The Web of Science Core Collection (WoSCC) is a comprehensive scholarly treasure trove covering more than 190 subject areas worldwide. The database is widely recognized as an outstanding resource for bibliometric research in a variety of disciplines, providing superior literature retrieval and citation analysis services (Han et al., 2023).

The study used bibliometric analysis and visualization software, including R 4.3.0, BiblioMetrix, Citespace, VOSviewer, SCImago Graphica, and the online tool MapEquation.

This study used R (v4.3.0) to perform descriptive statistics and visualization. The fitted model for the trend analysis of the number of articles is the formula = y ∼ poly (x, 2). The fitted curve is a quadratic polynomial model based on the year x) and the number of publications y). The trend of the number of publications and the yearly citation trend are visualized in this study using the ggplot2 package.

We used line graphs to present in detail the trend of growth in the number of papers and the trend of annual citation frequency in the field of head and neck cancer drug resistance research in the WoSCC database for the period from 2000 to 2023. In the overall study, we used R to fit a nonlinear model. This reveals the macro-trend that academic publications in this field are on the rise. In addition, we analyze this trend in depth by phase. Figure 2A shows a relatively flat growth trend in paper numbers between 2000 and 2010. Between 2011 and 2022, however, the number of papers in this field increased significantly. Taken together, our analysis reveals that drug resistance research in head and neck cancer has flourished, especially in recent years. This provides valuable insights into academic medicine.

In addition, we analyzed annual citation trends. As shown in Figure 2B, the trend can be divided into three parts: fluctuating (2000-2008), stable (2009-2017), and decreasing year by year (2018-2023). Combined with the trend of publications, we come up with five reasons: 1) Low-quality research: the increased number of publications may originate from low-quality or insufficiently influential research, which fails to attract other scholars’ attention and citations. Fragmentation of the field: As the number of publications increases, research may become more fragmented rather than concentrated on a few high-impact papers, which may lead to a decline in overall citations. 3) Citation lag: It may take time for citations to reflect the impact of research, and if the latest literature has not yet been fully cited, a decline in citations may be observed initially. 4) Changes in research direction: Changes in research direction within the field may cause a decline in citations. Citations may decrease if the proposed direction is not widely recognized or does not attract enough interest from the academic community.

In summary, head and neck cancer drug resistance research has shown significant growth between 2000 and 2023, especially explosive growth in recent years. The annual citation trend undergoes three phases of fluctuation, stabilization, and gradual decrease. This may be influenced by factors such as low-quality studies, field fragmentation, citation lag, changes in research direction, and potential data insufficiency or short-term fluctuations. These findings provide deep insights into the current state and trends of the field domain.

The analysis of national publications and citation frequency provides a powerful tool for understanding the scientific ecosystem, international partnerships, and assessing a country’s position and influence in the field of head and neck cancer drug resistance research. Supplementary Table S1 analyzes national publication volume and citation frequency. Figure 3A shows that China, the United States, and Japan are in the top three countries in terms of national publications. In addition, China, the United States, and South Korea are in the top three countries in terms of standardized citations. These figures may reflect the overall research strength and activity of China, the U.S., and Japan in this field. In addition, the citation performance hints at these countries’ academic influence. South Korea’s performance in citation frequency compared with Japan may imply that its research in the field or direction of head and neck cancer drug resistance research has relatively higher academic value.

In addition, we analysed the collaborative connections between countries and institutions in drug resistance research in head and neck cancer. This was done to reveal the current status of international academic exchanges in this field. First, in Figure 3B, the strength of collaborative connections between countries is categorized into three clusters, among which the strength of collaboration between China and the United States is high and in the same category. Second, the United States acts as a key cooperation bridge between these three clusters. In addition, Figure 3C shows that Chinese medical universities lead the number of publications in this research area. Finally, Texas M. D. Anderson Cancer Research Center, on the other hand, acts as a link between these three clusters. It provides key support for drug resistance research in head and neck cancer.

In the field of drug resistance research in head and neck cancer, an in-depth analysis of the authors’ contributions is intended to provide a better understanding of the dynamics of scientific research in the field, especially those researchers who have achieved remarkable results in overcoming therapeutic resistance.

Figure 4A visualizes the top 10 authors in terms of posts and highlights Citespace software users. Among the top 10 authors in terms of posts, Grandis Jennifer R and Yang Jai-Sing are at the top of the list with 13 posts each. In addition, the authors highlighted in red, Osmak Maja, Kim Eun Hye, Roh Jong-Lyel, and Lu Chi-Cheng, excelled in citations and were the most popular authors in the TOP4. Meanwhile, in Supplementary Figure S1, we present a timeline plot of the citation prominence of these four authors. Among them, Kim Eun Hye has the highest citation burst intensity of 4.32, lasting from 2016 to 2018.

In order to gain a deeper understanding of the research direction of authors in the field of head and neck cancer drug resistance research, we used LLR cluster analysis to obtain 46 clusters, in which the clusters from #0 to #46 were arranged in decreasing order of the number of authors. Meanwhile, analyzing the authors in combination with the TOP10 authors, we found that these authors were covered in 5 clusters. In Figure 4B, we show that authors with TOP10 publication volume were clustered into “#0 cetuximab”, “#4 osteopontin overexpression”, “#10 apoptosis”, “#29 cellular accumulation”, and “#34 pi3k inhibitor” in these five taxa. Therefore, through the analysis, we learned that these five taxa represent the research directions of TOP10 posting authors in the field of head and neck cancer drug resistance research.

In addition, we counted the publication volume, H-index, G-index and M-index of the TOP10 authors in this field in Supplementary Tables S2–S5, and further evaluated their scholarly influence and contribution to the field of head and neck cancer drug resistance research. First, in Figure 4C, we take the intersection of the authors of the TOP 10 of the above four indices using a Wayne diagram. This will enable us to obtain nine authors. Second, Figure 4D shows the annual publication volume of these nine authors. These nine authors have significantly contributed to the progress and development of head and neck cancer drug resistance research. They have done this with their excellent research output, high academic impact, and wide number of citations. Finally, Table 1 shows the institutions, publication volume, H-index, G-index, M-index, and total citation frequency of these nine authors. Their research results are of significant significance in guiding academic development and clinical practice of drug resistance research in head and neck cancer.

Keyword co-occurrence analysis of drug resistance studies in head and neck cancer can reveal the interrelationships between keywords in head and neck cancer drug resistance studies, which helps to identify research hotspots and potential association mechanisms. We performed statistics and visualization of author keywords with VOSViewer. Figure 5A shows the keyword heat map, with darker colors representing higher keyword frequencies. In order to gain a deeper understanding of the hotspots and trends in drug resistance research in head and neck cancer, we categorized the keywords for frequency analysis. First, in Table 2, we categorized the keywords into 3 types of treatment methods, drug-resistant types, and research topics, and counted the frequency of TOP10 keywords in these three categories. In head and neck cancer drug-resistant treatment methods, cisplatin, cetuximab and paclitaxel keywords were Top 3. Cisplatin-resistant, anti-radiation and multi-resistant keywords were Top 3 in the drug-resistant group, and apoptosis, autophagy, EMT, EGFR and Cancer stem cell keywords were Top 3 in the research theme group. These high-frequency keywords reflect ongoing research hotspots. Secondly, we supplemented the statistics of keyword frequency in Supplementary Tables S6, S7 for therapeutic approach and research topic groups. Among them, drugs such as tetrandrine, temsirolimus, and triptolide in the drug therapeutics group potentially increase the sensitivity of anti-head and neck cancer drugs. And keywords such as extracellular vesicles, tumor microenvironment, and ferroptosis in the research topic group may reflect potential research hotspots in this field.

Keyword clustering analysis, on the other hand, groups high-value keywords. This provides researchers with a systematic understanding of the drug resistance mechanism of head and neck cancer and a direction for in-depth exploration. We used Citespace software for LLR and LSI cluster analysis and keyword visualization. We set the clustering parameter to TOP N = 30/40/50, and obtained 16, 15, and 16 clusters, respectively (Figure 5B, Supplementary Figures S2, S3). Figure 5B shows that the TOP N = 30 visualization result contains 16 keyword clusters. The number of keywords in the clusters decreases in the direction of the arrows. In addition, we analyze the same clusters using different clustering algorithms. This is to determine the research direction of the #2, #5, #7, #8, #11, and #13 clusters. LSI clustering is shown in red font and LLR clustering is shown in black font in Figure 5C. #2 and #5 demonstrate multi-resistance versus radiotherapy sensitivity in nasopharyngeal cancer. #7, on the other hand, indicates that RT-PCR is a commonly used tool in drug resistance studies. #8 shows that coenzyme Q-related genes are associated with drug resistance. #11 reflects the relationship between recovery training and survival quality. Finally, #13 reflects the potential value of peptide vaccines as immunotherapeutic tools in anti-head and neck cancer resistance studies.

Further, we are interested in revealing the current research focus, research trends and innovative directions in drug resistance in head and neck cancer. We will do this by visualizing the annual keyword frequency heatmap based on keyword set theory and topic network construction. Figure 5D heatmap presents the normalized frequency of authors’ keywords during 2000–2023, with annual keyword frequency on the left and cumulative annual keyword frequency on the right. In terms of drug therapy, paclitaxel, immunotherapy, cisplatin resistance and cetuximab constitute the focus of drug resistance research in head and neck cancer. In terms of thematic research, “MicroRNA”, “Metastasis”, The keywords “Ferroptosis” and “AKT”, highlighted in blue, have become an emerging focus in the field of drug resistance research in head and neck cancer. In addition, in the upper right quadrant of Supplementary Figure S4, “cetuximab resistance”, “cisplatin-resistance”, “erlotinib ", “cisplatin-resistance”, “erlotinib” and “cell hypoxia” belong to the motor themes. These keywords have strong centrality and high density in head and neck cancer resistance research. They are conceptually closely related to other quadrant themes. The keyword categories “microarray” and “MTT assay” in the upper left quadrant have well-defined internal connections, but external connections are not relevant. The keywords in the lower left quadrant have themes that are neither developed nor significant. Topics in the lower right quadrant have relevant keywords to the research area, but are not developed. In summary, we have provided a comprehensive description of the hotspots and trends in drug resistance research in head and neck cancer. This is done through co-occurrence and clustering analysis of keywords.

Our literature co-citation and clustering analyses provide insights to systematically understand the hotspots of drug resistance research in head and neck cancer, assess the impact of scientific research, and reveal correlations between related subfields. Figure 6A presents the TOP10 most cited authors, with red highlighted authors. Siegel RL’s “Cancer statistics, 2019” (Siegel et al., 2019) and Agrawal N’s “Exome sequencing of head and neck squamous cell carcinoma reveals inactivating mutations in NOTCH1” (Agrawal et al., 2011) are the papers with the two authors with the high centrality. These two papers play a key role in bridging networks of information dissemination and communication. Academically, their contributions are highly influential and leading. Meanwhile, we present the papers that exploded in the field in Figure 6B using red circles based on the above. Further, we count the TOP 10 papers in terms of outbreak intensity in Figure 6C. During 2018–2023, the outbreak intensity of Chen YP (Chen et al., 2019) and Chua MLK (Chua et al., 2016) papers on Nasopharyngeal carcinoma was 9.86 and 6.84, respectively. This indicates that Nasopharyngeal carcinoma has been the focus of drug-resistant research in head and neck cancer for 5 years and is developing rapidly. In addition, we visualized the shock flow map of citation duration in Figure 6D. We screened the key papers that were consistently cited for more than 4 years. First, Xiao L and Hsieh MJ’s studies on improving cisplatin resistance and sensitivity to radiotherapy in nasopharyngeal carcinoma, respectively, received sustained attention (Xiao et al., 2014; Hsieh et al., 2019). Second, Herbst RS’s study on the effect of the PD-L1 antibody MPDL3280A on patients expressing high levels of PD-L1 in a variety of cancer types has been consistently cited for 6 years (Herbst et al., 2014). Finally, Xing MZ’s research on the mechanism of BRAF V600E mutation in thyroid cancer progression has been profoundly influenced by scholars in the field (Xing et al., 2015). In particular, the microRNA downregulation of Pallante P in thyroid cancer treatment and diagnosis continued to receive attention during 2016–2022 (Pallante et al., 2014). In summary, we dissected the key literature in drug resistance research in head and neck cancer from multiple perspectives. We provided insightful academic references for researchers, policymakers, and the academic community.

In addition, clustering analysis by literature co-citation helps us dig deeper into the knowledge structure and research focus of drug resistance research in head and neck cancer. We obtained 9 clusters, #0-#8, after keyword and title clustering and filtering the literature by citespace. We labeled the clusters using LSI and LLR algorithms. The size, silhouette, Mean, LSI, and LLR information of each cluster in the results of keyword clustering of the literature is shown in detail in Table 3. Further, we deeply analyzed the hotspot and field variation of drug resistance research in head and neck cancer. We did this by the dependency between the taxon labeling and the previous taxon. First, in Figure 7A, the time-series changes in the number of publications of the nine taxa are presented, and the vertical coordinates are the LLR and LSI labels of different taxa. Among them, “#1 Cancer Stem Cells” is a cluster containing 257 publications, suggesting that cancer stem cells may be the focus of attention in drug resistance research in head and neck cancer. Secondly, taxa #2-#6 LLR and LSI classification labels were consistent and contained a decreasing number of literature based on the taxon number, reflecting the hot topic of drug resistance research in head and neck cancer. However, taxon #7 represents “Ferroptosis” and “Cispaltin Resistance” respectively, which may indicate that the relationship between iron death and cisplatin resistance mechanism has received attention from scholars. Similarly, taxon #8 may indicate the correlation between drug resistance and ERK pathway in laryngeal squamous carcinoma. Finally, we visualized the dependencies between different clusters in the keyword and title clustering of #0-#8 literature through the citespace “Cluster Dependencies” module in Figure 7B and Supplementary Figure S5A, respectively. By analyzing the dependencies among different clusters, we are able to deduce the evolutionary patterns of the themes of each cluster. Finally, for ease of analysis, we simplify this evolutionary pattern in Figure 7C. Clearly, "#1 Cancer stem cell”, "#2 nasopharyngeal carcinoma” and "#4 thyroid cancer " developed into the "#0 SCCHN” theme. Similarly, the dependency analysis presenting the clustering results of the literature titles in Supplementary Figure S5 showed that the "#0 targeting EGFR resistance network” theme was built on the “#1 stem-like cell” and “#4 thyroid cancer” themes. “ and ”#2 thyroid cancer” clusters.

Taken together, the co-citation and clustering analysis of the literature in the field of head and neck cancer drug resistance research provided us with a deep insight into the research hotspots and the evolution of the key #0 to #8 clusters.

We analyzed journals in the field of drug resistance in head and neck cancer through Citespace’s “Overlay Maps”. Overlap analysis helps identify high-impact journals and papers to provide research direction. Figure 8A provides the necessary knowledge base for citing journals. The yellow #4 and green #2 paths in the journal biplot overlay mapping indicate that research published in journals related to “Molecular, Biological and Immunological” and “Medical, Medical and Clinical”, respectively, is usually cited in journals in the “Molecular, Biological and Genetic” field, which is colored #8 in pink. Specifically, the cited articles in “Molecular, Biology and Genetics” were primarily from Cancer Research and Clinical Cancer Research journals. In addition, we counted the impact factors, JCR quartiles, and open access (OA) information of the top 20 cited journals in Supplementary Table S8. These findings highlight the interconnectedness of different fields in the study of drug resistance in head and neck cancer. They also highlight the importance of interdisciplinary research in advancing scientific knowledge.

Furthermore, we analyzed the highly published and influential journals in the field of drug resistance in head and neck cancer. We used the “Bradford’s Law” module of the bibloshiny tool. According to Bradford’s Law, a small number of core journals contribute the majority of research output in the field. In contrast, most journals contribute relatively little. The left side of Figure 8B presents the overall picture and the right side shows the core journals. There are 20 core journals on the panel, of which the TOP3 journals are Oncotarget, Cancers, and Clinical Cancer Research. Further, we count the publication volume, H-index, impact factor, partitioning, and OA index of these 20 core journals in the field in Table 4. The first thing to note is that the journal Oncotarget has open access (OA) attributes and ranks first in the field with 25 articles and 19 H-indexes in the area of head and neck cancer drug resistance. However, it is worth pointing out that the journal is not included in the Science Citation Index (SCI) journal category. Second, Clinical Cancer Research demonstrated the highest overall drug resistance in head and neck cancer. This was in terms of number of articles, H-index, impact factor, and partitioning. Finally, of these 20 core journals, 11 are in the high impact factor quartile (Q1), 6 are in the medium quartile (Q2), and 2 are in the lower quartile (Q3). Of these, eight journals have an impact factor of more than 5, while seven are open access (OA) journals. Taken together, we gained more comprehensive access to the latest research findings about drug resistance in head and neck cancer. We did this by focusing exclusively on core journals in this area.

For patients with locally advanced and recurrent metastatic head and neck cancer, surgery and drug combination therapy have become the current mainstream recommended regimen. In Figure 9, we have combined the 2022 American Society of Clinical Oncology (ASCO) meeting and the 2023 Chinese Society of Clinical Oncology (CSCO) guidelines on head and neck cancer to provide an overview of current treatment strategies and drug combination options. In addition, we refer to new advances in head and neck cancer treatment presented at the ASCO 2023 meeting to guide future treatment regimens.

In the area of drug therapy for localized head and neck cancer, four academics’ protocols were included in the category of “future therapies”. Prof. Rosenberg says a neoadjuvant regimen based on nivolumab in combination with paclitaxel and carboplatin has shown significant survival and local control benefits in patients with highly advanced HPV-negative squamous head and neck cancer (Rosenberg et al., 2023). Meanwhile, the experimental II regimen introduced by Prof. Ferrarotto in the field of laryngeal cancer treatment showed excellent advantages in terms of laryngeal preservation rate, recurrence rate and survival rate (Ferrarotto et al., 2023). In addition, experimental regimens iii and iv proposed by Chinese doctors Xiao Min and Gui Lin have shown significant efficacy in the treatment of localized head and neck cancer (Gui et al., 2023; Ou et al., 2023).

The protocols of three authors have been included in the category of “future treatments” for recurrent metastatic head and neck cancers. First, a study from France treated 64 patients who could not receive cisplatin-based chemotherapy with regimen i, showing safety and efficacy in a vulnerable population (Fayette et al., 2023). Second, Prof. Hanna presented regimen ii (containing the EGFR/TGFβ bifunctional inhibitor BCA101 in combination with pembrolizumab), which showed significant efficacy in HPV-negative patients (Hanna et al., 2023). Finally, Dr. Xue Liqiong shared regimen iii (including the EGFR/HER3 bispecific antibody SI-B001 in combination with paclitaxel), which presented significant efficacy in patients who had not received paclitaxel (Xue et al., 2023). Of particular note is the growing importance of “de-chemotherapy” in the treatment of recurrent/metastatic head and neck cancer. In the 2023 edition of the CSCO Head and Neck Cancer Treatment Guidelines, targeted therapy in combination with immunotherapy is recommended as a level III therapy. This indicates that this treatment modality is being explored. As a result, recurrent/metastatic head and neck cancer may move toward a " De-chemotherapy " era in the future. These options are included in the category of “future treatments” for locally advanced head and neck cancer.

Additionally, targeted therapy combined with immunotherapy is recommended as a level III recommendation in the CSCO Head and Neck Cancer Treatment Guidelines 2023. This indicates that this treatment modality is being explored. As a result, head and neck cancer treatment may progress toward a " De-chemotherapy " era in the future.

We statistically analyzed head and neck cancer drug resistance trends from 2000 to 2023. We paid particular attention to the significant growth in recent years. Annual citation trends show three phases of fluctuation, plateauing, and decreasing over time. These phases may be due to low-quality research, fragmentation of the field, citation lag, changes in research direction, and potential data deficiencies or short-term fluctuations.

Continued global investment and in-depth exploration of basic drug resistance research in head and neck cancer has provided crucial impetus for advancing drug resistance research in head and neck cancer. In recent years, worldwide research on drug resistance in head and neck cancer has made progress, focusing on the following three aspects.

(1) Targeted therapy: This therapy kills tumor cells by inhibiting specific targets of tumor cells. Although targeted agents such as erlotinib and cetuximab have gained approval in the treatment of head and neck cancer, patients are often challenged by resistance to the targeted agents (Ratushny et al., 2009). Studies have revealed resistance mechanisms, including genetic mutations and signaling pathway reorganization (Chen et al., 2021; Li et al., 2022; Chan et al., 2023). These findings highlight limitations to therapy effectiveness. More in-depth studies are urgently needed to find effective strategies to overcome drug resistance to improve the survival of head and neck cancer patients.

Furthermore, individualized treatment, including stem cell (Küçükgüven and Çelebi-Saltik, 2021; Byun et al., 2022) and gene therapy. Medical professionals can use systematic genomic analysis to understand cancer characteristics and develop personalized treatment plans. In summary, global research on drug resistance in head and neck cancer has progressed, yet significant challenges remain. Future research should focus on innovating more effective treatments to improve patient prognosis.

This paper statistically analyzes international collaborations in head and neck cancer drug resistance research at three levels: country, institution and author. Firstly, China, the United States and Japan lead in head and neck cancer drug resistance research. This is with the number of publications and citation frequency ranking among the top three. Among them, China has an absolute advantage in the number of publications, and the United States has an obvious advantage in the frequency of citations. Secondly, in terms of institutions, China, the United States, and Japan are the main contributors to drug resistance research in head and neck cancer. China Medical University is the leading university in China. The United States plays a key role in international collaborations. M.D. Anderson Cancer Research Center is very significant in the field because it provides key support between the various clusters. Finally, in terms of authors, the Top10 authors, Grandis Jennifer R and Yang Jai-Sing lead the volume of publications, while Osmak Maja, Kim Eun Hye, Roh Jong-Lyel, and Lu Chi-Cheng are noted for their excellent citation performance. Through LLR clustering analysis, the TOP10 authors focused on five major research directions. This demonstrated their profound impact on head and neck cancer drug resistance research. Detailed statistics on the TOP10 authors’ publication volume, academic index, and influence in the field highlight their notable academic and clinical contributions.

Head and neck cancer drug resistance studies revealed research hotspots through keyword co-occurrence analysis. First, VOSViewer counted and visualized keywords. This indicated that treatment method, drug resistance type, and research topic were the three major categories of keywords. Second, LLR and LSI clustering analysis and visualization were used to obtain 16 clusters. These clusters included multidrug resistance in nasopharyngeal carcinoma, the application of RT-PCR in drug resistance research, and the relationship between coenzyme Q-related genes and drug resistance. Finally, the annual keyword frequency heatmap revealed therapeutic focus (Paclitaxel, Immunotherapy, Cisplatin Resistance, Cetuximab), emerging themes (MicroRNA, Metastasis, Ferroptosis, AKT), and motor themes (Cetuximab Resistance, Cisplatin-resistance, Erlotinib, Cell Hypoxia), providing a comprehensive understanding of hotspots and trends in head and neck cancer resistance research. Specifically, emerging areas of cetuximab resistance research in head and neck cancer involve EFNB2 (Chaudhary et al., 2023a), NRG1 (Iida et al., 2022), TRIP13-pY56 (Banerjee et al., 2022), and mathematical resistance prediction models (Cárdenas et al., 2022). Furthermore, resveratrol (Chang et al., 2021), miR-196a (Qin et al., 2019), ferroptosis (Roh et al., 2017; Shin et al., 2018), and photodynamic therapy (Lu et al., 2014) have been investigated specifically as agents for reversing cisplatin resistance in head and neck cancer.

Literature co-citation cluster analysis deepened drug resistance research knowledge structure and focused on head and neck cancer. First, citespace clustered literature keywords and titles to generate nine clusters. It labeled the cluster labels using LSI and LLR algorithms. Second, the hotspots and field evolution of drug resistance research in head and neck cancer were revealed by analyzing the taxon labels and their dependencies. #1 focuses on cancer stem cells, #2-#6 reflect hot topics, while #7 involves Ferroptosis and Cisplatin Resistance, and #8 may involve laryngeal squamous carcinoma drug resistance with the ERK pathway (Kim et al., 2012). Chemotherapeutic agents may increase stem-like cells in cancer tissue (Dorna and Paluszczak, 2023). Therefore, combining conventional chemotherapeutic agents with stemness modulators inhibits cancer cell proliferation and reduces recurrence. By combining a sphingosine kinase one antagonist (FTY720) with paclitaxel, the levels of stemness-associated proteins in oral squamous carcinoma cells can be effectively reduced, which in turn achieves anti-cancer effects (Torres et al., 2024). Finally, the Citespace “Cluster Dependencies” module was used to visualize the dependencies between clusters, simplifying the evolutionary pattern and revealing the research focus trajectory (Li and Li, 2024). This provides a deep insight into the hot trends and evolutionary relationships between taxa in head and neck cancer drug resistance research.

We analyzed journals in the field of drug resistance in head and neck cancer through Citespace’s “Overlay Maps”, revealing the importance of interdisciplinary research. The overlap analysis between cited journals showed that research and citations published in the fields of “Molecular, Biology and Immunology” and “Medicine, Medical and Clinical” were mainly concentrated in journals related to “Molecular, Biology and Genetics”, emphasizing the interconnections between different fields. In addition, we analyzed the core journals using Bradford’s Law and found that Oncotarget, Cancers, and Clinical Cancer Research were the main influential journals in the field of drug resistance in head and neck cancer, with Clinical Cancer Research showing the highest level of overall strength, and Oncotarget demonstrating the highest level of open access strength, and Clinical Cancer Research showing the highest level of open access strength. Oncotarget was also noted for its open access attributes and high impact. The specific attributes of these core journals are critical for obtaining the latest research results on drug resistance in head and neck cancer.

This study has the following strengths.

(1) To the extent of our knowledge, this study is the first bibliometric literature that comprehensively assesses global drug resistance studies in head and neck cancer.

Shortcomings of this study.

(1) Although a single database (WOSCC) was used in this study for bibliometric analysis of head and neck cancer drug resistance studies. However, several studies have shown that this database is considered an excellent resource for bibliometric studies in various disciplines.