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 — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Helen Strongman United Kingdom	15	359	292	265	140	132	35	1.1k
Anthony Matthews Sweden	16	377 1.1×	170 0.6×	235 0.9×	124 0.9×	127 1.0×	44	1.1k
Yejin Mok United States	19	352 1.0×	193 0.7×	236 0.9×	189 1.4×	198 1.5×	64	1.4k
Grigory Sidorenkov Netherlands	19	179 0.5×	287 1.0×	176 0.7×	81 0.6×	95 0.7×	79	1.0k
Wenli Lu China	18	139 0.4×	168 0.6×	311 1.2×	154 1.1×	212 1.6×	73	1.2k
Ghada N. Farhat United States	16	165 0.5×	172 0.6×	214 0.8×	122 0.9×	64 0.5×	26	1.0k
Yunhe Zhao China	8	224 0.6×	241 0.8×	346 1.3×	257 1.8×	161 1.2×	18	1.8k
Helen Hancock United Kingdom	20	268 0.7×	241 0.8×	357 1.3×	73 0.5×	131 1.0×	66	1.4k
Issei Kurahashi Japan	18	195 0.5×	216 0.7×	160 0.6×	114 0.8×	157 1.2×	36	1.0k
Uffe Heide‐Jørgensen Denmark	21	233 0.6×	269 0.9×	346 1.3×	139 1.0×	185 1.4×	75	1.4k
Eva Lustigova United States	15	253 0.7×	116 0.4×	130 0.5×	95 0.7×	72 0.5×	42	1.0k

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

Strongman, Helen, Sofia Eriksson, Michelle A. Miller, et al.. (2025). 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). 5. 100110–100110.

Nolte, Ellen, Fred Martineau, Michelle A. Miller, et al.. (2025). Barriers and facilitators to specialist service referrals for sleep disorders from healthcare professionals’ perspective: A scoping review of qualitative research evidence. medRxiv. 1 indexed citations

Schultze, Anna, Helen Strongman, Krishnan Bhaskaran, et al.. (2024). Cohort studies on 71 outcomes among people with atopic eczema in UK primary care data. Nature Communications. 15(1). 9573–9573. 2 indexed citations

Tazare, John, Alasdair Henderson, Jessica Morley, et al.. (2024). NHS national data opt-outs: trends and potential consequences for health data research. BJGP Open. 8(3). BJGPO.2024.0020–BJGPO.2024.0020. 5 indexed citations

Forbes, Harriet, Helena Carreira, Garth Funston, et al.. (2024). 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. 76. 102826–102826. 4 indexed citations

Lin, Liang-Yu, Anna Schultze, John Tazare, et al.. (2024). Checklist and guidance on creating codelists for routinely collected health data research. SHILAP Revista de lepidopterología. 4. 20–20. 1 indexed citations

Carreira, Helena, Helen Strongman, Helen McDonald, et al.. (2023). The risk of acute kidney injury in colorectal cancer survivors: an english population-based matched cohort study. BMC Cancer. 23(1). 839–839. 4 indexed citations

Warren‐Gash, Charlotte, Jennifer Davidson, Helen Strongman, et al.. (2023). Severe COVID-19 outcomes by cardiovascular risk profile in England in 2020: a population-based cohort study. The Lancet Regional Health - Europe. 27. 100604–100604. 23 indexed citations

Davidson, Jennifer, Amitava Banerjee, Helen Strongman, et al.. (2023). Acute Cardiovascular Events After COVID-19 in England in 2020: A Self-Controlled Case Series Study. Clinical Epidemiology. Volume 15. 911–921. 5 indexed citations

10.

Strongman, Helen, Emily Herrett, Rod Jackson, et al.. (2022). Cancer history as a predictor in cardiovascular risk scores: a primary care cohort study. British Journal of General Practice. 73(726). e34–e42. 6 indexed citations

11.

Strongman, Helen, Sarah Gadd, Anthony Matthews, et al.. (2022). Does Cardiovascular Mortality Overtake Cancer Mortality During Cancer Survivorship?. JACC CardioOncology. 4(1). 113–123. 47 indexed citations

12.

Walker, Jemma, Daniel Grint, Helen Strongman, et al.. (2021). 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. 21(1). 484–484. 22 indexed citations

13.

Strongman, Helen, Rachael Williams, & Krishnan Bhaskaran. (2020). 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. 10(8). e037719–e037719. 23 indexed citations

14.

Carreira, Helena, Helen Strongman, Helen McDonald, et al.. (2020). 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. 29-30. 100656–100656. 40 indexed citations

15.

Carreira, Helena, Rachael Williams, Helen Strongman, & Krishnan Bhaskaran. (2019). Identification of mental health and quality of life outcomes in primary care databases in the UK: a systematic review. BMJ Open. 9(7). e029227–e029227. 18 indexed citations

16.

Strongman, Helen, Adam J. Brown, Liam Smeeth, & Krishnan Bhaskaran. (2019). Body mass index and Hodgkin's lymphoma: UK population-based cohort study of 5.8 million individuals. British Journal of Cancer. 120(7). 768–770. 19 indexed citations

17.

Strongman, Helen, Sarah Gadd, Anthony Matthews, et al.. (2019). 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. The Lancet. 394(10203). 1041–1054. 334 indexed citations breakdown →

18.

Padmanabhan, Shivani, et al.. (2018). 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. 34(1). 91–99. 144 indexed citations

19.

Strongman, Helen, et al.. (2015). 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. 17(6). 573–580. 1 indexed citations

20.

Langerman, Haya, et al.. (2014). 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. 17(7). A360–A360. 1 indexed citations

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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