Sani H. Kizilbash

2.1k total citations · 1 hit paper
76 papers, 1.4k citations indexed

About

Sani H. Kizilbash is a scholar working on Genetics, Pulmonary and Respiratory Medicine and Oncology. According to data from OpenAlex, Sani H. Kizilbash has authored 76 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Genetics, 32 papers in Pulmonary and Respiratory Medicine and 24 papers in Oncology. Recurrent topics in Sani H. Kizilbash's work include Glioma Diagnosis and Treatment (59 papers), Brain Metastases and Treatment (21 papers) and Meningioma and schwannoma management (12 papers). Sani H. Kizilbash is often cited by papers focused on Glioma Diagnosis and Treatment (59 papers), Brain Metastases and Treatment (21 papers) and Meningioma and schwannoma management (12 papers). Sani H. Kizilbash collaborates with scholars based in United States, United Kingdom and Canada. Sani H. Kizilbash's co-authors include Jann N. Sarkaria, William F. Elmquist, Jan C. Buckner, Janice K. Laramy, Caterina Giannini, Nadia N. Laack, Paul D. Brown, Nathalie Y.R. Agar, Evanthia Galanis and Ian F. Parney and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Sani H. Kizilbash

68 papers receiving 1.3k 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.

Is the blood–brain barrier really disrupted in all glioblastomas? A critical assessment of existing clinical data

2017 504 citations Jann N. Sarkaria, Leland Hu et al. Neuro-Oncology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sani H. Kizilbash United States	16	748	453	444	284	202	76	1.4k
An Claes Netherlands	13	503 0.7×	548 1.2×	354 0.8×	253 0.9×	115 0.6×	17	1.3k
David Tran United States	20	568 0.8×	528 1.2×	485 1.1×	253 0.9×	142 0.7×	39	1.4k
Jay‐Jiguang Zhu United States	25	1.0k 1.4×	384 0.8×	294 0.7×	345 1.2×	242 1.2×	88	1.7k
Mackenzie Price United States	8	921 1.2×	433 1.0×	204 0.5×	325 1.1×	135 0.7×	22	1.6k
Tali Voloshin Israel	19	495 0.7×	490 1.1×	404 0.9×	232 0.8×	441 2.2×	79	1.4k
Corey Neff United States	11	993 1.3×	463 1.0×	223 0.5×	368 1.3×	149 0.7×	22	1.8k
Jenny L. Pokorny United States	13	496 0.7×	719 1.6×	405 0.9×	151 0.5×	96 0.5×	21	1.2k
David A. Nathanson United States	23	346 0.5×	581 1.3×	328 0.7×	218 0.8×	193 1.0×	63	1.4k
Dana Cernea Romania	8	1.4k 1.9×	595 1.3×	462 1.0×	557 2.0×	224 1.1×	16	2.0k
Jordonna Fulop United States	2	929 1.2×	441 1.0×	213 0.5×	292 1.0×	122 0.6×	2	1.6k

Countries citing papers authored by Sani H. Kizilbash

Since Specialization

Citations

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

Fields of papers citing papers by Sani H. Kizilbash

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sani H. Kizilbash. 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 Sani H. Kizilbash. The network helps show where Sani H. Kizilbash may publish in the future.

Co-authorship network of co-authors of Sani H. Kizilbash

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

All Works

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20 of 20 papers shown

Breen, William G., Jesse G. Dixon, S. Keith Anderson, et al.. (2025). Final report on North Central Cancer Treatment Group N0877 (alliance): A phase II randomized, placebo-controlled trial of chemoradiotherapy with or without dasatinib for glioblastoma. Neuro-Oncology. 27(10). 2661–2670.

Chelakkot, Vipin Shankar, Paul A. Decker, Katrina K. Bakken, et al.. (2025). Transcriptomic analysis identifies a potential target for bevacizumab resistant glioblastoma. Scientific Reports. 15(1). 36860–36860.

Jenkins, Robert B., et al.. (2024). Prognostic factors of grade 4 IDH-mutant astrocytoma.. Journal of Clinical Oncology. 42(16_suppl). e14019–e14019.

Sener, Uğur, et al.. (2024). Antiangiogenic exclusion rules in glioma trials: Historical perspectives and guidance for future trial design. Neuro-Oncology Advances. 6(1). vdae039–vdae039. 4 indexed citations

Desai, Aakash, Daheui Choi, Þorvarður R. Hálfdánarson, et al.. (2024). Molecular Characterization and Therapeutic Opportunities in KRAS Wildtype Pancreatic Ductal Adenocarcinoma. Cancers. 16(10). 1861–1861. 1 indexed citations

Lacey, Jean M., Lucas P. Carlstrom, Arthur E. Warrington, et al.. (2023). Cerebrospinal fluid 2-hydroxyglutarate as a monitoring biomarker for IDH-mutant gliomas. Neuro-Oncology Advances. 5(1). vdad061–vdad061. 9 indexed citations

Foster, Nathan R., Yanyan Lou, Yujie Zhao, et al.. (2023). A phase I trial of sequential dosing of sonidegib and pembrolizumab in advanced solid tumors (aST) and non–small-cell lung cancer (NSCLC).. Journal of Clinical Oncology. 41(16_suppl). 9093–9093. 2 indexed citations

Webb, Mason, Bryan J. Neth, Jamie J. Van Gompel, et al.. (2023). Withdrawal of bevacizumab is associated with rebound growth of vestibular schwannomas in neurofibromatosis type 2-related schwannomatosis patients. Neuro-Oncology Advances. 5(1). vdad123–vdad123. 4 indexed citations

Atkinson, John L. D., et al.. (2023). Contemporary Treatment Outcome of Metastases to the Pituitary Gland. World Neurosurgery. 172. e684–e694. 2 indexed citations

10.

Conte, Gian Marco, Mana Moassefi, Shahriar Faghani, et al.. (2023). NIMG-57. PERFORMANCE OF DEEP LEARNING IN MGMT PROMOTER METHYLATION STATUS PREDICTION USING BRAIN MRI: RESULTS FROM A LARGE COHORT OF IDH-WILDTYPE GLIOMAS TESTED BY A SINGLE METHYLATION ASSAY. Neuro-Oncology. 25(Supplement_5). v199–v199. 1 indexed citations

11.

Ensign, Shannon P. Fortin, Robert B. Jenkins, Caterina Giannini, et al.. (2022). Translational significance of CDKN2A/B homozygous deletion in isocitrate dehydrogenase-mutant astrocytoma. Neuro-Oncology. 25(1). 28–36. 20 indexed citations

12.

Kizilbash, Sani H., Shiv K. Gupta, Karen E. Parrish, et al.. (2021). In Vivo Efficacy of Tesevatinib in EGFR -Amplified Patient-Derived Xenograft Glioblastoma Models May Be Limited by Tissue Binding and Compensatory Signaling. Molecular Cancer Therapeutics. 20(6). 1009–1018. 10 indexed citations

13.

Ida, Cristiane M., Derek R. Johnson, Mohammed Ali Alvi, et al.. (2021). Diffuse Gliomas of the Brainstem and Cerebellum in Adults Show Molecular Heterogeneity. The American Journal of Surgical Pathology. 45(8). 1082–1090. 15 indexed citations

14.

Gupta, Shiv K., Emily J. Smith, Ann C. Mladek, et al.. (2019). PARP Inhibitors for Sensitization of Alkylation Chemotherapy in Glioblastoma: Impact of Blood-Brain Barrier and Molecular Heterogeneity. Frontiers in Oncology. 8. 670–670. 59 indexed citations

15.

Kizilbash, Sani H., Shiv K. Gupta, Kenneth Tou En Chang, et al.. (2017). Restricted Delivery of Talazoparib Across the Blood–Brain Barrier Limits the Sensitizing Effects of PARP Inhibition on Temozolomide Therapy in Glioblastoma. Molecular Cancer Therapeutics. 16(12). 2735–2746. 60 indexed citations

16.

Sarkaria, Jann N., Leland Hu, Ian F. Parney, et al.. (2017). Is the blood–brain barrier really disrupted in all glioblastomas? A critical assessment of existing clinical data. Neuro-Oncology. 20(2). 184–191. 504 indexed citations breakdown →

17.

Parrish, Karen E., Ling Cen, J. C. Murray, et al.. (2015). Efficacy of PARP Inhibitor Rucaparib in Orthotopic Glioblastoma Xenografts Is Limited by Ineffective Drug Penetration into the Central Nervous System. Molecular Cancer Therapeutics. 14(12). 2735–2743. 66 indexed citations

18.

Gupta, Shiv K., Sani H. Kizilbash, Brett L. Carlson, et al.. (2015). Delineation ofMGMTHypermethylation as a Biomarker for Veliparib-Mediated Temozolomide-Sensitizing Therapy of Glioblastoma. JNCI Journal of the National Cancer Institute. 108(5). djv369–djv369. 93 indexed citations

19.

Gupta, Shiv K., Ann C. Mladek, Brett L. Carlson, et al.. (2014). Discordant In Vitro and In Vivo Chemopotentiating Effects of the PARP Inhibitor Veliparib in Temozolomide-Sensitive versus -Resistant Glioblastoma Multiforme Xenografts. Clinical Cancer Research. 20(14). 3730–3741. 57 indexed citations

20.

Kizilbash, Sani H., Caterina Giannini, Jesse S. Voss, et al.. (2014). The impact of concurrent temozolomide with adjuvant radiation and IDH mutation status among patients with anaplastic astrocytoma. Journal of Neuro-Oncology. 120(1). 85–93. 30 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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