Kim Cocks

7.0k total citations · 1 hit paper
112 papers, 3.7k citations indexed

About

Kim Cocks is a scholar working on Oncology, Economics and Econometrics and Hematology. According to data from OpenAlex, Kim Cocks has authored 112 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Oncology, 25 papers in Economics and Econometrics and 22 papers in Hematology. Recurrent topics in Kim Cocks's work include Health Systems, Economic Evaluations, Quality of Life (22 papers), Cancer survivorship and care (21 papers) and Multiple Myeloma Research and Treatments (19 papers). Kim Cocks is often cited by papers focused on Health Systems, Economic Evaluations, Quality of Life (22 papers), Cancer survivorship and care (21 papers) and Multiple Myeloma Research and Treatments (19 papers). Kim Cocks collaborates with scholars based in United Kingdom, United States and Germany. Kim Cocks's co-authors include Galina Velikova, Julia Brown, Madeleine King, Peter Fayers, David Torgerson, Gilberto de Castro, Graham Jackson, Gareth J. Morgan, Faith E. Davies and Sue Bell and has published in prestigious journals such as The Lancet, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Kim Cocks

105 papers receiving 3.6k 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.

Evidence-Based Guidelines for Determination of Sample Size and Interpretation of the European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire Core 30

2010 469 citations Kim Cocks, Madeleine King et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kim Cocks United Kingdom	31	1.9k	883	633	497	480	112	3.7k
Tanya M. Wildes United States	34	1.6k 0.8×	1.1k 1.2×	546 0.9×	653 1.3×	375 0.8×	225	3.6k
Eva Culakova United States	38	2.8k 1.4×	1.0k 1.2×	860 1.4×	264 0.5×	755 1.6×	180	7.0k
María A. López-Olivo United States	34	974 0.5×	673 0.8×	470 0.7×	277 0.6×	586 1.2×	134	4.4k
Soo‐Mee Bang South Korea	35	2.3k 1.2×	892 1.0×	1.1k 1.7×	682 1.4×	766 1.6×	295	5.0k
Ulrich Wedding Germany	30	1.5k 0.8×	367 0.4×	808 1.3×	227 0.5×	351 0.7×	156	3.5k
Marc Botteman United States	36	1.2k 0.6×	440 0.5×	899 1.4×	711 1.4×	1.3k 2.8×	212	5.5k
Peter C. Trask United States	30	2.2k 1.1×	345 0.4×	1.1k 1.7×	697 1.4×	234 0.5×	105	4.2k
Christina Lacchetti United States	34	3.9k 2.0×	383 0.4×	1.4k 2.2×	648 1.3×	860 1.8×	63	6.8k
Kimberly Webster United States	25	2.8k 1.4×	517 0.6×	1.2k 1.9×	172 0.3×	426 0.9×	55	5.2k
Lazzaro Repetto Italy	32	3.0k 1.5×	662 0.7×	1.4k 2.2×	308 0.6×	756 1.6×	101	6.3k

Countries citing papers authored by Kim Cocks

Since Specialization

Citations

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

Fields of papers citing papers by Kim Cocks

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kim Cocks

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Worthy, Gill, et al.. (2025). Meaningful change threshold estimation for the non-small cell lung cancer symptom assessment questionnaire (NSCLC-SAQ): psychometric analysis from a phase 3 trial (LIBRETTO-431). Quality of Life Research. 34(4). 1137–1146.

Zeman, Florian, Johannes M. Giesinger, Tobias Pukrop, et al.. (2025). The EORTC QLQ-F17 as a shortened version of the EORTC QLQ-C30 to assess self-reported functioning in cancer patients: investigating equivalence and psychometric properties in a randomized cross-over trial. EClinicalMedicine. 84. 103262–103262.

Hummel, Horst-Dieter, Myung‐Ju Ahn, Fiona Blackhall, et al.. (2025). Patient-Reported Outcomes for Patients with Previously Treated Small Cell Lung Cancer Receiving Tarlatamab: Results from the DeLLphi-301 Phase 2 Trial. Advances in Therapy. 42(4). 1950–1964. 1 indexed citations

Braverman, Julia, Gill Worthy, James W. Shaw, et al.. (2024). A Review of Meaningful Change Thresholds for EORTC QLQ-C30 and FACT-G Within Oncology. Value in Health. 27(4). 458–468. 4 indexed citations

Forde, Kimberly A., et al.. (2023). Use of the European Organisation for Research and Treatment of Cancer multiple myeloma module (EORTC QLQ-MY20): a review of the literature 25 years after development. Blood Cancer Journal. 13(1). 79–79. 2 indexed citations

Musoro, Jammbe, Corneel Coens, Mirjam A. G. Sprangers, et al.. (2023). Minimally important differences for interpreting EORTC QLQ-C30 change scores over time: A synthesis across 21 clinical trials involving nine different cancer types. European Journal of Cancer. 188. 171–182. 64 indexed citations

Holch, Patricia, Grace Turner, Anju Keetharuth, et al.. (2023). The impact of COVID-19 on PRO development, collection and implementation: views of UK and Ireland professionals. Journal of Patient-Reported Outcomes. 7(1). 121–121.

Hirji, Ishan, et al.. (2023). Healthcare resource utilization of maribavir versus investigator‐assigned therapy in transplant recipients with cytomegalovirus infection refractory (with or without genotypic resistance) to prior treatment: Exploratory analysis of the Phase 3 SOLSTICE trial. Transplant Infectious Disease. 25(3). e14064–e14064. 4 indexed citations

Hirji, Ishan, et al.. (2022). Healthcare Resource Utilization in Transplant Recipients with Cytomegalovirus Infection Refractory/Resistant to Treatment Receiving Maribavir Versus Investigator Assigned Therapy: Exploratory Analysis of a Phase 3 Trial. Transplantation and Cellular Therapy. 28(3). S45–S46. 1 indexed citations

10.

Peipert, John Devin, et al.. (2022). Validity of a single-item indicator of treatment side effect bother in a diverse sample of cancer patients. Supportive Care in Cancer. 30(4). 3613–3623. 16 indexed citations

11.

Cocks, Kim, Colin A. Johnson, Heike Schmidt, et al.. (2022). Content validity of the EORTC quality of life questionnaire QLQ-C30 for use in cancer. European Journal of Cancer. 178. 128–138. 69 indexed citations

12.

Cocks, Kim & Jacqueline Buchanan. (2022). How scoring limits the usability of minimal important differences (MIDs) as responder definition (RD): an exemplary demonstration using EORTC QLQ-C30 subscales. Quality of Life Research. 32(5). 1247–1253. 9 indexed citations

13.

Koller, Michael, Jammbe Musoro, Krzysztof A. Tomaszewski, et al.. (2022). Minimally important differences of EORTC QLQ-C30 scales in patients with lung cancer or malignant pleural mesothelioma – Interpretation guidance derived from two randomized EORTC trials. Lung Cancer. 167. 65–72. 11 indexed citations

14.

Trigg, Andrew, Elaine Brohan, Kim Cocks, et al.. (2021). Health-related quality of life in pediatric patients with partial onset seizures or primary generalized tonic-clonic seizures receiving adjunctive perampanel. Epilepsy & Behavior. 118. 107938–107938. 8 indexed citations

15.

Sully, Kate, Andrew Trigg, Nicola Bonner, et al.. (2019). Estimation of minimally important differences and responder definitions for EORTC QLQ‐MY20 scores in multiple myeloma patients. European Journal Of Haematology. 103(5). 500–509. 30 indexed citations

16.

Moreau, Philippe, Shaji Kumar, Ralph V. Boccia, et al.. (2019). Convenience, satisfaction, health-related quality of life of once-weekly 70 mg/m2 vs. twice-weekly 27 mg/m2 carfilzomib (randomized A.R.R.O.W. study). Leukemia. 33(12). 2934–2946. 20 indexed citations

17.

Ludwig, Heinz, Philippe Moreau, Meletios Α. Dimopoulos, et al.. (2019). Health-related quality of life in the ENDEAVOR study: carfilzomib-dexamethasone vs bortezomib-dexamethasone in relapsed/refractory multiple myeloma. Blood Cancer Journal. 9(3). 23–23. 28 indexed citations

18.

Smith, Adam B., Kim Cocks, Matthew Taylor, & David Parry. (2014). Most domains of the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire C30 are reliable. Journal of Clinical Epidemiology. 67(8). 952–957. 12 indexed citations

19.

Gillmore, JD, Kim Cocks, Prayman Sattianayagam, et al.. (2010). UK AL Amyloidosis Treatment Trial (UKATT) - a randomised study: lessons for future trial design. UCL Discovery (University College London). 2 indexed citations

20.

Vasudev, Naveen, Janet E. Brown, Sarah Brown, et al.. (2008). Prognostic Factors in Renal Cell Carcinoma: Association of Preoperative Sodium Concentration with Survival. Clinical Cancer Research. 14(6). 1775–1781. 31 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.

Explore authors with similar magnitude of impact