L. Pusztai

781 total citations
23 papers, 534 citations indexed

About

L. Pusztai is a scholar working on Oncology, Cancer Research and Pulmonary and Respiratory Medicine. According to data from OpenAlex, L. Pusztai has authored 23 papers receiving a total of 534 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Oncology, 17 papers in Cancer Research and 9 papers in Pulmonary and Respiratory Medicine. Recurrent topics in L. Pusztai's work include Breast Cancer Treatment Studies (14 papers), Cancer Immunotherapy and Biomarkers (5 papers) and Cancer Genomics and Diagnostics (5 papers). L. Pusztai is often cited by papers focused on Breast Cancer Treatment Studies (14 papers), Cancer Immunotherapy and Biomarkers (5 papers) and Cancer Genomics and Diagnostics (5 papers). L. Pusztai collaborates with scholars based in United States, Italy and Germany. L. Pusztai's co-authors include Thomas Karn, Cornelia Liedtke, Achim Rody, R. Gaetje, Manfred Kaufmann, A. Ahr, Knut Engels, Dirk Metzler, Christine Solbach and Lars Hanker and has published in prestigious journals such as Journal of Clinical Oncology, Cancer Research and Annals of Oncology.

In The Last Decade

L. Pusztai

23 papers receiving 526 citations

Peers

L. Pusztai
Borbála Székely Hungary
Antonios Papanicolau‐Sengos United States
Marco Torregroza Otero Spain
Anton Safonov United States
Lisa Flaum United States
Marit Synnestvedt Norway
Manuel Ruíz Borrego Spain
Sanna Madan United States
Ruslan D. Novosiadly United States
Alexandre Houy France
Borbála Székely Hungary
L. Pusztai
Citations per year, relative to L. Pusztai L. Pusztai (= 1×) peers Borbála Székely

Countries citing papers authored by L. Pusztai

Since Specialization
Citations

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

Fields of papers citing papers by L. Pusztai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of L. Pusztai

This figure shows the co-authorship network connecting the top 25 collaborators of L. Pusztai. A scholar is included among the top collaborators of L. Pusztai 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 L. Pusztai. L. Pusztai 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.
Bottai, Giulia, Ahmed Nagy, L. Pusztai, et al.. (2017). Abstract P1-07-06: Immune signatures define and affect prognosis in triple-negative breast cancer subtypes. Cancer Research. 77(4_Supplement). P1–7. 1 indexed citations
2.
Liedtke, Cornelia, Ken Hess, Thomas Karn, et al.. (2013). The prognostic impact of age in patients with triple-negative breast cancer. Breast Cancer Research and Treatment. 138(2). 591–599. 70 indexed citations
3.
Wei, Changyuan, et al.. (2013). Abstract S6-02: Long-term prognostic value of residual cancer burden (RCB) classification following neoadjuvant chemotherapy. Cancer Research. 73(24_Supplement). S6–2. 7 indexed citations
4.
Valagussa, Pinuccia, et al.. (2012). Abstract S6-7: Adaptive immune system and immune checkpoints are associated with response to pertuzumab (P) and trastuzumab (H) in the NeoSphere study. Cancer Research. 72(24_Supplement). S6–7. 19 indexed citations
5.
Székely, Borbála & L. Pusztai. (2011). The Value of Genomic Analysis of Breast Cancer in Drug Development. JNCI Monographs. 2011(43). 60–62. 1 indexed citations
6.
Delpech, Yann, Roman Rouzier, Joseph Gligorov, et al.. (2011). P2-12-06: Nomogram To Predict Subsequent Bone Metastasis in Patients with Non Metastatic Breast Carcinomas.. Cancer Research. 71(24_Supplement). P2–12. 1 indexed citations
7.
Rody, Achim, Thomas Karn, C Liedtke, et al.. (2010). Abstract S5-5: Identification of a Clinically Relevant Gene Signature in Triple Negative and Basal-Like Breast Cancer. Cancer Research. 70(24_Supplement). S5–5. 4 indexed citations
8.
Pusztai, L., Stacy L. Moulder, Jennifer K. Litton, et al.. (2010). Gene-signature-based patient selection for dasatinib therapy in metastatic breast cancer (MBC).. Journal of Clinical Oncology. 28(15_suppl). TPS130–TPS130. 1 indexed citations
9.
Rody, Achim, Uwe Holtrich, L. Pusztai, et al.. (2009). T-cell metagene predicts a favorable prognosis in estrogen receptor-negative and HER2-positive breast cancers. Breast Cancer Research. 11(2). R15–R15. 336 indexed citations
10.
Pusztai, Lajos, et al.. (2009). A specific nomogram to predict subsequent brain metastasis in metastatic triple-negative breast cancer patients. Journal of Clinical Oncology. 27(15_suppl). 1028–1028. 2 indexed citations
11.
Caudle, Abigail S., Ana M. González-Angulo, P. Liu, et al.. (2009). Predictors of tumor progression during neoadjuvant chemotherapy in breast cancer. Journal of Clinical Oncology. 27(15_suppl). 603–603. 4 indexed citations
12.
Pusztai, L., Christos Hatzis, Fátima Cardoso, et al.. (2008). Combined use of genomic prognostic and treatment response predictors in breast cancer. Journal of Clinical Oncology. 26(15_suppl). 527–527. 4 indexed citations
13.
Moulder, SL, Linda Hsu, Shu‐Wan Kau, et al.. (2008). Prognostic impact of discordance/concordance of triple-receptor expression between primary tumor and metastasis in patients with metastatic breast cancer. Journal of Clinical Oncology. 26(15_suppl). 1001–1001. 7 indexed citations
14.
Gianni, Lorenzo, W. Eiermann, L. Pusztai, et al.. (2008). Biomarkers as potential predictors of pathologic complete response (pCR) in the NOAH trial of neoadjuvant trastuzumab in patients (pts) with HER2-positive locally advanced breast cancer (LABC). Journal of Clinical Oncology. 26(15_suppl). 504–504. 10 indexed citations
15.
Dean‐Colomb, Windy, Kai Yan, C Liedtke, et al.. (2008). Transcriptional profiles of triple receptor-negative breast cancer: Are Caucasian, Hispanic, and African-American women different?. Journal of Clinical Oncology. 26(15_suppl). 22014–22014. 9 indexed citations
16.
Hatzis, Christos, W. Fraser Symmans, Bingxin Zheng, et al.. (2008). Genomic predictors of pathologic response to preoperative chemotherapy for triple-negative and ER-positive/HER2-negative breast cancers. Journal of Clinical Oncology. 26(15_suppl). 571–571. 3 indexed citations
17.
André, Fabrice, Rita Nahta, Rosa Conforti, et al.. (2007). Expression patterns and predictive value of phosphorylated AKT in early-stage breast cancer. Annals of Oncology. 19(2). 315–320. 32 indexed citations
18.
Mazouni, Chafika, Florentia Peintinger, Fabrice André, et al.. (2007). Effect on patient outcome of residual DCIS in patients with complete eradication of invasive breast cancer after neoadjuvant chemotherapy. Journal of Clinical Oncology. 25(18_suppl). 530–530. 4 indexed citations
19.
Rouzier, Roman, Fabrice André, R. Arriagada, et al.. (2005). Individual benefits from adjuvant anthracycline-based chemotherapy can be predicted from a predictive nomogram created from primary chemotherapy (PC) data: Results of a randomized trial. Journal of Clinical Oncology. 23(16_suppl). 623–623. 5 indexed citations
20.
Pusztai, L., B. Gregory, Francisco J. Esteva, et al.. (2004). Pharmacoproteomic analysis of pre-and post-chemotherapy plasma samples from patients receiving neoadjuvant or adjuvant chemotherapy for breast cancer. Journal of Clinical Oncology. 22(14_suppl). 2109–2109. 6 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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