Research

Question 1

Professor David Cromwell (Director of the Clinical Effectiveness Unit)

Answer 1

• PROFESSOR OF HEALTH SERVICES RESEARCH
• I studied mathematics at Warwick University before completing a Masters degree in Operational Research at Lancaster University. On graduating, I had various analytical jobs in health care organisations in the UK, the Netherlands and Australia. For 10 years, I was a researcher at the University of Wollongong, Australia, undertaking projects on various topics, including health care financing, and the coordination of care. I gained my PhD while at Wollongong. Before joining the LSHTM, I worked at the UK Healthcare Commission.
• On the Public Health MSc, I am the organiser of Healthcare Evaluation and a seminar leader for Health Services. I also teach on courses about critical appraisal of the literature and statistics for The Royal College of Surgeons of England.
• I am interested in supervising research degree students who wish to investigate how best to evaluate the performance of health services (notably surgery) using observational data (such as clinical or administative databases).
• My research interests sit under the broad heading of improving the quality and use of information in the delivery of health care. This has involved developing quantitative models to aid health care management, evaluating health-related information systems, and undertaking statistical analyses to inform quality improvement initiatives or policy decisions. My current position as Director of the Clinical Effectiveness Unit of The Royal College of Surgeons of England means this general interest now focuses on issues related to evaluating the effectiveness of surgery.

Question 2

The Royal College of Surgeons of England research papers

Answer 2

• Patient and tumour factors affecting the receipt of breast surgery in older women with ER-positive or ER-negative early invasive breast cancer in England and Wales. 2021.

Question 3

What department will this role sit within?

Answer 3

National Cancer Audit Collaborating Centre (NATCAN) within the Clinical Effectiveness Unit (CEU) jointly run by the Royal College of Surgeons of England (RCS) and the London School of Hygiene and Tropical Medicine.

Question 4

Who will I be accountable to?

Answer 4

Julie Nossiter (Director of Operations, NATCAN) and David Cromwell (Director of the Clinical Effectiveness Unit)

Question 5

Aim of role

Answer 5

To help strengthen NHS cancer services and reduce variation in care.

Question 6

What will the multidisciplinary teams look like?

Answer 6

Statisticians/data scientists, senior cancer specialists, clinical fellows and project managers, who together deliver national cancer audits and carry out research.

Question 7

What will the data look like?

Answer 7

Large detailed linked datasets

Question 8

What opportunities does the availability of large detailed linked datasets present?

Answer 8

Opportunities to be involved in methodological development and in epidemiological studies assessing the quality of care and answering the most pressing questions about why some cancer patients receive different treatments and outcomes than others.
There will be opportunities to answer really important questions about how to improve the quality of cancer care, and to develop the methods that we use for these national studies.

Question 9

What are the broad categories of duties and responsibilities of this role?

Answer 9

1. Statistical analyses for national cancer audits and research projects
2. Data management and provision of automated reporting across cancer audits
3. Data access and Information Governance (IG)
4. Development and training

Question 10

Dr Julie Nossiter (Director of Operations, NATCAN)

Answer 10

Julie Nossiter is Audit Lead for the National Prostate Cancer Audit (NPCA), based at the Clinical Effectiveness Unit, an academic collaboration between The Royal College of Surgeons of England and the Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine (LSHTM). Julie’s research focuses primarily on evaluating the performance and quality of prostate care services in England and Wales using patient-reported outcome measures linked to patient-level data from large clinical and administrative databases.

Question 11

What types of cancer will NATCAN audit?

Answer 11

NATCAN will deliver five new national cancer audits in breast cancer (primary and metastatic), ovarian, pancreatic, non-Hodgkin lymphoma and kidney cancer.

Question 12

What does the Clinical Effectiveness Unit do?

Answer 12

The CEU currently delivers clinical audits in prostate, lung, bowel, oesophageal and stomach cancer, and recently completed an audit of breast cancer in older patients. These audits have helped provide a wider understanding of cancer treatments across England and Wales, and improve outcomes for patients. They have also promoted improvement initiatives within NHS cancer services and identified areas of best practice.

Question 13

What will be the aims of the new audits?

Answer 13

The aim of these audits will be to:

-Provide regular and timely evidence to cancer services of where patterns of care in England and Wales may vary.
-Support NHS services to increase the consistency of access to treatments and help guide quality improvement initiatives.
-Stimulate improvements in cancer detection, treatment and outcomes for patients, including survival rates.

Question 14

What have the existing cancer audits done?

Answer 14

Professor Neil Mortensen, President of the Royal College of Surgeons of England said: “Over the past 15 years, our national clinical audits have shone an important spotlight on NHS cancer care across England and Wales, helping NHS hospitals to improve their services for patients.

Question 15

Public engagement

Answer 15

NATCAN will collaborate closely with professional groups and patient charities. Patient forums will be established to ensure that patients inform the quality improvement goals of each audit. The audits are committed to engaging widely with charities and experts involved in cancer care, delivering for patients and their families, as well as healthcare professionals and the health service.

Question 16

What is a key aim for each audit?

Answer 16

Cancer treatment is complex – there are multiple treatment options for different types of cancer. A patient’s treatment plan needs to take into account the stage of their cancer and how they will respond to treatment. A key aim for each audit will be to ensure the information produced for cancer services recognises these differences and supports hospitals to focus on specific parts of the care pathway.

Question 17

Dr Julie Nossiter (Director of Operations, NATCAN) Papers

Answer 17

• Impact of the COVID-19 pandemic on the diagnosis and treatment of men with prostate cancer.
• Robot-assisted radical prostatectomy vs laparoscopic and open retropubic radical prostatectomy: functional outcomes 18 months after diagnosis from a national cohort study in England.

Question 18

What does NATCAN stand for?

Answer 18

National Cancer Audit Collaborating Centre

Question 19

What sort of statistical analyses do you think you’ll be involved in?

Answer 19

Statistical analyses for national cancer audits and research projects
In collaboration with other team members, the post holders will design and carry out statistical analyses for national cancer audits and research projects using linked national cancer and administrative datasets. They will deal with methodological issues that arise, such as handling missing data, incomplete data linkage, or the censoring of individuals in time-to-event data, and the development of risk-adjustment approaches for making fair comparisons between organisations. Areas of statistical analysis work will include, for example:
* Describing the cancer care and outcomes across different NHS organisations
* Examining how different patterns of care may influence patient outcomes
* Conducting analyses to support quality improvement initiatives

The post holder will be expected to work collaboratively within multidisciplinary teams and be able to communicate the methods and findings of analyses to a medical and lay audience. They will be expected to present their analyses in seminars, and write up their findings for inclusion in project reports, academic journals and conference presentations.

Question 20

What data management and provision of automated reporting will you be involved in?

Answer 20

Data management and provision of automated reporting across cancer audits
The delivery of six new cancer audits brings the opportunity for highly efficient working across audits. The post-holders will be required to actively seek potential areas for cross-audit working in data preparation, analysis methods and reporting. Accurate documentation of data extraction, cleaning, validation and indicator production will be crucial. Areas contributing to the aspiration of efficient cross-audit working will include:
* Extracting, wrangling and curating large scale linked clinical datasets ready for analysis using SQL or statistical software
* Developing and applying reusable data pipelines and applying algorithms and code lists to derive required variables
* Developing and performing systematic data quality checks across and within projects
* Producing automated reports, dashboards and data visualisations to support local quality improvement

Question 21

How will you be involved in data access and Information Governance?

Answer 21

• Supporting the Operations Director with data access requests
• Developing and maintaining processes to ensure that data access, management and analysis activities take place within a robust data sharing and information governance framework that meets legal IG requirements
• Liaise with RCS Data protection Officer (DPO) to ensure projects comply with RCS information governance policies and other statutory requirements

Question 22

How will you be involved in development and training?

Answer 22

• Contribute to training material for technical and non-technical staff on data management and the application of statistical techniques
• Undergo further training in statistics, data science, research and audit methodology
• Keep abreast of and adapt to changes in the national cancer data landscape, and developments in presenting and disseminating statistical information (e.g. dashboards and control charts) to hospitals.

Question 23

What other duties and responsibilities may you have?

Answer 23

• Maintaining the confidentiality of data at all times and to ensure that the requirements of the Data Protection Act are met throughout the work of the National Cancer Audit Collaborating Centre
• Ensuring that data collection, analysis and reporting is carried out to the highest professional standards
• Carrying out other occasional duties within the National Cancer Audit Collaborating Centre and the CEU, e.g. contributing to training workshops

Question 24

RCS Values: Collaboration

Answer 24

We embrace our collective responsibilities working collaboratively and as one college.
* We work together, using our collective expertise and experience to effect positive change
* We are open, honest and transparent, straightforward in our language and actions, acting with sincerity and delivering on our commitments
* We take our responsibilities to each other, to patient care and to the environment seriously and we act with this in mind across our work

Question 25

RCS Values: Respect

Answer 25

We value every person we come into contact with at the College as an individual, respect their aspirations and commitments in life, and seek to understand and meet their physical and wellbeing needs.
* We treat everyone we meet with kindness and integrity and we seek to promote these behaviours in others
* We actively seek a range of views and experiences across our work, and we listen to, and make everyone feel, a valued part of the team

Question 26

RCS Values: Excellence

Answer 26

We aspire to excellence and success. We share learning from our experiences, apply feedback into practice, and commit to continual improvement.
* We work hard to be the best at what we do, recognising and celebrating effort and achievement, and reflecting on our work, so we can learn and improve
* We value and invest in research, education and training to drive excellence and put improvements in surgical practice, dentistry and patient care at the heart of our work
* We always seek to learn and discover more, valuing knowledge and scientific evidence, basing our decisions on insights, fact and experience

Question 27

Who will work at and led the centre? (NATCAN)

Answer 27

The Centre will have approximately 20 staff from a range of disciplines including statistics, data science, health services research, epidemiology, healthcare quality improvement and clinical audit management. It will be led by Dr Julie Nossiter, who will be the Centre’s Operations Director, and Prof David Cromwell, Dr Kate Walker, and Prof Jan van der Meulen who are public health academics at London School of Hygiene and Tropical Medicine (LSHTM).

Question 28

Clinical Effectiveness Unit Overview

Answer 28

The Clinical Effectiveness Unit (CEU) is a collaboration between The Royal College of Surgeons of England and the Department of Health Services Research and Policy of the London School of Hygiene and Tropical Medicine (LSHTM).

The work of the CEU involves carrying out national clinical audits, developing audit methodologies and producing evidence on clinical and cost effectiveness. The CEU currently delivers cancer audits in prostate, lung, bowel, oesophageal and stomach cancer, and recently completed an audit of breast cancer in older patients. These audits have helped to identify and address variations in cancer care across England and Wales, and improve outcomes for patients. They have also promoted quality improvement initiatives within NHS cancer services and identified best practice.

An essential element of the CEU’s strategy is that it considers audit projects as epidemiological studies of the quality of hospital care. Epidemiological methods are used to generate high quality evidence on the processes and outcomes of hospital care as well as on their determinants.

Another important feature of the CEU’s strategy is the emphasis it gives to joint clinical and methodological leadership.

The CEU has 20 staff members, of whom 6 are academic staff members of LSHTM. The background of the staff demonstrates the multidisciplinary character of the Unit (medicine, health services research, medical statistics, epidemiology and public health). The Unit’s Director is David Cromwell, Professor of Health Services Research.

Question 29

Dr Kate Walker (Senior Statistician, NATCAN)

Answer 29

• ASSOCIATE PROFESSOR OF MEDICAL STATISTICS
• I completed my PhD in 2006 at UCL and worked for a year at Queen Mary University as a research fellow in the Wolfson Institute of Preventive Medicine. I joined LSHTM in 2007 in the Faculty of Epidemiology and Population Health, and started my current role, attached to the Royal College of Surgeons, in February 2011.
• I am Deputy Module Organiser for Basic Statistics for Public Health and Policy. I also lecture and run practicals on and Advanced Statistical Methods in Epidemiology (ASME).
• I am based in the Clinical Effectiveness Unit, a collaboration with the Royal College of Surgeons. My research includes developing risk models, statistical issues in performance monitoring, linkage of multiple routine datasets and developing clinical indicators from large routine datasets. The clinical area of my research is primarily the management and outcomes of patients with bowel cancer. I am the lead methodologist for the National Bowel Cancer Audit, carrying out health services research using linked data from large clinical and administrative databases, and I am a methodologist for the National Emergency Laparotomy Audit.

Question 30

Dr Kate Walker (Senior Statistician, NATCAN) Papers

Answer 30

• Probabilistic linkage without personal information successfully linked national clinical datasets. 2021.
• Surgical Treatment and Outcomes of Colorectal Cancer Patients During the COVID-19 Pandemic: A National Population-based Study in England. 2021.

Question 31

Probabilistic linkage without personal information successfully linked national clinical datasets. 2021. Kate Walker

Answer 31

BACKGROUND: Probabilistic linkage can link patients from different clinical databases without the need for personal information. If accurate linkage can be achieved, it would accelerate the use of linked datasets to address important clinical and public health questions. OBJECTIVE: We developed a step-by-step process for probabilistic linkage of national clinical and administrative datasets without personal information, and validated it against deterministic linkage using patient identifiers. STUDY DESIGN AND SETTING: We used electronic health records from the National Bowel Cancer Audit and Hospital Episode Statistics databases for 10,566 bowel cancer patients undergoing emergency surgery in the English National Health Service. RESULTS: Probabilistic linkage linked 81.4% of National Bowel Cancer Audit records to Hospital Episode Statistics, vs. 82.8% using deterministic linkage. No systematic differences were seen between patients that were and were not linked, and regression models for mortality and length of hospital stay according to patient and tumour characteristics were not sensitive to the linkage approach. CONCLUSION: Probabilistic linkage was successful in linking national clinical and administrative datasets for patients undergoing a major surgical procedure. It allows analysts outside highly secure data environments to undertake linkage while minimizing costs and delays, protecting data security, and maintaining linkage quality.

Question 32

Patient and tumour factors affecting the receipt of breast surgery in older women with ER-positive
or ER-negative early invasive breast cancer in England and Wales

Answer 32

Introduction: Studies reporting lower rates of surgery for older women with early invasive breast cancer (EIBC)
have focused on women with oestrogen receptor (ER-) positive tumours. This study examined the factors that influence receipt of breast surgery in older women with ER-positive and ER-negative EIBC.
Methods: Women aged ≥50yrs with unilateral EIBC (stage 1-3A) diagnosed between 2014-2017 were identified
from linked English and Welsh cancer registration and routine hospital datasets. Logistic regression was used to evaluate influence of tumour and patient factors on receipt of surgery.
Results: Among 83,188 women, 87% had ER-positive and 13% had ER-negative EIBC. This percentage was
unaffected by age at diagnosis. In comparison to women with ER-negative EIBC, a higher percentage of women with ER-positive EIBC presented with low risk tumour characteristics: G1 (20% vs. 2%), T1 (61% vs. 44%) and N0 (74% vs. 69%). The percentages of women with any recorded comorbidity (14%
vs. 14%) or degree of frailty (25% vs. 26%) were similar among women with ER-positive and ERnegative disease, respectively. In women with ER-positive EIBC aged 70-74yrs, 75-79yrs and ≥80yrs, rates of no surgery were 6%, 11% and 42%, respectively. The rates were 4%, 4% and 12% among women with ER-negative EIBC. The relative lower rate of surgery for ER-positive EIBC persisted in women with good fitness.
Conclusion: Fewer fit older women in England and Wales receive surgery if diagnosed with ER-positive compared
to ER-negative EIBC. Reasons for this variation should be explored, to ensure consistency of treatment decisions among older women.

Question 33

Patient and tumour factors affecting the receipt of breast surgery in older women with ER-positive
or ER-negative early invasive breast cancer in England and Wales Data Sources

Answer 33

The population-level cohort study was undertaken as part of the NABCOP. The NABCOP uses pseudonymised patient-level datasets provided by the National Cancer Registration and Analysis Service (NCRAS) in England and Wales Cancer Network for Wales. The datasets included national cancer registrations and extracts from the routine hospital admission databases for NHS hospitals (the English Hospital Episode Statistics (HES) and the Patient Episode Database for Wales (PEDW)). Survival information is recorded in the Civil Registration/Mortality data.
.

Question 34

Patient and tumour factors affecting the receipt of breast surgery in older women with ER-positive
or ER-negative early invasive breast cancer in England and Wales. Other points

Answer 34

• Among the 109 018 eligible women in the NABCOP datasets, women with a missing record of ER status (n = 10 951 (10%)) or other key study variables (n = 14 837 (14%)), or who were borderline ER status (n = 42), were excluded from the study.
• Information on patient demographics (age, social deprivation), date of diagnosis, method of
  presentation and tumour characteristics was obtained from the national cancer registration dataset.

Question 35

Patient and tumour factors affecting the receipt of breast surgery in older women with ER-positive
or ER-negative early invasive breast cancer in England and Wales. Statistical analysis

Answer 35

• The percentage of patients not receiving surgery was calculated for women with ER-positive and ERnegative EIBC, and among groups with different patient and tumour characteristics. The statistical significance of differences between the groups was assessed using statistical tests appropriate for continuous or categorical variables. Patient and tumour factors of interest included age, deprivation quintile, CCI, SCARF index, tumour grade, tumour size (T stage), the presence of malignant lymph nodes (N stage), human epidermal growth factor receptor 2 (HER2) status and mode of presentation (screen-detected or symptomatic). Short-term surgical outcomes were also calculated for women
  aged 50-69 or ≥70 years with ER-positive and ER-negative disease.
• Multi-variable logistic regression was used to investigate how all the patient and tumour factors were associated with the likelihood of no surgery. Age was included in the model as a continuous variable, and a cubic spline was used to accommodate its non-linear effect. The spline knots were defined at ages 51, 73, 85 and 90 years, which were selected based on the Akaike information criterion (AIC). The
  model also included Interaction terms to capture differences in the patterns of surgery between women with ER-positive and ER-negative EIBC. The interaction terms were ER-status and age, ERstatus and N-stage, and ER-status and frailty. The performance of the model was evaluated in terms of its calibration and discrimination in the overall cohort and within the two ER subgroups.
• As the spline coefficients and the interaction terms are difficult to interpret, predictions from the model were produced to illustrate the relationship between age and the likelihood of no surgery for women with ER-positive and ER-negative EIBC. The predictions were produced for four patient subgroups: women with low risk (grade 1, stage T1 N0) or high risk (grade 3, stage T2 N1) breast cancer, with each stratified by two levels of fitness: good (no comorbidities, not frail) and poor (comorbidity score ≥ 2 and severe frailty). Analysis for this study was conducted as a complete case analysis using Stata 15.1 (StataCorp LP, College Station, Texas USA). All statistical tests were two sided.

Question 36

Patient and tumour factors affecting the receipt of breast surgery in older women with ER-positive
or ER-negative early invasive breast cancer in England and Wales. Statistical analysis

Answer 36

• The percentage of patients not receiving surgery was calculated for women with ER-positive and ERnegative EIBC, and among groups with different patient and tumour characteristics. The statistical significance of differences between the groups was assessed using statistical tests appropriate for continuous or categorical variables. Patient and tumour factors of interest included age, deprivation quintile, CCI, SCARF index, tumour grade, tumour size (T stage), the presence of malignant lymph nodes (N stage), human epidermal growth factor receptor 2 (HER2) status and mode of presentation (screen-detected or symptomatic). Short-term surgical outcomes were also calculated for women
  aged 50-69 or ≥70 years with ER-positive and ER-negative disease.
• Multi-variable logistic regression was used to investigate how all the patient and tumour factors were associated with the likelihood of no surgery. Age was included in the model as a continuous variable, and a cubic spline was used to accommodate its non-linear effect. The spline knots were defined at ages 51, 73, 85 and 90 years, which were selected based on the Akaike information criterion (AIC). The
  model also included Interaction terms to capture differences in the patterns of surgery between women with ER-positive and ER-negative EIBC. The interaction terms were ER-status and age, ERstatus and N-stage, and ER-status and frailty. The performance of the model was evaluated in terms of its calibration and discrimination in the overall cohort and within the two ER subgroups.
• As the spline coefficients and the interaction terms are difficult to interpret, predictions from the model were produced to illustrate the relationship between age and the likelihood of no surgery for women with ER-positive and ER-negative EIBC. The predictions were produced for four patient subgroups: women with low risk (grade 1, stage T1 N0) or high risk (grade 3, stage T2 N1) breast cancer, with each stratified by two levels of fitness: good (no comorbidities, not frail) and poor (comorbidity score ≥ 2 and severe frailty). Analysis for this study was conducted as a complete case analysis using Stata 15.1 (StataCorp LP, College Station, Texas USA). All statistical tests were two sided.