Charlotte Roach

7.8k total citations
15 papers, 717 citations indexed

About

Charlotte Roach is a scholar working on Oncology, Radiology, Nuclear Medicine and Imaging and Immunology. According to data from OpenAlex, Charlotte Roach has authored 15 papers receiving a total of 717 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Oncology, 7 papers in Radiology, Nuclear Medicine and Imaging and 4 papers in Immunology. Recurrent topics in Charlotte Roach's work include Cancer Immunotherapy and Biomarkers (11 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and Cancer Genomics and Diagnostics (4 papers). Charlotte Roach is often cited by papers focused on Cancer Immunotherapy and Biomarkers (11 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and Cancer Genomics and Diagnostics (4 papers). Charlotte Roach collaborates with scholars based in United States, Australia and Spain. Charlotte Roach's co-authors include Kenneth Emancipator, Marisa Dolled‐Filhart, Grant Toland, Malinka Jansson, Karina Kulangara, Ellie Corigliano, Nancy R. Zhang, Gregory M. Lubiniecki, Leora Horn and Enriqueta Felip and has published in prestigious journals such as Journal of Clinical Oncology, Cancer Research and Annals of Oncology.

In The Last Decade

Charlotte Roach

15 papers receiving 709 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Charlotte Roach United States 10 608 357 152 101 99 15 717
Ashley Kowalewski United States 5 677 1.1× 331 0.9× 225 1.5× 66 0.7× 140 1.4× 5 768
Junxun Ma China 18 596 1.0× 373 1.0× 135 0.9× 95 0.9× 82 0.8× 45 796
Raphael Brandão Moreira United States 11 504 0.8× 369 1.0× 116 0.8× 83 0.8× 99 1.0× 30 719
Malinka Jansson United States 4 639 1.1× 350 1.0× 125 0.8× 170 1.7× 103 1.0× 11 742
Giulia Mazzaschi Italy 11 444 0.7× 254 0.7× 166 1.1× 50 0.5× 96 1.0× 54 634
Xiao-Jing Du China 8 497 0.8× 194 0.5× 103 0.7× 145 1.4× 60 0.6× 9 677
Beung‐Chul Ahn South Korea 12 497 0.8× 366 1.0× 106 0.7× 63 0.6× 81 0.8× 38 621
Ellie Corigliano United States 3 546 0.9× 307 0.9× 109 0.7× 146 1.4× 80 0.8× 4 635
Aliyah Pabani Canada 13 629 1.0× 533 1.5× 82 0.5× 86 0.9× 65 0.7× 32 814
Sophie Marguet France 8 395 0.6× 402 1.1× 108 0.7× 184 1.8× 131 1.3× 12 806

Countries citing papers authored by Charlotte Roach

Since Specialization
Citations

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

Fields of papers citing papers by Charlotte Roach

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Charlotte Roach

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

All Works

15 of 15 papers shown
1.
Robinson, Jennifer G., et al.. (2022). 52 Digital pathology training effectiveness for the evaluation of PD-L1 expression in multiple tumor indications. Regular and Young Investigator Award Abstracts. A55–A56. 1 indexed citations
2.
Zhang, Yiwei, et al.. (2022). High interobserver and intraobserver reproducibility among pathologists assessing PD‐L1 CPS across multiple indications. Histopathology. 81(6). 732–741. 17 indexed citations
3.
Roach, Charlotte, et al.. (2021). Intrapatient Tumor Heterogeneity in IHC Interpretation Using PD-L1 IHC 22C3 pharmDx. Applied immunohistochemistry & molecular morphology. 29(9). 667–673. 17 indexed citations
4.
Hui, Rina, Edward B. Garon, Natasha B. Leighl, et al.. (2017). Pembrolizumab as first-line therapy for patients with PD-L1-positive advanced non-small cell lung cancer: a phase 1 trial. Annals of Oncology. 28(4). 874–881. 188 indexed citations
5.
Kulangara, Karina, Debra Hanks, Supriya Shah, et al.. (2017). Development of the combined positive score (CPS) for the evaluation of PD-L1 in solid tumors with the immunohistochemistry assay PD-L1 IHC 22C3 pharmDx.. Journal of Clinical Oncology. 35(15_suppl). e14589–e14589. 68 indexed citations
6.
Roach, Charlotte, Nancy R. Zhang, Ellie Corigliano, et al.. (2016). Development of a Companion Diagnostic PD-L1 Immunohistochemistry Assay for Pembrolizumab Therapy in Non–Small-cell Lung Cancer. Applied immunohistochemistry & molecular morphology. 24(6). 392–397. 249 indexed citations
7.
Dolled‐Filhart, Marisa, Charlotte Roach, Grant Toland, et al.. (2016). Development of a Companion Diagnostic for Pembrolizumab in Non–Small Cell Lung Cancer Using Immunohistochemistry for Programmed Death Ligand-1. Archives of Pathology & Laboratory Medicine. 140(11). 1243–1249. 86 indexed citations
8.
Dolled‐Filhart, Marisa, Scot Ebbinghaus, Charlotte Roach, et al.. (2016). Development of a clinical trial assay for PD-L1 immunohistochemistry (IHC) for use with pembrolizumab (pembro) clinical trials in melanoma.. Journal of Clinical Oncology. 34(15_suppl). 9571–9571. 2 indexed citations
9.
Dolled‐Filhart, Marisa, et al.. (2015). Development of a PD-L1 immunohistochemistry (IHC) assay for use as a companion diagnostic for pembrolizumab (MK-3475) in non-small cell lung cancer (NSCLC).. Journal of Clinical Oncology. 33(15_suppl). 11065–11065. 8 indexed citations
10.
Puzanov, Igor, Reinhard Dummer, Jacob Schachter, et al.. (2015). Efficacy based on tumor PD-L1 expression in KEYNOTE-002, a randomized comparison of pembrolizumab (pembro; MK-3475) versus chemotherapy in patients (pts) with ipilimumab-refractory (IPI-R) advanced melanoma (MEL).. Journal of Clinical Oncology. 33(15_suppl). 3012–3012. 21 indexed citations
11.
Garon, Edward B., Naiyer A. Rizvi, Rina Hui, et al.. (2015). Abstract CT104: Efficacy of pembrolizumab (MK-3475) and relationship with PD-L1 expression in patients with non-small cell lung cancer: Findings from KEYNOTE-001). Cancer Research. 75(15_Supplement). CT104–CT104. 3 indexed citations
12.
Rizvi, Naiyer A., Edward B. Garon, Natasha B. Leighl, et al.. (2015). Optimizing PD-L1 as a biomarker of response with pembrolizumab (pembro; MK-3475) as first-line therapy for PD-L1–positive metastatic non-small cell lung cancer (NSCLC): Updated data from KEYNOTE-001.. Journal of Clinical Oncology. 33(15_suppl). 8026–8026. 18 indexed citations
13.
Boer, Willem de, et al.. (2010). SLP: A Zero-Contact Non-Invasive Method for Pulmonary Function Testing. 85.1–85.12. 23 indexed citations
14.
Roach, Charlotte, Jon Askaa, Dennis E. Chenoweth, et al.. (2004). Development of sensitive and specific immunohistochemical assays for pro-apoptotic TRAIL-receptors. Cancer Research. 64. 1145–1145. 6 indexed citations
15.
Halpern, Wendy, et al.. (2004). 225 Variable distribution of TRAIL Receptor 1 in primary human tumor and normal tissues. European Journal of Cancer Supplements. 2(8). 69–69. 10 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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