Roberto Labianca

39.1k total citations · 13 hit papers
323 papers, 21.9k citations indexed

About

Roberto Labianca is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Pathology and Forensic Medicine. According to data from OpenAlex, Roberto Labianca has authored 323 papers receiving a total of 21.9k indexed citations (citations by other indexed papers that have themselves been cited), including 234 papers in Oncology, 137 papers in Pulmonary and Respiratory Medicine and 77 papers in Pathology and Forensic Medicine. Recurrent topics in Roberto Labianca's work include Colorectal Cancer Treatments and Studies (154 papers), Gastric Cancer Management and Outcomes (87 papers) and Genetic factors in colorectal cancer (65 papers). Roberto Labianca is often cited by papers focused on Colorectal Cancer Treatments and Studies (154 papers), Gastric Cancer Management and Outcomes (87 papers) and Genetic factors in colorectal cancer (65 papers). Roberto Labianca collaborates with scholars based in Italy, France and United States. Roberto Labianca's co-authors include Giordano Beretta, Daniel J. Sargent, Bernard Nordlinger, Mario Mandalà, Eric Van Cutsem, Stefania Mosconi, Alberto Zaniboni, Stefano Cascinu, Richard M. Goldberg and Sandro Barni and has published in prestigious journals such as New England Journal of Medicine, The Lancet and Journal of Clinical Oncology.

In The Last Decade

Roberto Labianca

316 papers receiving 21.3k citations

Hit Papers

Defective Mismatch Repair... 1998 2026 2007 2016 2010 2013 2009 1998 2005 250 500 750 1000

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Roberto Labianca 15.4k 5.8k 5.2k 4.5k 3.2k 323 21.9k
Jeffrey A. Meyerhardt 16.3k 1.1× 4.3k 0.7× 5.4k 1.0× 3.3k 0.7× 3.9k 1.2× 431 25.8k
Richard L. Schilsky 13.8k 0.9× 6.0k 1.0× 3.2k 0.6× 2.3k 0.5× 5.3k 1.7× 382 23.2k
Nicholas J. Petrelli 10.8k 0.7× 4.0k 0.7× 3.3k 0.6× 6.0k 1.3× 2.1k 0.7× 301 16.6k
Filippo de Braud 17.9k 1.2× 8.8k 1.5× 3.3k 0.6× 5.6k 1.3× 3.7k 1.2× 754 26.7k
Daniel G. Haller 16.8k 1.1× 9.2k 1.6× 4.6k 0.9× 8.7k 1.9× 2.3k 0.7× 243 25.2k
Richard M. Goldberg 24.0k 1.6× 8.3k 1.4× 9.7k 1.9× 6.9k 1.5× 4.9k 1.5× 531 33.3k
Andrés Cervantes 18.1k 1.2× 9.4k 1.6× 3.9k 0.8× 8.4k 1.9× 3.3k 1.0× 468 27.8k
Stefano Cascinu 11.2k 0.7× 7.3k 1.3× 2.6k 0.5× 3.4k 0.8× 3.4k 1.1× 648 18.3k
Shaker R. Dakhil 9.2k 0.6× 5.1k 0.9× 3.0k 0.6× 1.4k 0.3× 3.1k 1.0× 313 16.4k
Hans‐Joachim Schmoll 9.8k 0.6× 4.6k 0.8× 2.4k 0.5× 7.5k 1.7× 1.3k 0.4× 541 19.2k

Countries citing papers authored by Roberto Labianca

Since Specialization
Citations

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

Fields of papers citing papers by Roberto Labianca

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Roberto Labianca

This figure shows the co-authorship network connecting the top 25 collaborators of Roberto Labianca. A scholar is included among the top collaborators of Roberto Labianca 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 Roberto Labianca. Roberto Labianca 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
2.
Argilés, Guillem, Josep Tabernero, Roberto Labianca, et al.. (2020). Localised colon cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Annals of Oncology. 31(10). 1291–1305. 736 indexed citations breakdown →
5.
Gelsomino, Fabio, Valter Torri, Alberto Zaniboni, et al.. (2017). Sidedness influences prognosis in colon cancer patients receiving an adjuvant therapy. A GISCAD analysis from three randomized trials including 5234 patients. Annals of Oncology. 28. vi5–vi5. 2 indexed citations
6.
Graziano, Francesco, Annamaria Ruzzo, Eliana Rulli, et al.. (2016). Dihydropyrimidine dehydrogenase (DPYD) gene polymorphisms profiling in colon cancer patients treated with adjuvant chemotherapy in the randomized phase III TOSCA trial. Annals of Oncology. 27. iv1–iv1. 1 indexed citations
7.
Personeni, Nicola, Lorenza Rimassa, Claudio Verusio, et al.. (2015). FOLFIRI and Cetuximab Every Second Week for First-Line Treatment of KRAS Wild-Type Metastatic Colorectal Cancer According to Phosphatase and Tensin Homolog Expression: A Phase II Study. Clinical Colorectal Cancer. 14(3). 162–169. 9 indexed citations
8.
Hubbard, Joleen M., David M. Thomas, Greg Yothers, et al.. (2012). Benefits and Adverse Events in Younger Versus Older Patients Receiving Adjuvant Chemotherapy for Colon Cancer: Findings From the Adjuvant Colon Cancer Endpoints Data Set. Journal of Clinical Oncology. 30(19). 2334–2339. 32 indexed citations
9.
Labianca, Roberto, Barbara Merelli, & Stefania Mosconi. (2012). Treatment of advanced pancreatic cancer. Annals of Oncology. 23. x139–x140. 6 indexed citations
10.
Sargent, Daniel J., Silvia Marsoni, Geneviève Monges, et al.. (2010). Defective Mismatch Repair As a Predictive Marker for Lack of Efficacy of Fluorouracil-Based Adjuvant Therapy in Colon Cancer. Journal of Clinical Oncology. 28(20). 3219–3226. 1114 indexed citations breakdown →
11.
Roth, A., Dirk Klingbiel, Ping Yan, et al.. (2010). Molecular and clinical determinants of survival following relapse after treatment of stage ii-iii colon cancer (cc). results of the translational study on the petacc 3-eortc 40993-sakk 60-00 trial. Annals of Oncology. 21. 16–16. 2 indexed citations
12.
Roth, A., Sabine Tejpar, Ping Yan, et al.. (2009). Molecular markers in colon cancer have a stage specific prognostic value. results of the translational study on the petacc 3-eortc 40883-sakk 60-00 trial. Annals of Oncology. 20. 7–7. 7 indexed citations
13.
Mandalà, Mario, Sandro Barni, Martin H. Prins, et al.. (2009). Acquired and inherited risk factors for developing venous thromboembolism in cancer patients receiving adjuvant chemotherapy: a prospective trial. Annals of Oncology. 21(4). 871–876. 79 indexed citations
14.
Taylor, Paul, B. Castagneto, G. Dark, et al.. (2008). Single-Agent Pemetrexed for Chemonaïve and Pretreated Patients with Malignant Pleural Mesothelioma: Results of an International Expanded Access Program. Journal of Thoracic Oncology. 3(7). 764–771. 39 indexed citations
17.
Brambilla, L., et al.. (2000). Chemioterapia nel sarcoma di Kaposi mediterraneo: 20 anni di esperienza. Redia-Giornale Di Zoologia. 135(4). 433–437. 1 indexed citations
18.
Labianca, Roberto, et al.. (1997). Errata: Treatment of colorectal cancer: Current guidelines and future prospects for drug therapy (Drugs (1997) 53 (593-607)). Drugs. 54(1). 9 indexed citations
19.
Pizzocaro, Giorgio, Luigi Piva, Massimo Meregalli, et al.. (1995). Subcutaneous administration of interleukin 2 and interferon-alpha-2b in advanced renal cell carcinoma: a confirmatory study. British Journal of Cancer. 72(6). 1531–1535. 16 indexed citations
20.
Brambilla, L., Roberto Labianca, Silvia Fossati, et al.. (1995). Vinorelbine: An active drug in Mediterranean Kaposi's sarcoma. European Journal of Dermatology. 5(6). 467–469. 5 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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