Helen Strongman

2.1k total citations · 1 hit paper
35 papers, 1.1k citations indexed

About

Helen Strongman is a scholar working on Oncology, Epidemiology and Molecular Biology. According to data from OpenAlex, Helen Strongman has authored 35 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Oncology, 7 papers in Epidemiology and 6 papers in Molecular Biology. Recurrent topics in Helen Strongman's work include Chronic Disease Management Strategies (6 papers), Chemotherapy-induced cardiotoxicity and mitigation (5 papers) and Metabolism, Diabetes, and Cancer (4 papers). Helen Strongman is often cited by papers focused on Chronic Disease Management Strategies (6 papers), Chemotherapy-induced cardiotoxicity and mitigation (5 papers) and Metabolism, Diabetes, and Cancer (4 papers). Helen Strongman collaborates with scholars based in United Kingdom, United States and Sweden. Helen Strongman's co-authors include Krishnan Bhaskaran, Liam Smeeth, Susannah Stanway, Alexander R. Lyon, Anthony Matthews, Toby M. Maher, Isabel dos‐Santos‐Silva, Rachael Williams, Kathryn E. Mansfield and Sarah Gadd and has published in prestigious journals such as The Lancet, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Helen Strongman

31 papers receiving 1.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Medium and long-term risks of specific cardiovascular diseases in survivors of 20 adult cancers: a population-based cohort study using multiple linked UK electronic health records databases

2019 334 citations Helen Strongman, Sarah Gadd et al. The Lancet profile →

Peers

Countries citing papers authored by Helen Strongman

Since Specialization

Citations

This map shows the geographic impact of Helen Strongman's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Helen Strongman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Helen Strongman more than expected).

Fields of papers citing papers by Helen Strongman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Helen Strongman. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Helen Strongman. The network helps show where Helen Strongman may publish in the future.

Co-authorship network of co-authors of Helen Strongman

This figure shows the co-authorship network connecting the top 25 collaborators of Helen Strongman. A scholar is included among the top collaborators of Helen Strongman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Helen Strongman. Helen Strongman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Title	Journal	Authors	Indexed citations
1	Validation of algorithms identifying diagnosed obstructive sleep apnoea and narcolepsy in coded primary care and linked hospital activity data in England	LSHTM Research Online (London School of Hygiene and Tropical Medicine)	Helen Strongman, Sofia Eriksson et al.	0
2	Barriers and facilitators to specialist service referrals for sleep disorders from healthcare professionals’ perspective: A scoping review of qualitative research evidence	medRxiv	Ellen Nolte, Fred Martineau et al.	1
3	Cohort studies on 71 outcomes among people with atopic eczema in UK primary care data	Nature Communications	Anna Schultze, Helen Strongman et al.	2
4	NHS national data opt-outs: trends and potential consequences for health data research	BJGP Open	John Tazare, Alasdair Henderson et al.	5
5	Early, medium and long-term mental health in cancer survivors compared with cancer-free comparators: matched cohort study using linked UK electronic health records	EClinicalMedicine	Harriet Forbes, Helena Carreira et al.	4
6	Checklist and guidance on creating codelists for routinely collected health data research	SHILAP Revista de lepidopterología	Liang-Yu Lin, Anna Schultze et al.	1
7	The risk of acute kidney injury in colorectal cancer survivors: an english population-based matched cohort study	BMC Cancer	Helena Carreira, Helen Strongman et al.	4
8	Severe COVID-19 outcomes by cardiovascular risk profile in England in 2020: a population-based cohort study	The Lancet Regional Health - Europe	Charlotte Warren‐Gash, Jennifer Davidson et al.	23
9	Acute Cardiovascular Events After COVID-19 in England in 2020: A Self-Controlled Case Series Study	Clinical Epidemiology	Jennifer Davidson, Amitava Banerjee et al.	5
10	Cancer history as a predictor in cardiovascular risk scores: a primary care cohort study	British Journal of General Practice	Helen Strongman, Emily Herrett et al.	6
11	Does Cardiovascular Mortality Overtake Cancer Mortality During Cancer Survivorship?	JACC CardioOncology	Helen Strongman, Sarah Gadd et al.	47
12	UK prevalence of underlying conditions which increase the risk of severe COVID-19 disease: a point prevalence study using electronic health records	BMC Public Health	Jemma Walker, Daniel Grint et al.	22
13	What are the implications of using individual and combined sources of routinely collected data to identify and characterise incident site-specific cancers? a concordance and validation study using linked English electronic health records data	BMJ Open	Helen Strongman, Rachael Williams et al.	23
14	Prevalence of COVID-19-related risk factors and risk of severe influenza outcomes in cancer survivors: A matched cohort study using linked English electronic health records data	EClinicalMedicine	Helena Carreira, Helen Strongman et al.	40
15	Identification of mental health and quality of life outcomes in primary care databases in the UK: a systematic review	BMJ Open	Helena Carreira, Rachael Williams et al.	18
16	Body mass index and Hodgkin's lymphoma: UK population-based cohort study of 5.8 million individuals	British Journal of Cancer	Helen Strongman, Adam J. Brown et al.	19
17	Medium and long-term risks of specific cardiovascular diseases in survivors of 20 adult cancers: a population-based cohort study using multiple linked UK electronic health records databases breakdown →	The Lancet	Helen Strongman, Sarah Gadd et al.	334
18	Approach to record linkage of primary care data from Clinical Practice Research Datalink to other health-related patient data: overview and implications	European Journal of Epidemiology	Shivani Padmanabhan, Rebecca Ghosh et al.	144
19	Comparison of diabetes‐associated secondary healthcare utilization between alternative oral antihyperglycaemic dual therapy combinations with metformin in patients with type 2 diabetes: an observational cohort study	Diabetes Obesity and Metabolism	Helen Strongman, Haya Langerman et al.	1
20	An Observational Cohort Study of Diabetes-Associated Secondary Health Care Utilisation in Patients With Type 2 Diabetes Prescribed Dual Combination Therapy With Oral Anti-Hyperglycaemic Agents in the UK	Value in Health	Haya Langerman, Helen Strongman et al.	1

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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