Natalie Dimier

2.0k total citations
20 papers, 747 citations indexed

About

Natalie Dimier is a scholar working on Oncology, Pathology and Forensic Medicine and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Natalie Dimier has authored 20 papers receiving a total of 747 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Oncology, 11 papers in Pathology and Forensic Medicine and 8 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Natalie Dimier's work include Lymphoma Diagnosis and Treatment (11 papers), CAR-T cell therapy research (8 papers) and Monoclonal and Polyclonal Antibodies Research (8 papers). Natalie Dimier is often cited by papers focused on Lymphoma Diagnosis and Treatment (11 papers), CAR-T cell therapy research (8 papers) and Monoclonal and Polyclonal Antibodies Research (8 papers). Natalie Dimier collaborates with scholars based in United Kingdom, Switzerland and United States. Natalie Dimier's co-authors include Günter Fingerle‐Rowson, Gilles Salles, Dédée F. Murrell, Jeannie Hou, Laurent Mortier, Nicole Basset‐Séguin, John G. Gribben, Aleksandar Sekulić, Sarah Williams and Anja Gesierich and has published in prestigious journals such as Journal of Clinical Oncology, Blood and The Lancet Oncology.

In The Last Decade

Natalie Dimier

17 papers receiving 728 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Natalie Dimier United Kingdom	10	385	380	257	212	205	20	747
Gail Ryan Australia	13	378 1.0×	328 0.9×	267 1.0×	204 1.0×	176 0.9×	20	973
Klaus Willenbrock Germany	16	558 1.4×	465 1.2×	148 0.6×	83 0.4×	198 1.0×	23	874
Paulo Lúcio Portugal	13	163 0.4×	160 0.4×	255 1.0×	61 0.3×	181 0.9×	30	854
Maria Delioukina United States	13	426 1.1×	308 0.8×	157 0.6×	45 0.2×	168 0.8×	33	652
Neha Mehta–Shah United States	16	551 1.4×	433 1.1×	106 0.4×	97 0.5×	99 0.5×	94	878
Beata Holkova United States	13	297 0.8×	307 0.8×	222 0.9×	35 0.2×	139 0.7×	48	634
Sumeet Ambarkhane United States	9	439 1.1×	513 1.4×	47 0.2×	39 0.2×	155 0.8×	41	654
I Bolz Germany	11	331 0.9×	196 0.5×	133 0.5×	35 0.2×	192 0.9×	17	562
C Lavignac France	8	504 1.3×	369 1.0×	260 1.0×	28 0.1×	249 1.2×	14	836
Thérèse Rousset France	9	445 1.2×	346 0.9×	168 0.7×	36 0.2×	134 0.7×	12	714

Countries citing papers authored by Natalie Dimier

Since Specialization

Citations

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

Fields of papers citing papers by Natalie Dimier

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Natalie Dimier

This figure shows the co-authorship network connecting the top 25 collaborators of Natalie Dimier. A scholar is included among the top collaborators of Natalie Dimier 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 Natalie Dimier. Natalie Dimier 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

Jamois, Candice, Koorosh Korfi, Sylvia Herter, et al.. (2024). Integrated Quantitative Clinical Pharmacology Analysis Identifies Optimal Englumafusp Alfa Dose Range for Proof-of-Concept Study with Glofitamab in Second-Line Large B-Cell Lymphoma Patients. Blood. 144(Supplement 1). 4180–4180.

Dixon, Jesse G., Natalie Dimier, Tina Nielsen, et al.. (2022). End of induction positron emission tomography complete response (PET‐CR) as a surrogate for progression‐free survival in previously untreated follicular lymphoma. British Journal of Haematology. 198(2). 333–337. 3 indexed citations

Dixon, Jesse G., Dai Chihara, Tina Nielsen, et al.. (2022). Factors Affecting the Clinical Course of Follicular Lymphoma: A Multistate Survival Analysis Using Individual Patient Data from Eight Multicenter Randomized Clinical Trials. Clinical Lymphoma Myeloma & Leukemia. 22(11). e1009–e1018.

Bröske, Ann-Marie E, Koorosh Korfi, Anton Belousov, et al.. (2021). Pharmacodynamics and molecular correlates of response to glofitamab in relapsed/refractory non-Hodgkin lymphoma. Blood Advances. 6(3). 1025–1037. 46 indexed citations

Dimier, Natalie & Susan Todd. (2020). Assessment of the information theory approach to evaluatingtime‐to‐eventsurrogate and true endpoints in a meta‐analytic setting. Pharmaceutical Statistics. 20(2). 335–347.

Djebli, Nassim, François Mercier, Nicole A. Kratochwil, et al.. (2019). Population Pharmacokinetics and Novel Exposure-Response Analyses to Inform Optimal Biologic Dose Selection for CD20-TCB, a T-Cell-Engaging Bispecific Antibody, in Relapsed or Refractory B-Cell Non-Hodgkin Lymphoma. Blood. 134(Supplement_1). 3799–3799. 7 indexed citations

Morschhauser, Franck, Carmelo Carlo‐Stella, Fritz Offner, et al.. (2019). Dual CD20-Targeted Therapy With Concurrent CD20-TCB and Obinutuzumab Shows Highly Promising Clinical Activity and Manageable Safety in Relapsed or Refractory B-Cell Non-Hodgkin Lymphoma: Preliminary Results From a Phase Ib Trial. Blood. 134(Supplement_1). 1584–1584. 24 indexed citations

Bröske, Ann-Marie E, Ian James, Anton Belousov, et al.. (2019). CD20-TCB, a Novel T-Cell-Engaging Bispecific Antibody, Induces T-Cell-Mediated Killing in Relapsed or Refractory Non-Hodgkin Lymphoma: Biomarker Results From a Phase I Dose-Escalation Trial. Blood. 134(Supplement_1). 5319–5319. 5 indexed citations

Hutchings, Martin, Giuseppe Gritti, Anna Sureda, et al.. (2019). CD20-TCB, a Novel T-Cell-Engaging Bispecific Antibody, Can be Safely Combined with the Anti-PD-L1 Antibody Atezolizumab in Relapsed or Refractory B-Cell Non-Hodgkin Lymphoma. Blood. 134(Supplement_1). 2871–2871. 20 indexed citations

10.

Dickinson, Michael, Franck Morschhauser, Gloria Iacoboni, et al.. (2019). CD20‐TCB (RG6026), A NOVEL “2:1” FORMAT T‐CELL‐ENGAGING BISPECIFIC ANTIBODY, INDUCES COMPLETE REMISSIONS IN RELAPSED/REFRACTORY B‐CELL NON‐HODGKIN'S LYMPHOMA. Hematological Oncology. 37(S2). 92–93. 11 indexed citations

11.

Li, Chi‐Chung, Brendan C. Bender, Shen Yin, et al.. (2019). Exposure-Response Analyses Indicate a Promising Benefit/Risk Profile of Mosunetuzumab in Relapsed and Refractory Non-Hodgkin Lymphoma. Blood. 134(Supplement_1). 1285–1285. 11 indexed citations

12.

Hutchings, Martin, Gloria Iacoboni, Franck Morschhauser, et al.. (2018). CD20-Tcb (RG6026), a Novel "2:1" Format T-Cell-Engaging Bispecific Antibody, Induces Complete Remissions in Relapsed/Refractory B-Cell Non-Hodgkin's Lymphoma: Preliminary Results from a Phase I First in Human Trial. Blood. 132(Supplement 1). 226–226. 25 indexed citations

13.

Sekulić, Aleksandar, Michael R. Migden, Nicole Basset‐Séguin, et al.. (2017). Long-term safety and efficacy of vismodegib in patients with advanced basal cell carcinoma: final update of the pivotal ERIVANCE BCC study. BMC Cancer. 17(1). 332–332. 283 indexed citations

14.

Dimier, Natalie & Susan Todd. (2017). An investigation into the two‐stage meta‐analytic copula modelling approach for evaluating time‐to‐event surrogate endpoints which comprise of one or more events of interest. Pharmaceutical Statistics. 16(5). 322–333. 4 indexed citations

15.

Dimier, Natalie, Paul Delmar, Carol Ward, et al.. (2017). A model for predicting effect of treatment on progression-free survival using MRD as a surrogate end point in CLL. Blood. 131(9). 955–962. 50 indexed citations

16.

Cheson, Bruce D., Peter C. Trask, John G. Gribben, et al.. (2016). Health-related quality of life and symptoms in patients with rituximab-refractory indolent non-Hodgkin lymphoma treated in the phase III GADOLIN study with obinutuzumab plus bendamustine versus bendamustine alone. Annals of Hematology. 96(2). 253–259. 18 indexed citations

17.

Sehn, Laurie H., Neil Chua, Jiřı́ Mayer, et al.. (2016). Obinutuzumab plus bendamustine versus bendamustine monotherapy in patients with rituximab-refractory indolent non-Hodgkin lymphoma (GADOLIN): a randomised, controlled, open-label, multicentre, phase 3 trial. The Lancet Oncology. 17(8). 1081–1093. 227 indexed citations

18.

Hansson, Johan, Axel Hauschild, Rainer Kunstfeld, et al.. (2016). Vismodegib (VISMO), a hedgehog pathway inhibitor (HPI), in advanced basal cell carcinoma (aBCC): STEVIE study primary analysis in 1215 patients (pts).. Journal of Clinical Oncology. 34(15_suppl). 9532–9532. 6 indexed citations

19.

Dimier, Natalie, Paul Delmar, Carol Ward, et al.. (2015). A Model for Predicting Effect of Treatment on Progression-Free Survival Using Minimal Residual Disease As a Surrogate Endpoint in Chronic Lymphocytic Leukemia. Blood. 126(23). 720–720. 3 indexed citations

20.

Cheson, Bruce D., Peter C. Trask, John G. Gribben, et al.. (2015). Primary Results of the Health-Related Quality of Life Assessment from the Phase III Gadolin Study of Obinutuzumab Plus Bendamustine Compared with Bendamustine Alone in Patients with Rituximab-Refractory, Indolent Non-Hodgkin Lymphoma. Blood. 126(23). 1532–1532. 4 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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