Zhong-Jun Xia

2.0k total citations
50 papers, 1.5k citations indexed

About

Zhong-Jun Xia is a scholar working on Pathology and Forensic Medicine, Oncology and Immunology. According to data from OpenAlex, Zhong-Jun Xia has authored 50 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Pathology and Forensic Medicine, 31 papers in Oncology and 15 papers in Immunology. Recurrent topics in Zhong-Jun Xia's work include Lymphoma Diagnosis and Treatment (41 papers), Viral-associated cancers and disorders (23 papers) and Immune Cell Function and Interaction (10 papers). Zhong-Jun Xia is often cited by papers focused on Lymphoma Diagnosis and Treatment (41 papers), Viral-associated cancers and disorders (23 papers) and Immune Cell Function and Interaction (10 papers). Zhong-Jun Xia collaborates with scholars based in China, United States and United Kingdom. Zhong-Jun Xia's co-authors include Yue Lu, Hui-Qiang Huang, Liang Wang, Wen-Qi Jiang, Jing‐Hua Wang, Qi-rong Geng, Hui-Qiang Huang, Tong-Yu Lin, Hua Wang and Hua Wang and has published in prestigious journals such as PLoS ONE, British Journal of Cancer and Autophagy.

In The Last Decade

Zhong-Jun Xia

50 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhong-Jun Xia China 20 1.0k 760 544 235 177 50 1.5k
Florence Loong China 17 988 0.9× 1.1k 1.4× 523 1.0× 372 1.6× 78 0.4× 32 1.9k
Sylvia Hoeller Switzerland 18 718 0.7× 595 0.8× 432 0.8× 255 1.1× 71 0.4× 35 1.3k
Kenneth MacLennan United Kingdom 20 712 0.7× 988 1.3× 381 0.7× 242 1.0× 70 0.4× 43 1.6k
Hirokazu Nakamine Japan 21 718 0.7× 921 1.2× 360 0.7× 227 1.0× 45 0.3× 101 1.5k
Anna Dodero Italy 21 898 0.9× 948 1.2× 695 1.3× 181 0.8× 64 0.4× 73 1.7k
Weiyun Z. Ai United States 18 977 0.9× 565 0.7× 700 1.3× 207 0.9× 41 0.2× 64 1.5k
P. M. Kluin Netherlands 21 797 0.8× 1.0k 1.3× 314 0.6× 380 1.6× 80 0.5× 40 1.8k
Nathanael G. Bailey United States 22 498 0.5× 711 0.9× 527 1.0× 392 1.7× 58 0.3× 67 1.6k
I. Anagnostopoulos Germany 15 1.2k 1.2× 945 1.2× 220 0.4× 175 0.7× 42 0.2× 25 1.6k
Patrick P.C. Boor Netherlands 26 1.0k 1.0× 430 0.6× 1.1k 2.1× 334 1.4× 181 1.0× 47 2.1k

Countries citing papers authored by Zhong-Jun Xia

Since Specialization
Citations

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

Fields of papers citing papers by Zhong-Jun Xia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zhong-Jun Xia. 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 Zhong-Jun Xia. The network helps show where Zhong-Jun Xia may publish in the future.

Co-authorship network of co-authors of Zhong-Jun Xia

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

All Works

20 of 20 papers shown
1.
Wang, Jing‐Hua, Xi-Wen Bi, Pengfei Li, et al.. (2017). Overexpression of MYC and BCL2 Predicts Poor Prognosis in Patients with Extranodal NK/T-cell Lymphoma, Nasal Type. Journal of Cancer. 8(5). 793–800. 14 indexed citations
2.
Wang, Hua, et al.. (2016). High level of interleukin-10 in serum predicts poor prognosis in multiple myeloma. British Journal of Cancer. 114(4). 463–468. 52 indexed citations
3.
Yan, Zheng, Hui-Qiang Huang, Xiao-Xiao Wang, et al.. (2015). A TNM Staging System for Nasal NK/T-Cell Lymphoma. PLoS ONE. 10(6). e0130984–e0130984. 17 indexed citations
4.
Wang, Zhao, et al.. (2015). CD56-negative extranodal NK/T cell lymphoma should be regarded as a distinct subtype with poor prognosis. Tumor Biology. 36(10). 7717–7723. 15 indexed citations
5.
Liu, Yan Hui, Jie Chen, Qi-rong Geng, et al.. (2015). The prognostic nutritional index predicts survival for patients with extranodal natural killer/T cell lymphoma, nasal type. Annals of Hematology. 94(8). 1389–1400. 32 indexed citations
6.
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Wang, Liang, Zhong-Jun Xia, Yue Lu, & Yu‐Jing Zhang. (2014). Prophylactic cervical lymph node irradiation provides no benefit for patients of stage IE extranodal natural killer/T cell lymphoma, nasal type. Medical Oncology. 32(1). 320–320. 5 indexed citations
9.
10.
Wang, Kefeng, Xiaoqin Chen, Zhihui Wang, et al.. (2014). Long-term outcomes of modified Berlin–Frankfurt–Münster-90 regimen in adults with T-lymphoblastic lymphoma: a single-center experience. Leukemia & lymphoma. 55(8). 1800–1805. 11 indexed citations
11.
Zhang, Xu, et al.. (2014). Use of subsequent PET/CT in diffuse large B-cell lymphoma patients in complete remission following primary therapy. Chinese Journal of Cancer. 34(2). 70–78. 8 indexed citations
12.
Wang, Liang, et al.. (2014). Hepatitis B virus infection correlates with poor prognosis of extranodal natural killer/T cell lymphoma. Leukemia & lymphoma. 56(4). 936–941. 8 indexed citations
13.
Li, Zhiming, Hui-Qiang Huang, Zhong-Jun Xia, et al.. (2013). Prognostic Value of Interim and Posttherapy 18F-FDG PET/CT in Patients with Mature T-Cell and Natural Killer Cell Lymphomas. Journal of Nuclear Medicine. 54(4). 507–515. 28 indexed citations
14.
Li, Zhiming, Yi Xia, Hui-Qiang Huang, et al.. (2013). Serum C-Reactive Protein (CRP) as a Simple and Independent Prognostic Factor in Extranodal Natural Killer/T-Cell Lymphoma, Nasal Type. PLoS ONE. 8(5). e64158–e64158. 41 indexed citations
15.
Jiang, Wen-Qi, Hui-Lan Rao, Jia-Jia Huang, et al.. (2012). Expression of BAFF and BAFF-R in Follicular Lymphoma: Correlation with Clinicopathologic Characteristics and Survival Outcomes. PLoS ONE. 7(12). e50936–e50936. 21 indexed citations
16.
Wang, Feng, Shuqiang Yuan, Celia Garcı́a-Prieto, et al.. (2012). High hepatitis B virus infection in B-cell lymphoma tissue and its potential clinical relevance. European Journal of Cancer Prevention. 21(3). 261–267. 22 indexed citations
17.
Li, Zhiming, Hui-Lan Rao, Yi Xia, et al.. (2012). CD20-negative de novo diffuse large B-cell lymphoma in HIV-negative patients: A matched case-control analysis in a single institution. Journal of Translational Medicine. 10(1). 84–84. 19 indexed citations
18.
Wang, Hua, et al.. (2011). Induction therapy using the MRC UKALLXII/ECOG E2993 protocol in Chinese adults with acute lymphoblastic leukemia. International Journal of Hematology. 94(2). 163–168. 3 indexed citations
19.
Huang, Jia-Jia, Wen-Qi Jiang, Rui‐Hua Xu, et al.. (2010). Primary gastric non-Hodgkin's lymphoma in Chinese patients: clinical characteristics and prognostic factors. BMC Cancer. 10(1). 358–358. 28 indexed citations
20.
Lin, Hui, et al.. (2009). Correlation between peripheral blood CD4+CD25high CD127low regulatory T cell and clinical characteristics of patients with non-Hodgkin's lymphoma. Chinese Journal of Cancer. 28(11). 1186–1192. 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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