Thomas J. Prior

1.7k total citations · 1 hit paper
12 papers, 1.1k citations indexed

About

Thomas J. Prior is a scholar working on Oncology, Hematology and Economics and Econometrics. According to data from OpenAlex, Thomas J. Prior has authored 12 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Oncology, 6 papers in Hematology and 5 papers in Economics and Econometrics. Recurrent topics in Thomas J. Prior's work include Multiple Myeloma Research and Treatments (6 papers), CAR-T cell therapy research (5 papers) and Health Systems, Economic Evaluations, Quality of Life (4 papers). Thomas J. Prior is often cited by papers focused on Multiple Myeloma Research and Treatments (6 papers), CAR-T cell therapy research (5 papers) and Health Systems, Economic Evaluations, Quality of Life (4 papers). Thomas J. Prior collaborates with scholars based in United States, Netherlands and Spain. Thomas J. Prior's co-authors include John F. P. Bridges, Maarten J. IJzerman, Karin Groothuis‐Oudshoorn, Deborah A. Marshall, Brett Hauber, Juan Marcos González, Charles E. Cunningham, Amrita Krishnan, María‐Victoria Mateos and Niels W.C.J. van de Donk and has published in prestigious journals such as Journal of Clinical Oncology, Blood and Clinical Cancer Research.

In The Last Decade

Thomas J. Prior

10 papers receiving 1.0k 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.

Statistical Methods for the Analysis of Discrete Choice Experiments: A Report of the ISPOR Conjoint Analysis Good Research Practices Task Force

2016 898 citations Brett Hauber, Juan Marcos González et al. Value in Health profile →

Peers

Thomas J. Prior

EE

GHP

ONCOL

PHEOH

HEMAT

Johann‐Matthias Graf von der Schulenburg Germany

Karen Lee Australia

Juan Marcos González United States

Jörg Mahlich Germany

Helen Clark United Kingdom

J. Mac McCullough United States

Devendra Raj Singh Nepal

Larry Green United States

Richard M. Nixon United Kingdom

Xiao Qin Wang China

Johann‐Matthias Graf von der Schulenburg Germany

Thomas J. Prior

346 ×0.8

EE

170 ×0.9

GHP

108 ×0.8

ONCOL

66 ×0.6

PHEOH

66 ×0.7

HEMAT

Citations per year, relative to Thomas J. Prior Thomas J. Prior (= 1×) peers Johann‐Matthias Graf von der Schulenburg

Countries citing papers authored by Thomas J. Prior

Since Specialization

Citations

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

Fields of papers citing papers by Thomas J. Prior

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Thomas J. Prior. 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 Thomas J. Prior. The network helps show where Thomas J. Prior may publish in the future.

Co-authorship network of co-authors of Thomas J. Prior

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

All Works

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12 of 12 papers shown

1.

Gregory, Walter M., Thomas J. Prior, Pieter Sonneveld, et al.. (2025). Modeling MRD Changes in Myeloma to Understand Treatment Effects, Predict Outcomes, and Investigate Curative Potential. Clinical Cancer Research. 31(11). 2154–2161.

2.

Bahlis, Nizar J., Niels W.C.J. van de Donk, Donna Reece, et al.. (2024). OA-01 Talquetamab (tal) + Daratumumab (dara) + Pomalidomide (pom) in Patients (pts) With Relapsed/Refractory Multiple Myeloma (RRMM): Results from the Phase 1b TRIMM-2 Study. Clinical Lymphoma Myeloma & Leukemia. 24. S1–S1.

3.

Homer, Victoria, Christina Yap, Simon Bond, et al.. (2022). Early phase clinical trials extension to guidelines for the content of statistical analysis plans. BMJ. 376. e068177–e068177. 17 indexed citations

4.

Rodríguez‐Otero, Paula, Anita D’Souza, Donna Reece, et al.. (2022). S188: TECLISTAMAB IN COMBINATION WITH DARATUMUMAB, A NOVEL, IMMUNOTHERAPY-BASED APPROACH FOR THE TREATMENT OF RELAPSED/REFRACTORY MULTIPLE MYELOMA: UPDATED PHASE 1B RESULTS. HemaSphere. 6. 89–90. 12 indexed citations

5.

Rodríguez‐Otero, Paula, Anita D’Souza, Donna Reece, et al.. (2022). A novel, immunotherapy-based approach for the treatment of relapsed/refractory multiple myeloma (RRMM): Updated phase 1b results for daratumumab in combination with teclistamab (a BCMA x CD3 bispecific antibody).. Journal of Clinical Oncology. 40(16_suppl). 8032–8032. 22 indexed citations

6.

Oriol, Albert, Paula Rodríguez‐Otero, María‐Victoria Mateos, et al.. (2021). TALQUETAMAB, A G PROTEIN-COUPLED RECEPTOR FAMILY C GROUP 5 MEMBER D (GPRC5D) CD3 BISPECIFIC ANTIBODY FOR RELAPSED/REFRACTORY MULTIPLE MYELOMA (RRMM): UPDATED PHASE 1 STUDY RESULTS. Hematology Transfusion and Cell Therapy. 43. S215–S216. 1 indexed citations

7.

Berdeja, Jesús G., Amrita Krishnan, Albert Oriol, et al.. (2021). Updated results of a phase 1, first-in-human study of talquetamab, a G protein-coupled receptor family C group 5 member D (GPRC5D) × CD3 bispecific antibody, in relapsed/refractory multiple myeloma (MM).. Journal of Clinical Oncology. 39(15_suppl). 8008–8008. 20 indexed citations

8.

Chari, Ajai, Jesús G. Berdeja, Albert Oriol, et al.. (2020). A Phase 1, First-in-Human Study of Talquetamab, a G Protein-Coupled Receptor Family C Group 5 Member D (GPRC5D) x CD3 Bispecific Antibody, in Patients with Relapsed and/or Refractory Multiple Myeloma (RRMM). Blood. 136(Supplement 1). 40–41. 48 indexed citations

9.

Prior, Thomas J.. (2020). Group sequential monitoring based on the maximum of weighted log-rank statistics with the Fleming–Harrington class of weights in oncology clinical trials. Statistical Methods in Medical Research. 29(12). 3525–3532. 11 indexed citations

10.

Hauber, Brett, Juan Marcos González, Karin Groothuis‐Oudshoorn, et al.. (2016). Statistical Methods for the Analysis of Discrete Choice Experiments: A Report of the ISPOR Conjoint Analysis Good Research Practices Task Force. Value in Health. 19(4). 300–315. 898 indexed citations breakdown →

11.

Kinter, Elizabeth, Thomas J. Prior, Chris Carswell, & John F. P. Bridges. (2012). A Comparison of Two Experimental Design Approaches in Applying Conjoint Analysis in Patient-Centered Outcomes Research. Patient. 5(4). 279–294. 14 indexed citations

12.

Kinter, Elizabeth, Thomas J. Prior, Chris Carswell, & John F. P. Bridges. (2012). A Comparison of Two Experimental Design Approaches in Applying Conjoint Analysis in Patient-Centered Outcomes Research. Patient. 5(4). 279–294. 9 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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