education participation appeared to attenuate to zero over time.
Based on student destination data, UTC students were consistently less likely to be in sustained education, but more likely to be in sustained employment, and less likely to not have a sustained outcome compared with students at comparable schools.
November 14, 2025 at 10:30 AM
Based on student destination data, UTC students were consistently less likely to be in sustained education, but more likely to be in sustained employment, and less likely to not have a sustained outcome compared with students at comparable schools.
We performed a doubly-robust analysis, matching on these variables but also adjusting for them in a regression model. We also adjusted for proportion of pupils who are boys (%BOYS), but didn't match on this variable (as schools with unbalanced sex ratio are often atypical).
November 14, 2025 at 10:30 AM
We performed a doubly-robust analysis, matching on these variables but also adjusting for them in a regression model. We also adjusted for proportion of pupils who are boys (%BOYS), but didn't match on this variable (as schools with unbalanced sex ratio are often atypical).
We matched on three variables, proportion of pupils with English as an additional language (%EAL), proportion with special educational needs (%SEN), and proprtion with free school meals (%FSM).
November 14, 2025 at 10:30 AM
We matched on three variables, proportion of pupils with English as an additional language (%EAL), proportion with special educational needs (%SEN), and proprtion with free school meals (%FSM).
For most outcomes, we performed a matched analysis, matching each UTC with 5 similar schools in the same Local Educational Authority, and comparing outcomes within each matched set. This analysis uses less data than an analysis of the full dataset, but more relevant data.
November 14, 2025 at 10:30 AM
For most outcomes, we performed a matched analysis, matching each UTC with 5 similar schools in the same Local Educational Authority, and comparing outcomes within each matched set. This analysis uses less data than an analysis of the full dataset, but more relevant data.
We wanted to benchmark UTC performance for exam results and leaver outcomes. The analysis was challenging in a number of ways. How to conduct a like-with-like comparison of UTCs with similar secondary schools that are not UTCs using publicly-available data?
November 14, 2025 at 10:30 AM
We wanted to benchmark UTC performance for exam results and leaver outcomes. The analysis was challenging in a number of ways. How to conduct a like-with-like comparison of UTCs with similar secondary schools that are not UTCs using publicly-available data?
University Technical Colleges (UTCs) are non-selective state-funded “free” secondary schools in the UK (free = outside the control of the local education authority, as well as non-paying) that focus on science and technology.
November 14, 2025 at 10:30 AM
University Technical Colleges (UTCs) are non-selective state-funded “free” secondary schools in the UK (free = outside the control of the local education authority, as well as non-paying) that focus on science and technology.
Thanks to @hwang_seongwon for leading the project, to @jeffreypullin.bsky.social for performing code review, and to @chr1sw.bsky.social allace and John Whittaker for co-supervising - has been a fun project so far, and look forward to getting feedback from the community!
November 8, 2025 at 3:40 PM
Thanks to @hwang_seongwon for leading the project, to @jeffreypullin.bsky.social for performing code review, and to @chr1sw.bsky.social allace and John Whittaker for co-supervising - has been a fun project so far, and look forward to getting feedback from the community!