Sarah Runswick

4.8k total citations · 2 hit papers
18 papers, 3.0k citations indexed

About

Sarah Runswick is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Genetics. According to data from OpenAlex, Sarah Runswick has authored 18 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Oncology, 11 papers in Pulmonary and Respiratory Medicine and 9 papers in Genetics. Recurrent topics in Sarah Runswick's work include PARP inhibition in cancer therapy (12 papers), Advanced Breast Cancer Therapies (9 papers) and BRCA gene mutations in cancer (9 papers). Sarah Runswick is often cited by papers focused on PARP inhibition in cancer therapy (12 papers), Advanced Breast Cancer Therapies (9 papers) and BRCA gene mutations in cancer (9 papers). Sarah Runswick collaborates with scholars based in United Kingdom, United States and China. Sarah Runswick's co-authors include Anne Armstrong, Carsten Goessl, Norikazu Masuda, Nadine Tung, Elżbieta Senkus, Binghe Xu, Pierfranco Conté, Mark E. Robson, Susan M. Domchek and Seock‐Ah Im and has published in prestigious journals such as New England Journal of Medicine, Journal of Clinical Oncology and PLoS ONE.

In The Last Decade

Sarah Runswick

18 papers receiving 3.0k citations

Hit Papers

Olaparib for Metastatic Breast Cancer in Patients with a ... 2017 2026 2020 2023 2017 2019 500 1000 1.5k 2.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sarah Runswick United Kingdom 9 2.3k 1.3k 932 869 820 18 3.0k
Miguel Martín Spain 8 1.5k 0.7× 753 0.6× 657 0.7× 511 0.6× 585 0.7× 15 1.9k
Sami Diab United States 27 1.8k 0.8× 812 0.6× 805 0.9× 1.0k 1.2× 386 0.5× 74 2.8k
Bethan Powell United States 6 1.6k 0.7× 1.8k 1.4× 339 0.4× 594 0.7× 708 0.9× 10 2.9k
David K. Chang United Kingdom 29 2.3k 1.0× 1.2k 1.0× 546 0.6× 1.0k 1.2× 178 0.2× 90 3.2k
Elizabeth Lowe United States 19 2.8k 1.2× 1.1k 0.8× 1.4k 1.6× 510 0.6× 726 0.9× 51 3.6k
Filipa Lynce United States 21 1.3k 0.5× 571 0.5× 456 0.5× 474 0.5× 323 0.4× 110 1.9k
Darren Hodgson United Kingdom 21 2.3k 1.0× 1.4k 1.1× 782 0.8× 498 0.6× 704 0.9× 73 3.1k
Daniel Nava Rodrigues United Kingdom 26 878 0.4× 948 0.8× 1.0k 1.1× 820 0.9× 208 0.3× 54 2.2k
Sarah Halford United Kingdom 27 1.4k 0.6× 1.1k 0.9× 253 0.3× 735 0.8× 365 0.4× 51 2.5k
James R. Vasselli United States 21 1.2k 0.5× 1.6k 1.3× 1.2k 1.3× 1.1k 1.3× 480 0.6× 37 3.7k

Countries citing papers authored by Sarah Runswick

Since Specialization
Citations

This map shows the geographic impact of Sarah Runswick'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 Sarah Runswick with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sarah Runswick more than expected).

Fields of papers citing papers by Sarah Runswick

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sarah Runswick. 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 Sarah Runswick. The network helps show where Sarah Runswick may publish in the future.

Co-authorship network of co-authors of Sarah Runswick

This figure shows the co-authorship network connecting the top 25 collaborators of Sarah Runswick. A scholar is included among the top collaborators of Sarah Runswick 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 Sarah Runswick. Sarah Runswick is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
D’Alise, Anna Morena, Guido Leoni, Gabriella Cotugno, et al.. (2024). Phase I Trial of Viral Vector-Based Personalized Vaccination Elicits Robust Neoantigen-Specific Antitumor T-Cell Responses. Clinical Cancer Research. 30(11). 2412–2423. 23 indexed citations
2.
Robson, Mark E., Nadine Tung, Pierfranco Conté, et al.. (2019). OlympiAD final overall survival and tolerability results: Olaparib versus chemotherapy treatment of physician’s choice in patients with a germline BRCA mutation and HER2-negative metastatic breast cancer. Annals of Oncology. 30(4). 558–566. 497 indexed citations breakdown →
3.
Domchek, S. M., Mark E. Robson, S-A. Im, et al.. (2018). Abstract P5-21-12: Tolerability of olaparib monotherapy versus chemotherapy in patients with HER2-negative metastatic breast cancer and a germline BRCA mutation: OlympiAD. Cancer Research. 78(4_Supplement). P5–21. 3 indexed citations
4.
5.
Tung, Nadine, Seock‐Ah Im, Elżbieta Senkus, et al.. (2018). Olaparib versus chemotherapy treatment of physician’s choice in patients with a germline BRCA mutation and HER2-negative metastatic breast cancer (OlympiAD): Efficacy in patients with visceral metastases.. Journal of Clinical Oncology. 36(15_suppl). 1052–1052. 9 indexed citations
8.
Robson, Mark E., Seock‐Ah Im, Elżbieta Senkus, et al.. (2017). Olaparib for Metastatic Breast Cancer in Patients with a Germline BRCA Mutation. New England Journal of Medicine. 377(6). 523–533. 2156 indexed citations breakdown →
10.
Robson, Mark E., Seock‐Ah Im, Elżbieta Senkus, et al.. (2017). OlympiAD: Phase III trial of olaparib monotherapy versus chemotherapy for patients (pts) with HER2-negative metastatic breast cancer (mBC) and a germline BRCA mutation (gBRCAm).. Journal of Clinical Oncology. 35(18_suppl). LBA4–LBA4. 24 indexed citations
11.
Robson, Mark E., Seock‐Ah Im, Elżbieta Senkus, et al.. (2017). OlympiAD: Phase III trial of olaparib monotherapy versus chemotherapy for patients (pts) with HER2-negative metastatic breast cancer (mBC) and a germline BRCA mutation (gBRCAm).. Journal of Clinical Oncology. 35(15_suppl). LBA4–LBA4. 7 indexed citations
12.
Lheureux, Stéphanie, Jonathan A. Ledermann, Sarah Runswick, et al.. (2015). Genomic characterization of long-term responders to olaparib.. Journal of Clinical Oncology. 33(15_suppl). 5566–5566. 3 indexed citations
13.
Bradford, James, Matthew R. Farren, Steve Powell, et al.. (2013). RNA-Seq Differentiates Tumour and Host mRNA Expression Changes Induced by Treatment of Human Tumour Xenografts with the VEGFR Tyrosine Kinase Inhibitor Cediranib. PLoS ONE. 8(6). e66003–e66003. 24 indexed citations
14.
Holt, Sarah V., Armelle Logié, Barry R. Davies, et al.. (2012). Enhanced Apoptosis and Tumor Growth Suppression Elicited by Combination of MEK (Selumetinib) and mTOR Kinase Inhibitors (AZD8055). Cancer Research. 72(7). 1804–1813. 70 indexed citations
15.
Schlicker, Andreas, Garry Beran, Christine M. Chresta, et al.. (2012). Subtypes of primary colorectal tumors correlate with response to targeted treatment in colorectal cell lines. BMC Medical Genomics. 5(1). 66–66. 180 indexed citations
16.
Chresta, Christine M., Sarah Runswick, Garry Beran, et al.. (2011). Abstract 5365: Molecular and pharmacological (EGFRi, MEKi) characterisation of a colorectal cancer (CRC) cell line panel to evaluate cellular phenotype and efficacy of targeted therapies in CRC. Cancer Research. 71(8_Supplement). 5365–5365. 3 indexed citations
17.
Dry, Jonathan R., Alan Lau, Charlotte Knights, et al.. (2010). Abstract 3497: Identifying pre-clinical predictive biomarkers for the PARP inhibitor olaparib. Cancer Research. 70(8_Supplement). 3497–3497. 1 indexed citations
18.
Runswick, Sarah, H. Boeing, F Clavel, et al.. (2002). Compliance with the urine marker PABAcheck in cancer epidemiology studies.. PubMed. 156. 35–7. 3 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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