Observational Study of Age, Test THreshold and Frequency on English NAtional Mammography Screening Outcomes (ATHENA-M)
Conditions: Breast Cancer
Sponsor: University of Warwick

 
 
1 
 
 
ATHENA-M, Version 1.4 
 
 
Observational study of Age, test THreshold and frequency on 
English NAtional Mammography screening outcomes 
(ATHENA-M) 
 
 
Protocol Version 1.4 16th February 2022 
 
NCT05247463 
 
 

 
 
2 
 
Observational study of Age, test THreshold and frequency on English NAtional 
Mammography screening outcomes (ATHENA-M) 
Protocol 
Version 1.4 16th February 2022 
 
Observational study of Age, test THreshold and frequency on English NAtional 
Mammography screening outcomes (ATHENA-M) 
Protocol 
Version 1.4 16th February 2022 
Study Investigators 
Sian Taylor-Phillips (Chief Investigator, University of Warwick) 
Ros Given-Wilson (St Georges University Hospitals) 
Matthew Wallis (Cambridge University Hospitals) 
Louise Wilkinson (Oxford University Hospitals) 
Sarah Pinder (Kings College London) 
Jon Deeks (Birmingham University) 
Alice Sitch (Birmingham University) 
Jonathan Sterne (Bristol University) 
Aileen Clarke (University of Warwick) 
James Mason (University of Warwick) 
David Jenkinson (University of Warwick) 
Karoline Freeman (University of Warwick) 
Olive Kearins (Public Health England) 
Jackie Walton (Public Health England) 
 
Sponsor: University of Warwick,  
 
Identification Numbers 
Office for Data Release: ODR1920_283 (pending) 
Sponsor’s Office Ref: SOC.03/20-21 (approved) 
HRA: 21/LO/0120 (approved) 
Breast Research Advisory Committee: BSP RAC 089 (Conditional approval) 
ClinicalTrials.gov Identifier: NCT05247463 
 
 

 
 
3 
 
Protocol Previous versions 
Version 1.0 January 2020 pre funding award.  
Version 1.1 Changes from version 1.0 were as a result of feedback from NIHR funding 
panel, and include removal of work package 3 (analysis of mammographic abnormality type) 
and change of title. This version was sent to HRA for initial approvals. 
Version 1.2 Minor amendments requested by Public Health England Office for Data Release. 
Page 7-8, expanded description of how the database differs from the POSTBOx study, and 
exact definition of the included cohort added. Data tables moved from appendix 2 to a 
separate file, appendix 2 adjusted to a broader description of the variables. ‘Mortality and 
births Information System’ corrected to ‘civil registrations mortality file’. Primary source of 
breast cancer mortality outcome changes from cancer registry to civil registrations mortality 
file. David Jenkinson, Olive Kearins, Karoline Freeman, and Jackie Walton added to study 
investigators, and affiliations added. Table 10 added to data requested. Table 10 lists the 
data items which would improve the analysis, but are not yet available for linkage into the 
dataset (but may soon be). Work package 2 added that different definitions of round length 
(beyond 2 vs 3 years) will be investigated if time permits. Timings updated on gantt chart. 
Other minor corrections to wording.  
Version 1.3 Minor additional amendments requested by Public Health England. Expanded 
details of cause and date of death, and sources. Expanded explanation of cancer type 
outcome to clarify it covers screen detected only, and symptomatic and screen detected 
combined. Clarified that reader threshold analysis will have to consider number of readers. 
Provided clarification of date of data extract. Tables renumbered to fit PHE preferred 
structure.   
Version 1.4 Clarification of outcomes to match clinicaltrials.gov registration, including: 
clarification that outcomes labelled ‘health outcomes’ (not intermediate outcomes) are the 
primary outcomes, clarification that breast cancer mortality is the first outcome (due to 
greater power to detect differences than all-cause mortality), moving false positive recall 
from intermediate to primary outcomes due to its known association with anxiety, and 
reordering of presentation to match clinicaltrials.gov entry. More detail added to 
measurement of characteristics of cancer detected. Outcomes, whilst reordered in 
presentation remain unchanged, Addition of preliminary analyses for test threshold to 
determine whether instrumental variable assumptions are met and therefore whether this 
analysis is possible. Clinicaltrials.gov identifier added.  
Summary of Research  
Background 
There is a lot of debate about whether the benefits of breast cancer screening outweigh the 
harms. The UK Independent Review (1) led by Sir Michael Marmot estimated that breast 
cancer screening in the UK saves 1300 women’s lives every year; however 70,000 women 
each year are unnecessarily made anxious after the screening test (mammography) shows 
potential signs of cancer, but which are found to be benign (false positive results). Another 
4000 women are given unnecessary cancer treatment, because they have a cancer detected 
at screening that is so slow growing that it would never have harmed them or given them any 
symptoms in their life (overdiagnosis).(1) These are the best national estimates we have, but 
Sir Michael Marmot and colleagues based their estimates on randomised controlled trials 
from the 1970s, and did not have sufficient data to update them to more recent tests or 
treatments. Current tests use much higher resolution so the radiologists can identify smaller, 

 
 
4 
 
earlier stage changes, and modern treatment is much more effective. This affects how much 
benefit screening provides, so the current balance of benefits and harms are uncertain.  
International Variation in Breast Screening 
Different countries offer diverse versions of breast screening, because it is uncertain which is 
best. In the UK we offer screening every three years, which is the longest interval between 
breast screens in the world. In the US screening is undertaken every 1-2 years, and in most 
of Europe every two years. In practice in England there is a lot of variability in round length 
received by individual women, due to the policy and procedures, and workload of individual 
breast screening centres. In England overall, 4% of women are recalled for further tests 
because their mammograms show suspicious signs, with other countries recalling as few as 
2% (Denmark) or as many as 10% (USA). However the recall rate varies greatly between 
centres, because there is uncertainty about what is the best level. 
Our Approach 
We need to understand which version of breast screening offers the most benefit with the 
least harm. The best evidence for this would be from a Randomised Controlled Trial (RCT). 
However, such trials are very expensive, often do not include sufficient women, and need at 
least 10 years follow-up. So a trial that started recruiting now would not give answers until 
the year 2036. Instead, we suggest making use of the data available from offering different 
versions of breast screening to over 13 million women in England over the last 25 years, as 
a retrospective observational research study. We have carefully designed the design and 
analysis using methods that allow causal inference to be made from observational data.  
The Research Plan 
In this very large observational study we will analyse the records of women screened in 
England between 1990 and 2018, with follow up available as to whether they got breast 
cancer (from the English Cancer Registry) and whether they died (from the civil registration 
mortality file). We will analyse the ages and frequencies women are invited and the 
proportion of women we recall for further tests affects the benefits and harms of screening. 
These benefits and harms will include numbers of false positive recalls, overdiagnosed 
cases, and mortality. We will also analyse the mechanism of action for any changes, how 
changes to number and nature (eg histological grade and type, stage and size) of cancers 
detected at screening affect number and nature of cancer detected symptomatically in the 
years after screening, numbers overdiagnosed and life years saved. We will explore how 
detecting greater numbers of Ductal Carcinoma in Situ (DCIS, i.e. most common form of 
potential precursor of invasive breast cancer) affects the benefits and harms of screening.  
Using Findings to Change NHS Practice 
We will use the findings to inform the UK National Screening Committee and revision of the 
English quality assurance guidelines for breast cancer screening. This will depend on 
results, but could for example include revising the targets for proportion of women recalled, 
of DCIS detection rates, or level of flexibility in the screening interval target. 
1. Background and Rationale 
 
What is the problem being addressed? 
We do not currently know which version of breast cancer screening gives most benefit and 
least harm to the women who are screened. In particular, how often should women be 

 
 
5 
 
invited to breast cancer screening? What is the appropriate age range to offer breast cancer 
screening? Which recall threshold should we use for the test? Which types of 
mammographic abnormality should be investigated further?  
 
There is huge national and international variation in breast screening practice. This is due to 
the lack of evidence of which version gives most benefit and causes least harm. In England 
breast screening is offered every three years to women aged 50-70 using two-view 
mammography (2 x-rays) of each breast. The decision to use a three yearly interval was 
made in 1985.(2) Other countries screen either every year (US(3)) or two years (most 
European countries). The upper age limit was extended in the UK from 64 to 70 years in the 
NHS Cancer Plan in 2000(4) on the basis of pilot studies of acceptability and uptake only.(4) 
There is an ongoing trial of extending breast screening to between ages 47 and 73 (first 
results to be reported in 2026)(5) but there has been no evaluation of the previous age 
extension to 70 years.  
In England, of women attending breast cancer screening, 3.9% are recalled for further tests 
from each screening appointment(6), compared to 2.5% (Denmark(7)) or 10.6% (USA(8)). 
The percentage of women recalled is a marker for the radiologists ‘recall threshold’ which 
the radiologist can change by electing whether or not to recall moderately suspicious 
findings by type, or even by changing the workstation/workflow.(9) We need to understand 
the impact of these different versions of screening not only on proxy outcomes such as 
numbers of breast cancers detected, but on outcomes which affect the women screened 
such as: cancer and treatment-related morbidity; mortality; and overdiagnosis and 
associated overtreatment of breast cancer which would never become symptomatic in the 
woman’s lifetime.  
There is also uncertainty about which types of mammographic abnormalities and cancers we 
should aim to detect at screening. Since the trials of breast screening in the 1970s screening 
technology has improved markedly in resolution. Now we can detect smaller cancers, and 
smaller microcalcifications that may be associated with DCIS. Similarly, we detect more of 
these when we reduce the recall threshold. We do not know what the balance of benefits 
and harms are of detecting these very small cancers and ‘pre-cancer’ abnormalities, they 
may increase the life years saved or the number of women harmed by overdiagnosis.  
 
The ideal study design to answer specific questions such as this would be the randomised 
controlled trial (RCT). However this approach is impractical given the multiplicity of 
unknowns, and is not financially feasible for most changes to screening. However, given the 
natural variations within the records of the English national screening programme, a large 
observational design study is possible, enabling sufficient power and follow-up to real clinical 
outcomes.   
 
Why is this research important in terms of improving the health and/or wellbeing of 
the public and/or to patients and health and care services? 
 
Over two million women attend breast cancer screening each year in England. There is an 
ongoing international debate about the balance of benefits and harms. The UK Independent 
Review chaired by Sir Michael Marmot concluded that breast screening saves 1300 lives 
each year in the UK; however results in overdiagnosis and unnecessary treatment of another 

 
 
6 
 
4000 women, and 70,000 women receive false positive results and are subject to the 
associated anxiety.(1) This review was based on RCT evidence from the 1970s. These trials 
did not provide sufficient evidence to optimise screening interval, recall threshold, or age of 
eligibility which has led to the international variability. In addition, since these RCTs breast 
screening technology has improved and many smaller features can be detected, in particular 
microcalcifications associated with DCIS.  
Since its inception in 1988, 10 million women have attended breast screening, receiving a 
range of different versions of screening. (e.g. invited at different ages with different intervals 
between their screens etc.) We have, nationally, kept excellent records regarding the 
versions of screening each woman was offered, whether and when they developed cancer, 
and whether and when they died. Women have received different screening strategies 
providing a natural experiment. The screening strategy received is driven by centre level 
variables rather than the woman’s individual characteristics and prognostic factors, reducing 
potential bias due to confounding. We propose using these data to understand which 
versions of screening are most effective, and determine which is the best version to offer to 
the two million women who attend each year going forwards. This would mean that breast 
screening can be standardised to the version which gives the most mortality and morbidity 
benefit and least overdiagnosis and false positive harm. We will focus equal attention on the 
possibility of more screening or less screening. 
 
This research will also provide evidence to minimise the variability in care that women in 
England currently receive. Some breast radiologists recall 18% of women whilst others just 
2%(9). There is huge inter-centre variability in number of cases of DCIS detected, due to 
differing beliefs in the benefits and harms of detection. Clear evidence linking to benefits and 
harms would drive reduction in variability. Our PPI team have identified this as a priority.   
This research will impact the health of those attending breast cancer screening through 
working with the UK National Screening Committee if our research suggests a substantial 
programme modification, and Public Health England (PHE) to modify the breast screening 
quality assurance guidelines, linking targets to maximising benefits and minimising harms of 
screening.   
 
Finally, this research also has the potential to influence future policy decisions. Our 
proposed analysis of mechanism of action will enhance our understanding of the benefits 
and harms of detecting different cancer and precancer types at screening. This will be 
important when making future policy decisions about new breast screening testing 
technology (such as incorporating fast MRI, tomosynthesis or artificial intelligence readers 
into the screening programme), as they all detect a different spectrum of disease to current 
screening. Our research will provide some evidence to link spectrum of disease to benefits 
and harms of screening.  
 
Review of existing evidence - How does the existing literature support this proposal? 
In 2016 the US Preventive Services Task Force undertook a comprehensive evidence 
review of the frequency and ages women should be offered breast screening.(10) They 
recommended mammography every two years for women aged 50 to 74 years. The review 
conclusions for screening frequency were based on two observational studies including 
941,938 women from the US.(11, 12) These studies were not able to account for 

 
 
7 
 
confounding, as they did not have information on which screening intervals were shortened 
for clinical reasons. We have this information in the English dataset, along with the exact 
round length in days. Significantly, the US review recommended future research of the type 
we are proposing here, for example examining at what age screening should be 
discontinued, and outcomes from DCIS detection. 
The last review concerning breast cancer screening commissioned by the UK National 
Screening Committee was undertaken by our research group in 2019.(13) This review 
examined whether to make changes to the screening test. This review highlighted that 
additional testing could detect extra cancers, but they tended to be smaller, node-negative, 
lower grade invasive cancers (which have a good prognosis). These are similar to the extra 
types of cancer detected when reducing the recall threshold for mammography(14, 15). The 
review highlighted the research needed to determine whether these would be beneficial in 
terms of reduction of mortality or morbidity, or would represent overdiagnosis.  
This proposed study would be an order of magnitude larger than the studies cited in the UK 
and US reviews, giving sufficient statistical power to investigate important outcomes for the 
woman screened, rather than proxies. We have individual patient data available, with very 
low rates of missing data and loss to follow-up as a result of the standardised software and 
mandatory reporting mechanisms in the English Breast Screening Programme.  
There are previous UK studies which have investigated impacts of recall threshold. Blanks 
and colleagues investigated the relationship between needle biopsy rate (proportion of 
women screened who are recalled for further tests and one of those tests is a needle biopsy) 
and cancer detection rate. (16) They found a positive correlation, with diminishing returns at 
higher rates of biopsy. They did not present data on interval cancers or health outcomes. In 
a similar study Blanks and colleagues investigated the relationship between English and 
Dutch breast screening centres recall rates and cancer detection rates.(14) They concluded 
that increasing recall rates was associated with increasing detection rates of DCIS, although 
this relationship may have been subject to Country level confounding as Dutch recall rates 
were systematically lower. They did not present data on interval cancers. Burnside and 
colleagues found an inverse relationship between recall rate (a proxy for test threshold) and 
rate of interval cancers at UK breast screening centres, equivalent to one fewer interval 
cancer for every 80-84 recalls.(17) Duffy et al. found an inverse correlation between 
detection of DCIS and subsequent interval cancers. (18) All four of these studies were at the 
centre level rather than the individual or reader levels. Our proposed analysis uses data at 
the individual, reader and centre level so there are more units of analysis and we are able to 
adjust for individual or reader level variables. Further, this allows us to design the study 
explicitly considering whether we can make causal inference, whereas previous studies 
simply reported correlations. Finally, none of these previous studies extended analyses 
beyond cancer detection or interval cancer development, to longer term health outcomes, 
which we propose to do.  
There was one randomised controlled trial comparing annual to three-yearly screening in the 
UK. They found no statistically significant difference between the two arms in predicted 
survival using Nottingham Prognostic Index, but the confidence intervals were wide and it 
was underpowered.(19) There is limited evidence from observational studies examining 
different screening frequencies.  
The previous extension of the upper age limit of screening from 64 to 70 is supported by 
women of these ages being included in some of the original RCTs of screening, although the 
balance of benefits and harms by age has mainly been assessed by economic modelling 
relying heavily on assumptions.(21) Screening has a higher cancer yield in older women, but 

 
 
8 
 
also increased risk of overdiagnosis.(21) In a recent survey of 21 countries, all of them 
screened up to at least age 70.(22) Recent advances in causal inference methods for 
observational data have been applied to examining the benefits and harms of colorectal 
cancer screening (20) but we believe we are the first group to propose to apply this 
approach to breast cancer screening. 
 
4. Aims and Objectives 
How does age of eligibility, screening interval and recall threshold affect the benefits and 
harms of breast cancer screening?  
Aims: 
1. To understand how age of eligibility, screening interval, and recall threshold for breast 
cancer screening affect benefits and harms including false positive recalls, overdiagnosis 
and mortality. 
2.  To inform revision of the quality assurance guidelines for breast screening centres based 
on maximising benefit and minimising harm from breast screening 
Work Package 1: Database development and access 
Objective 1: To assemble, clean and assess the quality of the combined datasets 
a. To obtain approvals to re-use the observational dataset of 13 million women 
offered breast screening 
b. To clean data and describe quality 
 
Work Package 2: Causal links between age of eligibility, screening interval, recall 
threshold and health outcomes  
Objective 2: To analyse the causal effect of age of eligibility, screening interval, and recall 
threshold on intermediate outcomes (numbers of breast cancers detected at screening by 
cancer type, interval cancers, false positive recalls) and health outcomes (mortality, 
morbidity, overdiagnosis). 
 
Work Package 3: Pathway to impact 
Objective 3: To apply findings to inform changes to practice, including changes to the NHS 
Breast Screening Programme consolidated standards.  
5. Research Plan/Methods 
The project team brings together direct experience of data linkage and analysis of the 
database (Taylor-Phillips/Clarke/Wallis/Kearins) with internationally renowned analytical 
expertise related to medical tests (Deeks/Sitch) and causal inference from observational 
data (Sterne), observational data quality (Brettschneider), and clinical expertise in breast 
radiology (Wallis/Given-Wilson/Wilkinson) and breast pathology (Pinder). To optimise local 
implementation of findings members/Chairs of English national decision-making groups are 
involved (Given-Wilson/Wilkinson/Taylor-Phillips/Wallis), and the Public Heath England 
national Quality Assurance lead (Kearins), along with implementation science expertise 
(Currie). We work in partnership with Independent Cancer Patients Voices 
(Gath/Radin/Walker) to include the patient voice at every stage. All co-applicants will be 
involved in every work package (and will contribute to study development meetings), the 
lead centre is shown in brackets for each.  
Work Package 1: Database development and Access (Led by Olive Kearins, PHE 
Screening and Sian Taylor-Phillips/Julia Brettschneider, Warwick)  

 
 
9 
 
Main data set (objective 1a): Our research team have already linked breast screening data 
from 80 English centres with English Cancer Registry and civil registration s mortality file 
data for 10 million women attending 35 million breast screening appointments, between 
1988 and 2018 (Taylor-Phillips, POSTBOx, NIHR, 572k). Data were extracted from centres 
up to 2018, but a date cut-off of date of first offered appointment up to end Dec 2016 was 
implemented in the previous data transfer to Warwick (for the previous POSTBOx project). 
The dataset for ATHENA-M will be based on this same database, but with the following 
additional data transferred to Warwick for analysis i. An additional 3 million women, who 
were offered screening but never attended, to enable intention to treat analysis ii. an 
additional outcome of cause of death, in particular breast cancer death. iii. Updated linkage 
to more recent follow-up in cancer registry to end 2018 and civil death registration to date of 
linkage in 2021. This transfer will be in two parts. Firstly, the expanded dataset with the extra 
3 million women, without updating linkages or adding the extra outcome of cause of death. 
This first dataset will ensure there are data available in the event of issues arising in the 
reorganisation of Public Health England. The second transfer will contain updated linkages 
to the cancer registry (to end 2018/2019 as available) and civil death registration (to 2021), 
and extra outcomes of cause of death. Further updates to the database based on later 
extracts from NBSS (post 2016) and updated linkage to civil death registration, cancer 
registry and/or BSselect may be made to ensure these data are as current as possible. 
Summary of requested tables is in appendix 2, and full definition of all variables is in a 
separate document. Inclusion criteria is in appendix 3. This cohort definition gives 2.3 million 
women invited never screened between 1988 and 2016 when aged 47 to 73. These are 
additional to the 10.5 million women with at least one screened episode between 1988 and 
2016 when aged 47 to 73. 
 
 
These data are more complete, and validated than any other breast screening data 
worldwide. They include >35 million screening appointments recalling >2.2 million women, 
detecting >250,000 cancers, with >100 million person-years of follow up to >500,000 
subsequent deaths. Analyses are well powered, (sample size calculations are given in work 
package 2). There are little missing data, for example the radiologist’s decision is missing in 
4,527 (0.01% or 1 in 10,000) episodes, reader identifier is missing in 7,571 (0.02%) 
episodes. Many of these cases of missing data are from the early years of screening, 
between 1988 and 1993).  Data are missing for the outcome of screening (cancer detected 
or not) in 6,992 (0.02%) episodes. Many of these are due to women dying between being 
recalled for further tests and attending for those tests, for these cases we have mortality data 
(which is the outcome in some analyses, and used for censoring in other analyses), so this 
may be an overestimation of data missingness.     
The variables in the current dataset include: 
• 
Details of each screening appointment (pseudonymised centre identifier, 
pseudonymised woman identifier, date (available for every appointment for each woman 
so screening interval is known), whether she attended, the decision of whether to recall 
and the pseudonymised identity of the first reader examining the mammograms, the 
decision of whether to recall and the pseudonymised identity of the second reader 
examining the mammograms, the decision and pseudonymised identity of the arbitrator 
of the decision whether to recall, whether she was recalled for further tests, whether she 
had a biopsy, whether she had cancer detected at screening (from biopsy results), 
whether this episode was part of a trial eg AgeX) 

 
 
10 
 
• 
Details of the woman (identifier to link to every screening episode she was invited to 
between 1988 and 2018, month and year of birth, index of multiple derivation from 
postcode) 
• 
Details of screen detected cancers obtained through linkage to the English Cancer 
Registry (Histological grade, tumour node metastasis (TNM) stage, size, hormonal 
status (oestrogen receptor (ER),progesterone receptor (PR), human epidermal growth 
factor receptor 2 (HER2)), nodal involvement, treatment received (breast surgery, 
axillary surgery, radiotherapy, chemotherapy)) 
• 
Details of symptomatically detected cancers obtained from the English Cancer Registry, 
including interval cancers detected between screening rounds and cancers detected in 
the years after screening (date of diagnosis, histological grade, TNM stage, size, 
hormonal status (ER,PR,HER2), nodal involvement, treatment received (breast surgery, 
axillary surgery, radiotherapy, chemotherapy) 
• 
Date of death (from the civil registrations mortality file, which is populated with data from 
the Office of National Statistics) 
 
We have existing permissions (NHS ethical, office of data release (ODR)) to use the data set 
to analyse the effect of recall threshold on rates of overdiagnosis only. We have already 
combined screening data from all 80 English centres within PHE, completed linkage to the 
Cancer Registry, and MBIS. Full permissions have been granted for transfer of these data to 
the University of Warwick, a contract is in place for the transfer, and transfer of these data is 
complete 
For the ATHENA-M project we will require the following. Firstly, updated permissions from 
ODR and NHSREC to include: extending the analyses to the frequency and age of eligibility 
research questions, to include outcomes beyond overdiagnosis, to extend the cohort to 
women never screened, and to extend the groups authorised to hold these data to include 
Birmingham and Bristol (which will require site specific data security plans). There is a small 
amount of extra data linkage within PHE Birmingham using the same methods as for the 
previous project, to extend the cohort to women never screened and add the outcome of 
cause of death to calculate breast cancer mortality. The data linkage work itself will take less 
than a week as we have pre-existing code from previous projects. It will not require any 
additional data to be extracted from breast screening centres, this was all completed as part 
of the previous project. We have conditional permissions from the Breast Research Advisory 
Committee for ATHENA-M. Approval from this group automatically starts the ODR 
permissions process, so we expect to be close to achieving these permissions by the project 
start date. The ATHENA-M project answers research questions of importance to Public 
Health England, and identified by Public Health England, and so is covered by the existing 
section 251 approvals, and does not require independent section 251 approval. HRA 
approval has been granted (21/LO/0120). 
Data quality and Cleaning (objective 1b): Datasets will be cleaned. Quality assessment 
including data completeness for each item, test for missingness at random, and accuracy vs 
other validated sources will be reported. Other validated sources will include the KC62 
annual Korner returns and the Association of Breast Surgeons (ABS) audit. Changes over 
time, and by centre will also be reported. We will also consider potential misclassification, 
such as the possibility that mortality is more likely attributed to breast cancer in screened 
women. This will be published in a journal article, and internal PHE report.  

 
 
11 
 
Work Package 2: Causal links between Age of eligibility, Screening interval, Recall 
Threshold and health outcomes  
We will define each question by specifying the eligible patients, experimental and 
comparator interventions and outcome for a ‘target trial’ whose results we aim to estimate 
using the observational data.(23) This target trial approach proposed by Hernan and 
colleagues(23) gives a framework to avoid potential biases that would prevent causal 
inference, such as immortal time bias (where the outcome cannot occur during part of the 
follow-up).  
Our comparisons are between different versions of invitations to screening. We have 
carefully considered time varying confounding in our analysis plans. There is a potential for 
time varying confounding if prognostic factors for outcomes of interest influence women 
moving from one treatment group to another over time, and if follow-up for individual women 
is split between treatment groups. Our proposed analyses explicitly account for time-varying 
confounding and use appropriate methods to address it. Importantly, in analyses assessing 
the effect of extra invitations to screening or different screening intervals it is unlikely that 
individual women’s prognostic factors directly affect receipt of invitations (they would by 
contrast affect uptake of invitations, which we do not propose to assess). This is because 
each centre sends invitations to all eligible women regardless of their personal 
characteristics. However, we will examine whether centre level characteristics that may be 
associated with prognostic factors for outcomes of interest also affect invitations to 
screening. We will consider a range of centre level characteristics for potential inclusion, 
such as index of multiple deprivation of population served, arbitration system used, centre 
size, quality assurance region, and quality assurance indicators. 
We will use survival analyses approaches allow for different lengths of follow-up, and will 
adjust standard errors account for clustering by centre,reader/reader pair, and/or screening 
batch where appropriate. Breast cancer treatment has developed significantly and 
associated mortality has decreased. We will therefore adjust for calendar time, using 
smoothing splines, in all time-to-event analyses. 
Screening programmes can exacerbate inequality by lower uptake in lower socioeconomic 
groups. In addition to the main analysis we will evaluate whether the outcomes from the 
evaluated changes to screening age of eligibility, interval and threshold differ by index of 
multiple deprivation (a proxy for socioeconomic status derived from the postcode of the 
woman’s most recent address). We will present results for how each change affects overall 
outcomes, and by groups according to index of multiple deprivation.   
Measuring Outcomes:  
Intermediate outcomes 
1. Interval cancers detected within 3 years of screening. An interval cancer is a cancer 
detected symptomatically in the interval between breast screening appointments. 
These are all biopsy proven, with records taken from the English Cancer Registry. It 
is a binary outcome for each episode of screening for each woman. We will use the 
NBSS data to exclude screen detected cancers from this measure. Interval cancers 
has been identified by the UK National Screening Committee, Public Health England 
and our PPI team as an important intermediate outcome because reducing interval 
cancers is not associated with increasing overdiagnosis in the same manner as 
number of cancers detected.  
2. Cancers detected at screening, taken from the results of screening recorded by the 
Breast Screening Programme in the National Breast Screening Service (NBSS) 

 
 
12 
 
database. It is a binary outcome for each episode of screening for each woman. 
These are all biopsy proven as per screening programme standards. Definition 
includes any invasive cancer or Ductal Carcinoma in situ (DCIS) or Lobular 
Carcinoma in Situ (LCIS) of the breast, using standard definition of cancer registry 
and screening programme) with subgroup with invasive cancer only also reported. 
Records are complete because there are quality assurance mechanisms to ensure 
complete recording of these as part of the standard KC62 reporting procedures. 
3. Screen detected cancer characteristics. This is defined by variables from the English 
Cancer Registry, including histological grade, cancer stage, and cancer size. These 
intermediate outcomes were chosen because the proposed mechanism of action of 
breast screening benefit is through detection of smaller earlier stage cancers. This 
outcome can be difficult to interpret as increased detection may be associated with 
mortality benefit or overdiagnosis harm. This will be measured for screen detected 
cancers only, (and for a combination of screen and symptomatic cancers, where 
differences between exposed and unexposed represents the stage shift of exposure: 
see stage shift outcome). [In detail TNM stage (size, nodes, distant metastases), 
alternative nodal count to match Z11 and POSNOC trials 1/1-2/3+, DCIS vs invasive, 
invasive grade 1/2/3, DCIS grade 1/2/3, DCIS surgical size (mm), Invasive surgical 
size (mm), invasive cancer type, hormonal status, Nottingham Prognostic Index].  
Health Outcomes or close proxies (Primary outcomes) 
1. Breast cancer mortality, as defined by the English Cancer Registry (where the initial 
source is the same but linkage to NBSS data more complete as uses multiple fields 
rather than just NHS number) checked against cause of death from the civil 
registrations mortality file. These sources have limited death data pre-1997, so we 
will also extract deaths data from NBSS to determine whether it can provide 
adequate quality, and if so use pre-1997. It is a binary outcome for each woman, with 
different lengths of follow up. Reported as cumulative incidence over all follow-up 
time, with focus on 10 year and 13 year to match previous systematic reviews.  
2. All-cause mortality for everyone in the included cohort. This is taken from the civil 
registrations mortality file, which is populated by the Office of National Statistics. It is 
a binary outcome for each woman, with different lengths of follow up. Reported as 
cumulative incidence over all follow-up time, with focus on 10 year and 13 year to 
match breast cancer mortality.   
3. Overdiagnosis. Overdiagnosis will be inferred as any difference between the study 
groups in total cumulative incidence of cancer (screen and symptomatic detected) 
after sufficient follow-up (the compensatory drop method). Therefore the outcome 
measured will be difference between groups in sum of breast cancers detected at 
screening and symptomatically. We will carefully consider length of follow-up in 
interpreting results relating to overdiagnosis, as insufficient follow up results in 
overestimation. We will publish a full protocol detailing all analysis methods and 
outcomes before commencing analysis to prevent selective reporting of outcomes or 
other analysis elements. Reported as cumulative incidence over all follow-up time, 
with focus on 10 year and 13 year to match breast cancer mortality.  
4. Stage shift. This is defined by variables from the English Cancer Registry, including 
histological grade, cancer stage, and cancer size. The proposed mechanism of 
action of breast screening benefit is through detection of smaller earlier stage 
cancers. This will be measured for a combination of screen and symptomatic 
cancers, where differences between exposed and unexposed represents the stage 
shift of exposure. [In detail TNM stage (size, nodes, distant metastases), alternative 
nodal count to match Z11 and POSNOC trials 1/1-2/3+, DCIS vs invasive, invasive 

 
 
13 
 
grade 1/2/3, DCIS grade 1/2/3, DCIS surgical size (mm), Invasive surgical size (mm), 
invasive cancer type, hormonal status, Nottingham Prognostic Index]. 
5. Morbidity. Here we are interested in the morbidity associated with breast cancer 
treatment. We measure this as four outcomes: women receiving breast surgery, 
axillary surgery, radiotherapy, and chemotherapy within one year of diagnosis. Each 
of these are binary outcomes for each episode of cancer for each woman.  
6. False positive recalls. These are women recalled from screening for extra tests but 
those extra tests do not indicate cancer. These data are taken from the NBSS 
computer system which automatically records who is recalled. This is measured as 
any women who were recalled but did not have cancer detected in follow up tests. It 
is a binary outcome for each episode of screening for each woman. This is an 
important harm of screening because it is associated with increased anxiety in 
women screened.  
 
We will investigate the mechanism of action linking the three exposures to the outcomes. In 
particular we will investigate the relationship between characteristics of cancer detected, and 
women’s outcomes such as overdiagnosis and mortality and morbidity associated with 
treatment. This analysis has dual purposes: firstly when inferring causation from 
observational research, in addition to appropriate accounting for confounding, it is important 
to elucidate the mechanism of action. Secondly, it is an important research output in its own 
right, to provide the evidence base for policy-makers to link the characteristics of cancers 
detected to benefits and harms of screening, when assessing a range of changes to 
screening. In the UK and Australia this is referred to as the linked evidence approach, and 
the US Preventative Services Task Force refer to it as the dotted line in the analytic 
framework. 
How do two extra invitations to screening between the ages of 65 and <71 years affect 
all-cause and breast cancer specific mortality, overdiagnosis, treatment associated 
morbidity, and false positive recalls, in women already invited to screening age 50-
64? (analysis led by Jonathan Sterne, carried out at Bristol) 
The NHS Cancer plan(4) extended the age range of breast screening in England from 50-64 
years to 50-70 years, which was rolled out across all 80 centres between the years 2000 and 
2006. The first sites to adopt the age extension were those piloting the introduction of the 
assistant practitioner role to assist radiographers in their work, as part of the introduction of 
the four tier workforce.(24) After these pilot sites, timing of roll out to other sites was 
dependent on funding, staffing and extra mammography equipment in place. The provision 
of extra equipment was lottery funded.  
Within the 2000-2006 time period we will compare outcomes in women who were and were 
not offered two extra rounds of screening, adjusting for temporal, centre and individual level 
confounding. We will use the approach described by García-Albéniz et al.,(20) to emulate a 
weekly series of trials in which eligible women who have not yet been offered additional 
screening are assigned to receive or not receive screening in the coming month. Women will 
become eligible for the first trial on their 64th birthday*, and each woman will contribute to 
subsequent trials providing that she remains eligible until the day before she turns 71. We 
will make two sets of comparison: (a) no additional screening compared with one or more 
invitations to additional screening; and (b) at least two additional invitations compared with 
no or one additional invitation. For each weekly trial, follow-up in women in the “less 
screening” group will be censored at the time that receive sufficiently many invitations for 
inclusion in the “more screening” group. We will use inverse probability weights to adjust for 

 
 
14 
 
selection bias introduced by such censoring. Standard errors will be adjusted for inclusion of 
women in multiple weekly trials. Analyses will be by intention to screen, with women included 
in each group regardless of whether they attended screening. We will limit the analysis to 
years in which some centres had and others had not rolled out the screening age extension. 
We will model changes in the rate of each outcome with calendar time using cubic splines. 
Self-referral to screening in the years after screening will attenuate any effect, but fewer than 
12% of women self-refer. *Preliminary investigation will be necessary to ascertain how the 
upper age limit of 64 was implemented, as it may in practice have been until a womans 65th 
birthday 
How does screening intervals of between 15 and 27 months, compared with intervals 
of between 28 and 40 months affect cancer stage at diagnosis, treatment associated 
morbidity, and false positive recalls in women attending breast cancer screening age 
50-70 years? (analysis led by Jonathan Sterne, carried out at Bristol) 
We will use the ‘clone, censor and weight’ approach described by Hernán.(25) Women will 
be eligible if screened between ages 50-70 years, and follow-up will start 15 months after the 
date of first invitation to screening. Follow-up for each woman will be duplicated (‘cloned’), 
with one copy assigned to each treatment strategy. Follow-up for each cloned copy will be 
until women deviate from the strategy assigned that copy, because they are invited to 
screening too late (in the more frequent screening group) or too early (in the less frequent 
screening group). We will model the probability of being screened over time, in order to 
derive inverse-probability of screening weights. Moving house (and screening centre) will be 
included as a covariate, as this can prompt a shorter screening interval. These weights will 
be used to adjust for the selection bias introduced by censoring follow-up at the time of 
deviation from assigned treatment strategy. Planned shorter screening intervals due to 
suspicious findings at baseline will be excluded. 
Additional analyses of will be conducted to investigate whether the effects of screening 
interval on health outcomes vary according to age group at screening (50-60 or 61-70 
years). 
Different definitions of round length will be investigated if time permits. This may include 
women attending family history screening and/or women whose round length was delayed 
by the COVID-19 pandemic.  
How does recall threshold affect all-cause and breast cancer specific mortality, 
overdiagnosis, treatment associated morbidity, and false positive recalls in women 
attending breast cancer screening age 50-70 years? (analysis led by Jon Deeks and 
Sian Taylor-Phillips, undertaken at Birmingham and Warwick [Taylor-Phillips and 
Freeman working across both universities]) 
We will estimate the effect of screening threshold, using instrumental variable approaches or 
other analyses with consideration of causal inference. The exposure or instrumental variable 
will be the rate of recall of the previous 5000 cases screened by the reader (or reader pair). 
The readers’ recall rate for previous cases may be an appropriate instrumental variable to 
because its effect on the outcome (for the current case) is only via the readers’ threshold for 
the current case. This assumption will be evaluated. Instrumental variable definitions will be 
finalised in preliminary analyses that aim to maximise their association with recall probability, 
in datasets from which all outcomes have been removed. At this stage we will consider 
different numbers of previous cases to inform the instrumental variable definition. 5000 
represents the mandated minimum per year for each reader, according to English quality 
assurance guidelines(26) and would give a reasonably precise estimate of recall threshold (if 

 
 
15 
 
the reader recalled 4% of cases the 95% binomial exact CI is 3.5% to 4.6%). We know there 
is substantial inter-reader variability in recall threshold, and intra-reader temporal changes 
(changes within a single reader over time) are much smaller, justifying increasing the 
number of previous cases to reduce statistical variability in the instrumental variable. We will 
conduct sensitivity analyses to assess whether results are robust to changes in the 
instrumental variable definition. We have data for a full range of thresholds for every year 
since 1988, and therefore have sufficient data to adjust for temporal changes. We will model 
changes in rates of outcome with calendar time using cubic splines. 
Three models will be developed for three time horizons (shown in brackets): 1: The effect of 
threshold at the final screening round (27 years) with adjustment for previous attendance 
record, so follow-up is not contaminated with screening invitations. 2: The effect of threshold 
in a screening round (3 years), adjusting for clustering of screening episodes within women, 
the women’s age at screening, and previous attendance patterns, with outcomes limited to 
false positive recalls, interval cancers, and stage of cancer detection. 3: If feasible, the 
cumulative effect of threshold over all screening rounds including the woman’s entire 
screening history and follow-up post screening (27 years) 
Modern mammography screening in England uses two readers and arbitration of discordant 
assessments. Any subsequent intervention to change the recall threshold would most likely 
act upon each individual reader. We will use modelling approaches to evaluate the impact of 
test threshold on screening outcomes; we will investigate the impact of changing the process 
(adjusting the threshold of both readers), changing the threshold for an individual reader, the 
impact of one vs two readers, changing the threshold for one or both, and the pairing of 
readers. We will use instrumental variables to describe the recall threshold of each reader, in 
these proposed models. We will also model the overall effect of changing recall threshold, 
using a predictor for the single readers decision in the older cases where there was only one 
reader, and the reader combination’s combined threshold in later years. This will show the 
relationship between the recall threshold of the system and women’s outcomes.   
We will investigate the mechanism of action of any effects, through intermediate outcomes. 
For example we expect that reduced recall threshold may increase cancer detection but 
change the spectrum of disease identified towards more small cancer detection (possibly of 
low histological grade) and also DCIS, which may in turn affect mortality and overdiagnosis. 
This will help our understanding of what we should aim to detect at breast screening.  
A further exploratory analysis of instrumental variable approaches to recall threshold 
specifically for DCIS will be undertaken, as DCIS is detected predominantly through 
microcalcifications, and there is vigorous debate about the benefits and harms of detecting 
DCIS.  
We will also investigate the variability between centres and readers, and its implications for 
screening QA targets.  
Additional analyses of will be conducted to investigate whether the effects of recall threshold on 
health outcomes vary according to age group at screening (50-60 or 61-70 years). 
Sample Size Requirements 
This observational data analysis does not require a formal sample size calculation. We will 
include every eligible case within the available cohort in analyses. However, we have 
included some calculations here to ensure that there are sufficient available data to enable 
meaningful analysis. Previous analyses have shown clustering of the proposed outcomes 
within centres and readers is negligible (ICC<<0.0001), hence the cluster of observations is 

 
 
16 
 
not accounted for in these calculation; however, we will adjust for these in the analyses 
where appropriate. 
Table 1. Sample size requirements for detecting differences within the dataset. All 
calculations are for 90% power at 5% significance level. There are more than 30 million 
screening appointments in the dataset, from more than 10 million women.  
Outcome  
Baseline value 
Change in value 
Number required in 
each group to detect 
Intermediate outcomes 
Recall rate 
3.9% 
0.1% 
777,920 
Cancer detection 
rate at screening 
8.4/1000  
0.5/1000 
679,499 
Small invasive 
cancer detection 
rate at screening 
3.4/1000  
0.3/1000 
756,401 
Interval cancer over 
3 years 
2.9/1000  
0.3/1000 
640,353 
False positive 
recalls  
3.1%  
0.1% 
641,114 
Health outcomes 
All-cause mortality 
0.6050 per 100 
person-years 
0.6025 per 100 
person years 
804,400 
Breast Cancer 
mortality 
0.0443 per 100 
person years 
0.0433 per 100 
person years 
880,116 
Overdiagnosis 
1.3% of women 
invited for screening 
for 20 years(1) 
0.1% 
279,869 
 
We will deliver three journal articles, one for each of the three questions investigated: age of 
eligibility; recall threshold and round length. We will submit a fourth journal article exploring 
the link between detection of different cancer types and outcomes, with a focus on DCIS in 
particular. We will also present results to the UK National Screening Committee, and inform 
redrafting of the English national quality assurance standards for breast screening (see work 
package 3). 
Work Package 3: Pathway to impact (Led by Olive Kearins, PHE and Sian Taylor-
Phillips, Warwick) 
In addition to journal publication there are three strands to our dissemination strategy. 1. 
Influencing national policy directly via the UK National Screening Committee 2. Influencing 
national practice through national professional guidance and communication to health 
professionals 3. Communication to the public 
1. Influencing national policy directly via the UK National Screening Committee (UKNSC) 
The UK National Screening Committee is responsible for all national screening policy, 
including making major changes to screening programmes such as age of eligibility or 
frequency of screening. We will present our results in person to the UK National Screening 
Committee Adult Reference Group (ARG) which is responsible for all adult screening 
programmes (on which Professor Taylor-Phillips sits). If our results suggest that a major 
change is appropriate then we will submit a formal request via the annual call or directly to 
the ARG, and the UKNSC would then undertake a systematic review putting our research 
into context and make a national decision on that basis. These decisions are directly 

 
 
17 
 
nationally implemented with associated budget so encounter fewer barriers to 
implementation than guidelines. 
We will provide evidence on how the changes would affect the benefits and harms of 
screening overall, and on how the changes would differentially affect women of different 
socioeconomic status (using our analysis of a proxy for this, Index of Multiple Deprivation). 
This will allow the UK NSC to consider the implications of any decision on inequalities, as 
required by UKNSC criterion 12. (There should be evidence that the complete screening 
programme (test, diagnostic procedures, treatment/ intervention) is clinically, socially and 
ethically acceptable to health professionals and the public). 
The UK National Screening Committee will be involved throughout the process, with 
Professor Bob Steele (UKNSC chair) and Professor Anne Mackie (Director of PHE 
Screening) joining our national policy advisory group, Dr Ros Given-Wilson (Chair of ARG) a 
co-applicant, and regular written updates given to key personnel such as John Marshall 
(PHE Screening evidence lead). Letters of support from Professor Steele and Professor 
Mackie are attached (appendix 1) 
2. Influencing national practice through national professional guidance and communication to 
health professionals 
If our research were to suggest that there is a need to reduce variability in screening 
intervals, or change test threshold this would be implemented through national professional 
guidance, changes to the breast screening programme specific operating model,(27) and 
influencing changes to practice. Here Professor Graeme Currie (Professor of Implementation 
Science, co-applicant) is advising on strategies to maximise implementation. Our approach 
will be: 
i. 
To engage in the process of redrafting the national professional guidance,  
ii. 
To identify and engage national champions for practice change who will drive change 
through their networks.  
Redrafting the national professional guidance: Our findings will be used to inform the regular 
update of the NHS Breast Screening Programme Consolidated standards, and the 
Professional Guidance for Breast Cancer Screening Radiology (objective 3, led by Olive 
Kearins, Breast Screening Research & Data Lead, PHE Screening). These are used by 
commissioners to develop the service specifications when commissioning breast cancer 
screening, by the screening QA service to inform quality interventions and by radiologists in 
assessing their own performance. We will use the findings from objectives 1 to 3 to propose 
changes to quality metrics to align with maximising benefit and minimising harm, cognisant 
of effects on inequalities (via the Index of multiple deprivation proxy), and of statistical 
variability and the need to define targets measurable every year at each centre. Our analysis 
of threshold will inform consideration of targets for recall rate (currently <5%), invasive 
cancer detection rate (currently ≥5.7/1000), small cancer detection rate (currently≥3.1/1000), 
DCIS detection rate (currently ≥0.6/1000, all for previous attenders), and round length 
(currently 3 years). (26, 28)   PHE are implementing a live data monitoring system, so 
centre-level performance towards QA targets can be measured. PHE will consult widely in 
developing revised guidance and standards, engaging a wider range of practitioners to 
identify practical issues, misunderstandings, attitudes, and context from a wider range of 
stakeholders including radiologists who are less research-involved, and radiographers, 
pathologists, breast clinicians, breast care nurses, administrative staff and centre managers.  
Whilst the guideline development is led by Public Health England, implementation through 
commissioning is the responsibility of NHS England. Jeff Featherstone, Head of Public 

 
 
18 
 
Health Commissioning and Operations for NHS England and NHS Improvement, and Cath 
Fenton (regional NHS England) will sit on our advisory group. They will advise early 
throughout the study on how practice may be influenced through commissioning, including 
barriers and enablers.  
Identify and engage national champions for practice change: Our strategy focuses on a no-
surprises approach, engaging national champions early, engaging in two-way dialogue 
designed to maximise practical usefulness of results, and ownership and understanding of 
results in national champions. The co-applicants on this proposal are the first set of national 
champions, who are opinion leaders in their fields and sit on the national decision-making 
bodies. Co-applicants will work with colleagues through national groups and beyond 
adapting and optimising the communication strategy to communicate to their peers, and 
receive feedback at every stage of the research. The groups we will involve include the 
English Breast Clinical Advisory Group (Wallis/Given-Wilson/Taylor-Phillips/Kearins/Pinder 
members), the Clinical and Professional Groups for Breast Radiology (Given-
Wilson/Wilkinson member), Radiography, administration, Breast Care Nursing and Surgery, 
the National Co-ordinating Committee for Breast Pathology (Pinder Chair) and the Breast 
Screening Advisory Committee (Wilkinson Chair), NHS England Breast Screening 
Programme Board (Kearins member) as well as to the internal PHE Breast Screening Joint 
Action Meeting (Kearins member). 
We will hold a workshop at the beginning and end of the project for national champions and 
key stakeholders. We will approach stakeholders through the existing national programme 
advisory network, at national conferences and regional breast screening professional 
network meetings, using the study teams extended networks, and via direct communication 
to the director of breast screening at each English Centre. We will engage a wide range of 
stakeholders using these methods, and expand our team of national champions.  
The benefits and harms of breast cancer screening is a controversial area with substantial 
debate around research methods. We will contact prominent methodologists and 
researchers with a range of views about breast screening at a very early stage. We will seek 
feedback on our protocol, and engage with them in order to maximise the probability of 
acceptance within the scientific communities involved.  
3. Communication to the public 
We recognise that communication to the public will be challenging as this is a complex, 
controversial and emotive topic. Previous studies have used citizen’s juries to engage 
members of the public for a prolonged period to give them time and resources to understand 
the complex benefits and harms of breast screening.(29) This has been successful, but has 
demonstrated that success in this context requires large amounts of people’s time and 
significant financial resources,(29) and is beyond the scope of this project. In this context our 
objectives for communication to the public are firstly to clearly communicate how and why 
we are using women’s data, and secondly to minimise the chances of misunderstanding of 
our results.  
Communicating how and why we are using women’s data. The PPI team will lead the design 
of a poster to send to all breast screening units to advise how data is used, direct them to 
the study website, and include details of how to opt out of future research, all from the 
patient’s perspective. The co-applicants (Kearins/Wallis/Wilkinson/Given-Wilson) will assist 
with accuracy of content. The ATHENA-M website will be co-produced between 
ProfessorTaylor-Phillips, the PPI team, and the co-applicants. It will include sections 
targeted at clinicians and the public. Example content will be stories explaining why the 
research is important from different perspectives such as the PPI team and clinicians, how 

 
 
19 
 
people’s data has been used and the ethical aspects, and findings as they emerge. This 
same content will be linked to the Independent Cancer Patient Voices website. 
The possibility of misunderstanding our results will depend on the results themselves. For 
example, if our results suggest that the previous expansion to age 70 significantly increased 
the harms of breast cancer screening with few benefits there is potential for press attention 
and sensationalism. A potential misunderstanding would be that this means that women 
should not attend screening at all. To reduce these risks our strategy will emphasise 
maintaining control of the messaging, focusing on core messages which have been tested to 
minimise the chances of misunderstanding. ProfessorTaylor-Phillips will lead the science 
communication, with our PPI team and radiologist co-applicants communicating what this 
means for patients and the NHS. We will work closely with University of Warwick and PHE 
communications team during the project, to synchronise messages, as we have for previous 
projects. The University of Warwick also has an established relationship with the Science 
Media centre (an independent organisation aiming to make coverage of science more 
balanced), and they can assist with expert reaction to controversial stories. The core 
messaging will be centred on improving breast screening accuracy using 30 years of NHS 
experience. We will work extensively with Warwick University PPI volunteers (a large and 
diverse group of members of the public) and with members of Independent Cancer Patients’ 
Voice (ICPV) to reduce the possibility of misunderstanding, or unforeseen consequences of 
our communication with people who are not familiar with the project. In this process we will 
seek a broad range of perspectives from groups of different ages, sex, ethnicity, and 
education. We will take particular care when communicating results concerning inequalities.   
 
 
 
 
 
Study Management 
The project timings are shown in the gantt chart below: 

 
 
20 
 
 
 
There will be monthly project management meetings within each University individually. All 
three universities will meet at least every 3 months via online meeting space. All co-
applicants and team members will meet in person annually.  
ProfessorTaylor-Phillips will lead the project and provide overall management. She will be 
mentored in this by Professor Aileen Clarke and Professor James Mason, both of whom 
have extensive experience in delivering large research projects across several universities. 
ProfessorTaylor-Phillips is already mentored by Professor Janet Dunn, Professor of Cancer 
Clinical Trials at Warwick Clinical Trials Unit.    
There will be a postdoctoral research fellow at each of Warwick, Birmingham and Bristol 
Universities to carry out the work. Work package 1 will be undertaken primarily at Warwick, 
with support from Public Health England. Work package 2 analyses of age extension and 
screening interval will be undertaken at Bristol. Work package 2 test threshold will be 
undertaken primarily at Birmingham. However analysis of the overdiagnosis outcome will be 
led by ProfessorTaylor-Phillips and Karoline Freeman from Warwick. Professor Taylor-
Phillips already works part time at Birmingham and Karoline Freeman holds an honorary 
contract there so it is an established collaboration. Work Package 3 will be led by Warwick 
with heavy involvement from Public Health England and all co-applicants.  
There will also be a member of administrative staff employed at Warwick University 
responsible for coordinating the work between the three universities and Public Health 
England, and assisting with the administrative tasks involved in achieving all of the 
necessary approvals and documentation required in routine data projects.  
There will be a policy and practice advisory group who meet in person every year. They will 
guide the research to maximise policy and practice relevance, and guide work package 3. 
We will also report progress updates to this group.  
 
Phase
Project Month
1
2
3
4
5
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36
Calendar Month
J
F
M
A
M
J
J
A
S
O
N
D
J
F
M
A
M
J
J
A
S
O
N
D
J
F
M
A
M
J
J
A
S
O
N
D
Approvals and set-up
Milestone 1 (NHS ethics approvals)
x
Milestone 2 (ODR approvals and contract signed with PHE)
x
x
Milestone 3 (Subcontracts Bristol and Birmingham signed)
x
Milestone 4 (Breast Research Advisory Committee approval conditions met)
x
Milestone 5 (Project administrator recruited)
x
x
Milestone 6 Data Transfer to Warwick
x
x
Work Package 1: Data cleaning and quality
Milestone 7 Single database created
x
x
Milestone 8 Data cleaning complete
x
x
x
x
x
Milestone 9 Data quality paper submitted to journal
x
Milestone 10 Database transferred to Bristol and Birmingham 
x
Work Package 2: Analysis
Milestone 11 Research Fellow employed at Bristol and Birmingham 
x
Milestone 12 Protocol Publication
x
Milestone 13 Analysis of screning age complete
x
x
x
x
x
x
Milestone 14 Analysis of screening interval complete
x
x
x
x
x
x
x
x
Milestone 15 Analysis of test threshold complete
x
x
x
x
x
x
x
x
x
x
Milestone 16 Submission of 3 journal papers
x
x
x
Work Package 3: Dissemination
Milestone 17 Policy and Practice Advisory Groups
x
x
x
Milestone 18 Website online and linked / results added
x
x
Milestone 19 Workshop for national champions
x
x
Milestone 20 Poster sent to breast screening units
x
Milestone 21 Presentation of research plan /results to all national meetings
x
x
Milestone 22 Presentation of results to UKNSC ARG meeting
x
Milestone 23 Recommendation of changes to breast screening quality assurace 
documents development and presented to group responsible for redraft
x
x
x
x
x
Milestone 24 Final report complete
x
x
x
Milestone 25 Public Dissemination complete
x
2021
2022
2023
Project Set-UpWork Package 1: Data preparation
Work package 2: Analysis
Work Package 3: Dissemination

 
 
21 
 
Appendix 1 – Letter of Support [redacted] 
 
 
 
Appendix 2: Data requested and reason 
 
 
Table 1: National Breast Screening Research Dataset (NBSRD) Patient Demographics 
data to be provided to the applicant in accordance with the cohort inclusion and 
exclusion criteria. 
To include one row per woman included, with pseudonymised identifiers to link between 
tables, with ethnicity, month and year and cause of death, month and year of birth, 
participation in relevant research trials, and issues with data quality of NHS number.  
Table 2: National Breast Screening Research Dataset (NBSRD) breast screening 
episode data for routine population screening episodes to be provided to the 
applicant in accordance with the cohort inclusion and exclusion criteria 
To include one row per screening episode, with pseudonymised identifiers to link between 
tables, screening date, pseudonymised identifiers for the radiologists examining the 
mammograms, their decisions, whether the woman was recalled for further tests, whether 
cancer was detected.  
Table 3: National Breast Screening Research Dataset (NBSRD) mammographic 
features to be provided to the applicant in accordance with the cohort inclusion and 
exclusion criteria.   
Details of mammographic features associated with detected cancers. Data will be provided 
for screen detected breast tumours only. Features to include side of the body, 
mammographic characteristics such as mass or calcifications.  
Table 4:  National Breast Screening Research Dataset (NBSRD) cancer tumour data to 
be provided to the applicant in accordance with the cohort inclusion and exclusion 
criteria.  
Tumours will be limited to C50 (breast cancer) or D05 (Breast DCIS or LCIS) records, or the 
pre-1995 equivalents in of ‘174’ and ‘2330’ respectively, only, inclusive of both screen 
detected and symptomatically detected breast tumours. Includes ICD classification, 
morphology, behaviour, grade, size, number of involved nodes, oestrogen, progesterone and 
HER2 status, Nottingham Prognostic Index, TNM stage, and whether screen detected.  
Table 5:  National Breast Screening Research Dataset (NBSRD) cancer treatment data 
to be provided to the applicant in accordance with the cohort inclusion and exclusion 
criteria.  
Treatment detailed will be restricted to records for the treatment of C50 or D05, or the pre-
1995 equivalents in of ‘174’ and ‘2330’ respectively, (inclusive of screen detected and 
symptomatically detected breast tumours). Includes all events those occurring within the first 
365 days from DATEOFDIAGNOSISBEST. All other event dates will be excluded. Treatment 
includes chemotherapy, radiotherapy and surgery.  

 
 
22 
 
Table 6: National Breast Screening Research Dataset (NBSRD) derived ‘First Event’ 
data to be provided to the applicant in accordance with the cohort inclusion and 
exclusion criteria.  
Events will be restricted to first procedure NCRAS is aware of for a C50 or D05, or the pre-
1995 equivalents in of ‘174’ and ‘2330’ respectively, within the first 365 days from 
DATEOFDIAGNOSISBEST. All other event dates will be excluded. Datasources include 
registration data supplemented with SURGERYETC and OTHERPROCEDURES; HES; 
SACT; RTDS. 
All dates and events for this table to be taken from multiple sources as described in the 
‘Custom fields’ tab of the data dictionary. Includes breast surgery (breast conserving, 
mastectomy) underarm surgery (axillary clearance, sentinel lymph node biopsy), hormone 
therapy, radiotherapy, chemotherapy. 
Table 7: National Breast Screening Research Dataset (NBSRD) breast screening 
episode data for non-routine screening episodes (high risk, GP/self-referral, non-
routine recall) to be provided to the applicant in accordance with the cohort inclusion 
and exclusion criteria 
To include date of any appointments for mammography which were not defined as screening 
appointments, such as GP referral.  
Table 8: IMD Score – to be based upon last known address in both NCRAS and NBSS.  
Index of multiple deprivation for woman’s last known address only.  
Table 9: Cause of date from the civil registration mortality file.  
Month and year of death and cause for main study outcome. Cause primarily to separate 
breast cancer death from other causes, with sensitivity analyses defining this using 
combinations of underlying and secondary cause. ICD10 code C50 in underlying cause is 
main indicator for breast cancer detch. However ICD10 code C76 multiple cancers may 
include some breast cancer detahs, to check this will use ICD10 secondary cause, and refer 
death certificate data death cause code 1a,b,c and 2 to clarify.  
Table 10 Cause of death from cancer registry 
Month year and cause of death from the cancer registry, to check data quality of data from 
civil registration mortality file (where quality may have been limited by only linking on NHS 
number).  
Table 11 Reference table with no data to extract 
Table 12 
Should the analysis expand in mutual agreement between members of the study team from 
Public Health England and Warwick, the following variables may also be required. Tumour 
histories of other (non-breast) cancers in women in the included cohort (as a potential 
confounder to the analysis). HES data providing additional detail of the morbidity associated 
with overdiagnosis and overtreatment (eg cardiac toxicity) and Charleston co-morbidity index 
(to characterise the population affected by overdiagnosis). Endocrine treatment data (not 
currently available as dispensed from community pharmacy, but linkage into cancer registry 
underway). Description of genomic characteristics of the cancer, which alongside other 
characteristics such as grade and stage may be important for predicting the benefits and 
harms of detecting each type of cancer in the mechanism of action analysis. 

 
 
23 
 
 
 
 

 
 
24 
 
Appendix 3 Inclusion criteria 
Women need an episode record (ODR Table 2) with date of first offered appointment 
(DOFOA) and age at DOFOA recorded and at least 1 demographics record (ODR Table 1) 
in order to be selected for the ATHENA-M cohort. So the ATHENA-M proposed cohort we 
are currently working towards is as follows (all dates are given for main project extract, there 
may be an initial extract with earlier dates and a subsequent extract with updated dates): 
Women invited to routine population breast cancer screening in England from screening 
programme inception in 1988 to December 31st 2016, who:  
              (i) Were aged 47 – 73 years at their routine screening invitation 
(ii) Have at least one demographics record, required for linking 
The inclusion criteria by table are as follows (again for the main project extract) 
• 
Table 1: NHS National Breast Screening Programme (Patient Demographics) NBSS 
data will be restricted to women meeting the inclusion criteria.  
• 
Table 2: NHS National Breast Screening Programme (routine episode) data will be 
restricted to women in Table 1. Records with no invitation to screening will be 
excluded from Table 2. Table 2 will be restricted to records with date of first offered 
appointment either (i) null or (ii) from screening programme inception in 1988 to 
31/03/2018. 
• 
Table 3: NHS National Breast Screening Programme (assessment procedures - 
mammographic features) NBSS data will be restricted to women in Table 1 and 
episodes in Table 2.  
• 
Table 4:  Cancer Registry data will be restricted to C50x or D05x records, or the pre-
1995 equivalents in of ‘174’ and ‘2330’ for all women identified in Table 1, 
irrespective of whether the tumour was screen detected, where 
DATEOFDIAGNOSISBEST is between 01/01/1988 and 31/12/2018. 
• 
Table 5:  Cancer Registry data will be restricted to events linked to the tumours 
identified in Table 4 and where the event occurs within the first 365 days from 
DATEOFDIAGNOSISBEST and the OPCS4_CODE is identified in Table 10: 
Reference table OPCS4_codes. All other event data will be excluded. 
• 
Table 6: Cancer Registry Derived ‘First Event’ data restricted to first procedure of 
each type the Cancer Registry is aware of for a C50x or D05x or the pre-1995 
equivalents in of ‘174’ and ‘2330’ respectively, within the first 365 days from 
DATEOFDIAGNOSISBEST in Table 4. All other event data will be excluded. Data 
sources include registration data supplemented with SURGERYETC and 
OTHERPROCEDURES; HES; SACT; RTDS. All dates and events for this table to be 
taken from multiple sources as described in the ‘Custom fields’ tab of the data 
dictionary. 
• 
Table 7: NHS National Breast Screening Programme (non-routine episode) data from 
BS Select will be restricted to women in Table 1. Records with no invitation to 
screening will be excluded from Table 7. Records in Table 7 will be restricted to 
records with date of first offered appointment either (i) null or (ii) from screening 
programme inception in 1988 to 31/03/2018 
• 
Table 8: IMD Score data will be based upon last known address in NBSS. 
• 
Table 9: MBIS civil registration mortality data be provided for all women identified in 
Table 1 and recorded in MBIS as deceased, updated in 2021. 
• 
Table 10: NCRAS death data to be provided for all women identified in Table 4 and 
recorded in NCRAS as deceased