Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment; however, their oral toxicity profile is not well elucidated. This review aimed to investigate the prevalence of oral toxicities including xerostomia, mucositis/stomatitis, dysgeusia, dysphagia, oral/oropharyngeal pain, oral infections, angular cheilitis, osteonecrosis, osteomyelitis, and oral mucosal reactions with ICIs. A review protocol was registered with PROSPERO (ID: CRD42023391674). A systematic search of ClinicalTrials.gov was conducted as of April 10, 2022. Studies were selected, assessed, and data extracted using PRISMA guidelines. Oral toxicity data were extracted from study arms using a single immunotherapy drug. Meta-analyses were conducted to summarize prevalence of oral toxicities using random-effects models. Of 750 screened records, 95 trials were included in the meta-analysis with published results. Time between study completion and first publication on ClinicalTrials.gov was 1 to 146 months (mean = 20.3, SD = 18.4). Weighted pooled prevalence was 5% (95% CI: 4–6%) for xerostomia, 3% (95% CI: 3–4%) for mucositis/stomatitis, 3% (95% CI: 2–3%) for dysgeusia, 2% (95% CI: 1–2%) for dysphagia, 3% (95% CI: 2–4%) for oropharyngeal/oral pain, 2% (95% CI: 1–3%) for oral candidiasis, and 2% (95% CI: 0–4%) for angular cheilitis. Subgroup differences based on ICI drugs were minimal. No trials reported lichenoid or pemphigoid mucosal reactions. Meta-analysis results revealed low prevalence of oral toxicities with ICIs; however, data reporting was limited and inconsistent. Limitations of study dataset reveal a significant need for systematic collection of oral morbidity data as well as improved consistency and compliance of reporting results on ClinicalTrials.gov.

Immunotherapy with immune checkpoint inhibitors (ICIs), has revolutionized cancer treatment, yet has also revealed a specific group of negative side effects called immune-related adverse events (irAEs). These side effects occur due to the same mechanism that make these drugs effective, that is, blocking inhibitory mechanisms that suppress the immune system which protect the body from an uncontrolled immune response.[1] Although most irAEs are mild to moderate in severity, therapeutic progress during immunotherapy can be complicated by the manifestation of irAEs. Serious and potentially fatal irAEs have also been reported in the literature. In fact, treatment-related deaths have occurred in up to 2% of patients, and this appears to be associated with the specific ICI being used.[1] irAEs are unique and distinct from side effects associated with traditional cancer therapies, as they tend to have delayed onset and prolonged duration.[1–3]

Gastrointestinal, endocrine, dermatological, cardiovascular, hematologic, musculoskeletal, neurologic, renal, pulmonary, and ocular irAEs have been commonly observed and reported with ICI use.[1–3] In contrast, the oral toxicity profiles of ICIs have not been fully elucidated.[4] Many trials have reported low incidence of oral irAEs with ICIs, although their impact might be undervalued. These oral irAEs can significantly influence hydration and nutrition during cancer therapy. Prevalence of severe oral adverse events (AEs) also remains unknown. Furthermore, clinical reports have revealed new oral mucosal barrier AEs that are not commonly noted with traditional chemotherapy.[4] These include oral lichenoid reactions with or without dermal involvement,[5–8] bullous pemphigoid,[9–11] mucous membrane pemphigoid,[12–15] erythema multiforme,[10–12,15] Stevens-Johnson Syndrome-like, and toxic epidermal necrolysis-like reactions.[16,17] Uncommon and unexpected AEs can compromise delivery of optimal cancer therapy protocols, especially if the oral morbidity requires dose modifications or treatment discontinuation to allow resolution of oral lesions, directly affecting patient survivorship.

Evaluating oral irAEs is important for enhancing patient safety by identifying risk factors, developing early warning systems, and advancing our understanding of complex medical conditions. Similarly, effective management of immune-related oral adverse events (irOAEs) requires recognition and reporting such that evidence-based clinical decisions can be made for management of these toxicities.[1] The aim of this review was to systematically evaluate clinical trial data, and conduct meta-analyses, when possible, to answer the focused review question: What is the prevalence of oral toxicities in adults with neoplastic disease treated with ICIs?

Eligibility Criteria and Search Strategy

A protocol for this systematic review was registered on PROSPERO (ID: CRD42023391674). Preferred Reporting Items for Systematic Review (PRISMA) guidelines were followed for reporting the systematic review and meta-analyses.

The search was planned considering the following PICOS[18] statement:

Participants/population (P): Adults diagnosed with neoplastic disease, irrespective of site of cancer.

Intervention(s), exposure(s) (I): ICIs including pembrolizumab, nivolumab, cemiplimab, ipilimumab, durvalumab, atezolizumab, and avelumab.

Comparator(s)/control (C): None/any

Outcome (O): Oral toxicities including dry mouth (xerostomia), mucositis/stomatitis, dysgeusia, dysphagia, oral/oropharyngeal pain, oral infections, angular cheilitis, osteonecrosis, osteomyelitis, and mucosal reactions including, but not limited to, lichen planus, bullous pemphigoid, mucous membrane pemphigoid, oral variant of erythema multiforme, Stevens-Johnson Syndrome-like, and toxic epidermal necrolysis-like reactions, irrespective of toxicity grading, primary tumor, or drug dosage.

Study Design (S): Clinical trials including Phase 0, 1, 2, and 3 trials, irrespective of randomization or presence of a control group.

A systematic search was carried out to identify all clinical trials registered on ClinicalTrials.gov as of April 10, 2022. We used the advanced search feature of the registry to search trials based on ICI drug names, specifically pembrolizumab, ipilimumab, nivolumab, cemiplimab, atezolizumab, avelumab, and durvalumab, as well as alternative/trade names such as MK-3475, Keytruda, and lambrolizumab for pembrolizumab.

The criteria for study inclusion were (1) clinical studies reporting irOAEs following administration of a single ICI, (2) clinical trials (phase 0, 1, 2 and 3, nonrandomized, and randomized), (3) study results published on ClinicalTrials.gov, and (4) adults (age 18 and older). ICI study arms as second-line treatment with prior chemotherapy were included. Studies were excluded if they only reported study arms with combination therapies, consisted of treatment for non-neoplastic conditions, or if relevant oral AE data were not clearly reported. Combination therapies were defined as ICI drug administered along with systemic chemotherapy, head and neck radiation, stem cell transplantation, or other immunotherapy agents.

Study Selection and Data Extraction

Two authors (A.S., J.S.) independently searched ClinicalTrials.gov and identified records of all included ICI drugs. No ambiguity or disagreements were noted during the screening process. Filters were applied to study status to include only “Completed” trials, and subsequently to study results to include only trials “With Results.” Full reports for trials with published study results were retrieved and assessed for eligibility by both authors.

Predesigned Excel databases were used for data extraction by one author (A.S.). As ClinicalTrials.gov allows bulk download, automated data extraction was done for study characteristics including (1) NCT identifier, (2) study title and study acronym, (3) condition treated (type of cancer), (4) interventions, (5) outcome measures, (6) sample size, (7) sex, (8) age, (9) study phase, (10) study design, (11) funding type, (12) sponsors and collaborators, (13) study location, and (14) relevant study dates, including start date, primary completion date, completion date, first posted, results first posted, and last update posted. Manual data extraction was carried out for oral toxicity data, as the registry does not allow systematic search for irOAEs. Accuracy of data entry was reviewed after extraction of studies for each ICI drug.

AE data on ClinicalTrials.gov do not include any toxicity grading scales. Instead, AEs are categorized as all-cause mortality, serious AEs, and other (not including serious) AEs. Serious AEs are defined as “an adverse event that results in death, is life-threatening, requires inpatient hospitalization or extends a current hospital stay, results in an ongoing or significant incapacity or interferes substantially with normal life functions, or causes a congenital anomaly or birth defect. Medical events that do not result in death, are not life-threatening, or do not require hospitalization may be considered serious AEs if they put the participant in danger or require medical or surgical intervention to prevent one of the results listed above.”[19] For this review, data were extracted for serious and other AEs.

Risk of Bias Assessment

As this review incorporates numerous study designs, including controlled and single-arm phase 0, 1, 2, and 3 studies, risk of bias assessment was primarily limited to selective reporting bias. This bias refers to systematic differences between reported and unreported findings. As AE data are optional on ClinicalTrials.gov, oral toxicity outcomes are likely to be subject to such bias among other more severe or frequent AEs that are more likely to be reported. For a systematic review, selective reporting bias may be one of the most substantial biases affecting the meta-analysis of available data.[20] Selective reporting bias was evaluated for each oral toxicity outcome and denoted dichotomously as low risk if irOAE data were reported for that specific outcome and high risk otherwise.

The level of selective reporting bias was also assessed for each included trial. Studies that reported six or more irOAE outcomes (including zero-events) were considered low risk. Studies that reported four or five outcomes were classified as medium risk, and studies that reported three or fewer outcomes were considered high risk.

Data on selection bias (allocation) for parallel assignment studies, performance bias (blinding of patients, personnel), and detection bias (blinding of outcomes assessment) for randomized controlled trials was retrieved. As this risk of bias assessment criteria could not be universally applied to the included studies, these were not used for study selection or to assess certainty of evidence. Potential funding (sponsorship) bias was characterized by source of funding.

Effect Measures and Synthesis of Results

For each oral toxicity outcome, the effect measure of prevalence/proportion ratios was used in quantitative synthesis of results. Forest plots were used to plot the prevalence of irOAEs with 95% CIs. The inverse variance-weighted average method was used for carrying out the meta-analyses.[21] Because the random-effect and fixed-effect methods give similar results when there is no heterogeneity, relative estimates for the prevalence of irOAEs were summarized using random-effects meta-analysis models, to account for statistical heterogeneity. When heterogeneity is present, a CI around the random-effects summary estimate is wider than a CI around the fixed-effect summary estimate. Heterogeneity was determined using the I2 statistic.[22] Heterogeneity was characterized as low, moderate, and high based on I2 values of 25%, 50%, and 75%, respectively.[22] We included all zero-event data when available to decrease mean square error and obtain more accurate and narrower 95% CIs.[23] Stata/SE version 17 was used to perform the analyses.

We graphed funnel plots to evaluate potential publication bias.[24] A funnel plot is a graphical representation used in meta-analyses to assess the publication bias visually. It plots the effect size of each study on the y-axis against a measure of precision (such as the reciprocal of the standard error) on the x-axis. The plot includes a vertical line that represents the fixed-effects summary estimate. In a symmetrical funnel plot, studies with smaller sample sizes will tend to be located toward the bottom of the plot, and larger studies will be located toward the top. If publication bias is present, the plot will appear asymmetrical, with a gap on one side of the plot indicating that smaller studies with less statistically significant results were not published. The possible causes of asymmetry in a funnel plot include selection biases such as publication bias or selective outcome reporting, poor methodological quality in smaller studies, true heterogeneity among studies, an artifact of the data, or chance.[25] This can lead to a bias in the overall meta-analysis results.

Study Selection

The registry search and screening process as per the PRISMA guidelines is depicted in Figure 1. ClinicalTrials.gov search identified a total of 750 records of completed ICI clinical trials, which were retrieved and assessed for availability of study results. Only 270 trials had study results published on ClinicalTrials.gov, which were reviewed for eligibility. Most of these records (n = 175) were excluded because of combination of ICI with other immunotherapy agents, chemotherapy, radiation therapy, stem cell transplantation, or because of a nononcologic patient pool. A total of 93 trials with a single ICI therapy arm and reported oral toxicities were included for data extraction and meta-analyses (Supplemental Table 1). Among these, two trials included a single ICI therapy arm and reported oral toxicities for both pembrolizumab and ipilimumab.[26,27] These trial arms were considered separately as they involved different participants. As a result, a total of 95 trials were used in the analysis and reported in this article for ease of understanding the results.

Figure 1

PRISMA flow diagram of literature search and screening process (*several trials included more than one oral adverse event data). PRISMA: Preferred Reporting Items for Systematic Review.

Figure 1

PRISMA flow diagram of literature search and screening process (*several trials included more than one oral adverse event data). PRISMA: Preferred Reporting Items for Systematic Review.

Close modal

Study Characteristics

Included ICI trials with oral toxicity data predominantly consisted of programmed death-1 (PD-1) inhibitors, including pembrolizumab (n = 38)[26–63] and nivolumab (n = 14).[64–77] The novel PD-1 inhibitor cemiplimab had no studies with published results. A single study arm for CTLA-4 inhibitor ipilimumab with irOAE data was included for 18 studies.[26,27,78–93] Trials with PD-L1 inhibitors included durvalumab (n = 9),[94–102] atezolizumab (n = 10),[103–112] and avelumab (n = 6).[113–118]Supplemental Table 1 presents detailed study and patient characteristics, including (1) NCT identifier, (2) sample size, (3) condition treated (type of cancer), (4) study phase, (5) study design (intervention model, allocation and binding), and (6) funding type and sources.

A total of 29,620 participants were enrolled in the included studies. The sample size of the individual studies ranged from 10 to 1844 participants. Eighty-four studies included adult participants 18 years and older, six studies included adults 20 years and older,[26,33,36,91] and one study included elderly patients 60 years and older.[56] Four studies included adults, older adults, and children with no raw data available for children for exclusion; these included three studies with participants 12 years and older,[39,76,77] and one study with participants 16 years and older.[82] Three studies[34,53,89] included female participants for investigating breast (n = 1) and ovarian (n = 2) cancer, four studies included male participants only for studying prostate cancer,[48,81,86,118] and 88 studies included both genders.

All studies were interventional, with the primary purpose of treatment of an oncologic pathology (n = 92), basic science research of pharmacodynamic and biologic properties of the ICI agent (n = 2),[65,66] and determination of treatment-related AE (n = 1).[71] No observational studies were included. The oncologic condition under treatment were primarily solid tumors, advanced solid tumors, or metastatic solid tumors (n = 89). Five studies included individuals with lymphomas, leukemia, or myeloma.[32,50,51,56,67] One study included benign human papilloma virus–associated recurrent respiratory/laryngeal papillomatosis.[117]

Study phase and design

Types of included studies were phase 1 (n = 15), phase 2 (n = 46), phase 3 (n = 24), combination phase 1, 2 (n = 9), and combination phase 2, 3 (n = 1) clinical trials (Supplemental Table 1). Of the phase 1 and 2 studies (n = 70), 35 studies included single study groups, 32 studies included two or more study groups with parallel assignment, one study had sequential nonrandomized assignment, one study had a crossover randomized assignment, and one study did not report the intervention model. Of the 32 studies with parallel assignment, 23 studies were randomized and nine were nonrandomized. All phase 3 studies (n = 25) had random allocation of study participants; of these, 24 studies had parallel assignment and one study had sequential assignment (Supplemental Table 1).

Oral toxicity outcomes

Included trials reported irOAE data for dry mouth (n = 55), oral mucositis/stomatitis (n = 64), dysgeusia (n = 43), dysphagia (n = 47), oropharyngeal/oral pain (n = 40), oral candidiasis (n = 16), and angular cheilitis (n = 5). AE data on ClinicalTrials.gov was reported as a proportion of individuals affected by the event and total number at risk. All irOAE data were incorporated in quantitative syntheses, including zero-event data.

Other irOAEs that were reported by a limited number of studies included: osteonecrosis of the jaw (four events, one trial),[28] oral herpes (14 events, one trial),[10] mouth hemorrhage (one event, one trial),[37] periodontal disease (three events, two trials),[33,113] toothache (10 events, six trials),[32,40,41,70,112,113] dental caries (two events, one trial),[36] tooth infection (three events, three trials),[39,69,83] and oral dysesthesia (one event, one trial).[52] Herpes zoster infections were reported by several studies with no specific site of infection. Similarly, osteomyelitis events (n = 8) were reported in eight studies, but site of infection was not clarified. For osteonecrosis and osteomyelitis events, no data regarding previous use of antiresorptive agents were available. Because of the limited number of studies and overall low prevalence, meta-analyses were not conducted for these outcomes. No trials included AE data on lichen planus, bullous pemphigoid, mucous membrane pemphigoid, erythema multiforme, Stevens-Johnson Syndrome-like and toxic epidermal necrolysis-like reactions or Sjogren syndrome-like reactions. No data on therapeutic interventions to resolve oral toxicities were available on ClinicalTrials.gov.

Study duration

The earliest study start date among the retrieved studies (n = 270) was June 1, 2004, for a ipilimumab trial[119] and Aug 1, 2006, for a nivolumab (MDX-1106) trial.[64] Study start date on ClinicalTrials.gov is defined as the actual date on which the first study participant was enrolled.[19] Other ICI drug trials started after 2011. The recent most interventional study with completed and published results had a start date of Mar 4, 2019, and primary completion date of Nov 6, 2019.[120] The latter indicates the date on which the last study participant was examined or received an intervention to collect final data for the primary outcome measure.[19] The average study duration between start and primary completion dates for the 95 included studies was 35 months (SD = 19.3) and ranged from 5 to 92 months. The time between primary study completion and the first publication of results on ClinicalTrials.gov ranged from 1 to 146 months, with an average of 20.3 months (SD = 18.4).

Risk of Bias

Figure 2 presents a summary of the risk of bias assessment. There was a substantial level of selective reporting bias for each oral toxicity outcome. A total of 64 trials reported fewer than three oral toxicity outcomes; these were classified as high risk for reporting bias. Twenty-four trials included four or five oral toxicity outcomes and marked as unclear risk of bias. Only one study reported all seven oral toxicity outcomes[64] and six studies reported six outcomes[28,64,72,90,94,98] that were classified as low risk of reporting bias.

Figure 2

Summary of risk of bias assessment.

Figure 2

Summary of risk of bias assessment.

Close modal

Only eight studies were blinded. Of these, three studies were double-blinded (participant, investigator),[29,76,83] two studies were triple-blinded (participant, investigator and care provider/outcome assessor),[55,78] and three studies were quadruple-blinded (participant, care provider, investigator, outcome assessor).[57,61,86] The remaining 87 studies were open-label with no blinding. Forty-nine randomized trials with parallel assignment were marked as low risk of bias. Trials with parallel assignment and nonrandomized allocation (n = 10) were classified as having high risk of bias. Uncontrolled studies were classified as unclear risk of bias (n = 36).

Funding sources were classified as the National Institutes of Health (NIH), industry, and others including individuals, universities, and organizations (Figure 3). Most of the included studies were industry funded (n = 73). Three studies were funded by NIH, and seven studies were funded by other individuals, organizations, or universities. The remaining studies were funded by a combination of industry and other sources (n = 7); industry and NIH (n = 1); NIH and other sources (n = 2); and NIH, industry, and other sources (n = 2). No studies were funded by other US federal agencies.

Figure 3

Funding sources for included clinical trials (funding source “Others” represents individuals, universities, and organizations). NIH: National Institutes of Health.

Figure 3

Funding sources for included clinical trials (funding source “Others” represents individuals, universities, and organizations). NIH: National Institutes of Health.

Close modal

Summary and Synthesis of Results

Meta-analysis was possible for prevalence of xerostomia, mucositis/stomatitis, dysgeusia, dysphagia, oropharyngeal/oral pain, oral candidiasis, and angular cheilitis. Table 1 provides a summary of results with subgroup pooled prevalence for each ICI drug for each of the outcomes. Figures 4 to 7 and Supplemental Figures 1 to 3 depict forest plots with individual effect estimates, total, and subgroup pooled prevalence by ICI drug, and weights assigned to included studies.

Table 1

Summary of results for meta-analyses of prevalence of oral adverse events in patients administered with ICIs

Summary of results for meta-analyses of prevalence of oral adverse events in patients administered with ICIs
Summary of results for meta-analyses of prevalence of oral adverse events in patients administered with ICIs

Prevalence of xerostomia (dry mouth)

A total of 55 trials revealed prevalence of xerostomia ranging from 0 to 38% (Figure 4). Pooled weighted prevalence of xerostomia was 5% (95% CI: 4–6%). Despite several subgroups with relatively low heterogeneity, the meta-analysis revealed significantly high heterogeneity among all included studies (I2 = 62.09%, p < 0.00001). Subgroup differences between ICI drugs were also statistically significant (χ2 (5, N = 53) = 32.46, p < 0.00001; I2= 84.6%).

Figure 4

Forest plot for meta-analysis of prevalence of xerostomia in patients administered with immune checkpoint inhibitors.

Figure 4

Forest plot for meta-analysis of prevalence of xerostomia in patients administered with immune checkpoint inhibitors.

Close modal

Prevalence of mucositis/stomatitis

Mucositis/stomatitis AEs were reported by the largest number of included trials (n = 64) with prevalence ranging from 0 to 21% (Figure 5). Pooled weighted prevalence of mucositis/stomatitis with ICI drugs was calculated as 3% (95% CI: 3–4%). The overall heterogeneity among all included studies was high (I2 = 79.03%, p < 0.00001), even though subgroup differences were not significant (χ2 = 3.71, p = 0.59; I2 = 0).

Figure 5

Forest plot for meta-analysis of prevalence of mucositis/stomatitis in patients administered with immune checkpoint inhibitors.

Figure 5

Forest plot for meta-analysis of prevalence of mucositis/stomatitis in patients administered with immune checkpoint inhibitors.

Close modal

Prevalence of dysgeusia

Dysgeusia was reported in 43 studies, in all six ICI drug categories, with prevalence ranging from 0 to 38% (Figure 6). Subgroup differences were not statistically significant (χ2 = 6.43, p = 0.27; I2 = 22.2%). Despite that, there was high heterogeneity among included studies (I2 = 59.71%, p < 0.00001) and a random-effects model was used to calculate weighted pooled prevalence of 2% (95% CI: 2–3%).

Figure 6

Forest plot for meta-analysis of prevalence of dysgeusia in patients administered with immune checkpoint inhibitors.

Figure 6

Forest plot for meta-analysis of prevalence of dysgeusia in patients administered with immune checkpoint inhibitors.

Close modal

Prevalence of dysphagia

Figure 7 illustrates a forest plot of the prevalence of dysphagia in 47 included studies. Individual weighted prevalence ranged from 0 to 17% and pooled weighted prevalence was assessed to be as 3% (95% CI: 2–5%). Heterogeneity of included studies was high (I2 = 90.85%, p < 0.000001) and subgroup differences (χ2 [5, N = 45] = 41.17, p < 0.000001; I2= 87.9%) were significant.

Figure 7

Forest plot for meta-analysis of prevalence of dysphagia in patients administered with immune checkpoint inhibitors.

Figure 7

Forest plot for meta-analysis of prevalence of dysphagia in patients administered with immune checkpoint inhibitors.

Close modal

Prevalence of oropharyngeal/oral pain

A total of 40 trials reported oropharyngeal/oral pain including all ICI drugs, with individual study prevalence ranging from 0 to 20% (Supplemental Figure 1). Both subgroup differences (χ2 = 25.22, p = 0.00001; I2 = 80.2%) and overall statistical heterogeneity (I2 = 78.32%, p < 0.00001) were significantly high. The pooled weighted prevalence of oropharyngeal/oral pain with all ICI drugs was calculated as 4% (95% CI: 2–5%).

Prevalence of oral candidiasis

Oral candidiasis was the only oral fungal infection reported in included studies. A total of 16 trials, in four ICI drugs categories, reported individual effect estimates for oral ranging from 0 to 7%, with low variability (Supplemental Figure 2). The overall heterogeneity of included studies was moderate (I2 = 47.29%, p = 0.001) although subgroups were not significantly different (χ2 = 5.24, p = 0.15; I2 = 42.8%). Pooled weighted prevalence was calculated as 2% (95% CI: 1–3%).

Prevalence of angular cheilitis

The fewest ICI drug trials (n = 5) reported angular cheilitis as an oral AE, with individual weighted prevalence ranging from 1 to 7% (Supplemental Figure 3). The pooled weighted prevalence of angular cheilitis was 3% (95% CI: 1–6%. The overall heterogeneity of included studies was low (I2 = 0%, p = 0.46). Subgroup differences (χ2 = 4.03, p = 0.26; I2 = 25.5%) were statistically not significant. Funnel plots to evaluate potential publication bias are presented in Supplemental Figures 4–10.

Prevalence of serious oral AEs

Thirty-two of the 95 included trials reported one or more serious AE. The unweighted prevalence of serious AEs among all AEs was 3.8% (74 of 1957 events). Dysphagia was the most commonly reported serious AE; of the total 45 trials with dysphagia events, 28 trials reported serious AEs. Unweighted prevalence of serious dysphagia AEs was 18.5% (56 of 302 events). Mucositis/stomatitis had an unweighted prevalence of 2% serious AEs (10 of 487 events), reported in a total of seven trials. Six of eight osteomyelitis events were reported as serious AEs resulting in a 75% unweighted prevalence. In addition, one event each of oral/oropharyngeal pain and oral candidiasis were reported as serious AEs with unweighted prevalence of 0.4% and 1%, respectively.

This is the first, most comprehensive systematic assessment of the effect of ICIs on the prevalence of common oral toxicities including xerostomia, mucositis/stomatitis, dysgeusia, dysphagia, oral/oropharyngeal pain, oral candidiasis, angular cheilitis, and osteonecrosis. Most reported oral toxicities were low grade with only 3.8% noted as serious AEs. It is worth noting that this meta-analysis solely examines irOAEs linked to single ICI drug monotherapy. In practical settings, combination regimens with traditional chemotherapy are more prevalent and may exert a more pronounced influence on oral adverse effects, although such data pose challenges in terms of meta-analysis integration. The relatively lower prevalence of serious irOAEs might also stem from the absence of universally accepted grading systems specifically tailored to these toxicities, which underlines the necessity for the development of more sensitive tools that can comprehensively capture such data globally.

Meta-analyses results revealed a comparatively low prevalence of oral AEs with ICIs, when compared with reports of conventional chemotherapy or head and neck radiation therapy–induced oral toxicities. For instance, the prevalence of mucositis can range from 59.4–100% with head and neck cancer patients receiving radiation therapy, 70–86.6% in hematopoietic stem cell transplant patients, and 14.4–81.3% in patients with solid tumors receiving chemotherapy.[121] In comparison, ICI-induced mucositis ranged from 0% to 38% with a pooled weighted prevalence of only 5%. In comparison with ocular, cutaneous, cardiac, pulmonary, and neurotoxicities associated with ICIs, irOAEs seem to exhibit lower levels of both prevalence and severity. Nevertheless, it is important to note that certain irOAEs like mucositis can be dose-limiting and necessitate continual systematic evaluation. The prevalence of irOAEs in this meta-analysis is predominantly influenced by the earlier generations of ICIs, with limited available data on oral toxicities. Interestingly, emerging drugs like avelumab showcase significantly higher occurrence rates of irOAEs based on the limited number of trials with published outcomes. For instance, xerostomia is reported at 38%, whereas oropharyngeal/oral pain stands at 20%. Given the nascent stage of immune therapy, newer drugs are entering the market with uncharted toxicity profiles, underscoring the ongoing need for prospective assessment of all AEs.

Subgroup differences in prevalence of irOAEs between anti-PD-1, anti-PD-L1, and anti-CTLA-4 drugs were minimal, although PD-L1 antagonists have limited data available.

ClinicalTrials.gov was selected for this review as it is among the largest clinical trial repositories. Before selecting ClinicalTrials.gov as the information source for this study, we conducted a scoping search of PubMed and Medline (OVID) relevant to this topic. This scoping search generated 580 de-duplicated citations. Title and abstract screening revealed that a limited number of abstracts reported irOAE data. For instance, 16 abstracts included mucositis and three abstracts included xerostomia as AEs. In comparison, the data in our meta-analysis from ClinicalTrials.gov includes 53 trials with xerostomia and 64 trials with mucositis irOAEs. Furthermore, most selected titles were rejected on full-text review as they corresponded to conference abstracts with no published articles. Finally, on full-text review of 20 relevant abstracts, we realized that other oral AEs are described in tables or texts that are not reported in abstracts. Because of these indexing discrepancies, a systematic analysis of irOAEs was not amenable to conventional systematic review strategies using bibliographic databases.

Although more comprehensive clinical trial registries such as International Clinical Trials Registry Platform (ICTRP) were not included, ClinicalTrials.gov provided an accurate sample of clinical trials being conducted globally in the domain of immunotherapy. We manually searched ICTRP for irOAE data associated with nivolumab and found that more than 80% of ICTRP trials were also registered in ClinicalTrials.gov, as has been noted in other reviews.[122,123] Furthermore, the Clinical Trials Transformation Initiative (CTTI) remodeled ClinicalTrials.gov to become a browsable database of trials. This allowed methodical search of records and expedient extraction of comprehensive structured data elements using targeted filters.

Nevertheless, almost two-thirds of completed trials on ClinicalTrials.gov screened for this review did not include study results, demonstrating low compliance with reporting policies. In addition, our results revealed that there is a substantial lag (mean = 20.3 months, range 1–146 months) between study completion and the first publication of results on ClinicalTrials.gov. Furthermore, AE data on clinicaltrials.gov are optional data elements that may not be reported by the study authors.[124] Consequently, there is a lack of consistency in oral AE data. For instance, only 38 studies reported both xerostomia and mucositis/stomatitis outcomes, including zero-event data. Only four studies reported xerostomia and three studies reported mucositis/stomatitis as AE categories when the numbers of events were zero. This simulates reporting bias encountered in conventional systematic reviews based on database search, where positive results are more likely to be published. Other challenges with trial registry metadata-based analysis included the fact that many trials are not registered on ClinicalTrials.gov. Despite the exhaustiveness of this review, because of the lack of comprehensive reporting and compliance, the results may not represent an unbiased reflection of all ICI research studies. These limitations also reveal a significant need for systematic collection of oral morbidities data as well as improved consistency and compliance of reporting results on ClinicalTrials.gov.

Within limitations of heterogeneity in the methodology, study population, and outcomes of the included studies, the meta-analyses revealed a relatively low prevalence of oral AEs with ICIs, when compared with previous reports of conventional chemotherapy or head and neck radiation therapy–induced oral toxicities. The overall weighted prevalence for ICI-associated oral toxicities ranged from 2% to 5%. Serious oral AEs were noted in only 3.8% of all participants with oral toxicities.

The metadata derived from ClinicalTrials.gov revealed a high proportion of unreported study results, missing data elements on AEs, and a prolonged lag between study completion and first publication of results in the registry. Systematic collection of AE data and improved consistency and compliance of reporting results are needed for accurate analyses of datasets derived from ClinicalTrials.gov.

Supplemental materials are available online with the article.

Source of Support: The salary for Graciela M. Nogueras-Gonzalez is partly supported by the Cancer Center Support Grant (National Cancer Institute Grant P30 CA016672).

Conflict of Interest: None

This study was previously presented at the American Head and Neck Society 2022 annual meeting held during the Combined Otolaryngology Spring Meeting, Apr 28, 2022, in Dallas, TX, USA.

1.
Puzanov
I,
Diab
A,
Abdallah
K,
et al
Managing toxicities associated with immune checkpoint inhibitors: consensus recommendations from the Society for Immunotherapy of Cancer (SITC)
Toxicity Management Working Group.
J Immunother Cancer
.
2017
;
5
:
95
.
2.
Ramos-Casals
M,
Brahmer
JR,
Callahan
MK,
et al
Immune-related adverse events of checkpoint inhibitors
.
Nat Rev Dis Primers
.
2020
;
6
:
38
.
3.
Schonfeld
SJ,
Tucker
MA,
Engels
EA,
et al
Immune-related adverse events after immune checkpoint inhibitors for melanoma among older adults
.
JAMA Netw Open
.
2022
;
5
:
e223461
e223461
.
4.
Klein
BA,
Alves
FA,
de Santana Rodrigues Velho
J,
et al
Oral manifestations of immune-related adverse events in cancer patients treated with immune checkpoint inhibitors
.
Oral Dis
.
2022
;
28
:
9
22
.
5.
Obara
K,
Masuzawa
M,
Amoh
Y.
Oral lichenoid reaction showing multiple ulcers associated with anti-programmed death cell receptor-1 treatment: a report of two cases and published work review
.
J Dermatol
.
2018
;
45
:
587
591
.
6.
Enomoto
Y,
Nakatani
H,
Kondo
S,
et al
Drug-induced oral lichenoid reaction during nivolumab therapy
.
Int J Oral Maxillofac Surg
.
2019
;
48
:
488
491
.
7.
Coleman
E,
Ko
C,
Dai
F,
et al
Inflammatory eruptions associated with immune checkpoint inhibitor therapy: a single-institution retrospective analysis with stratification of reactions by toxicity and implications for management
.
J Am Acad Dermatol
.
2019
;
80
:
990
997
.
8.
Bhattacharyya
I,
Chehal
H,
Migliorati
C.
Severe oral erosive lichenoid reaction to pembrolizumab therapy
.
Oral Surg Oral Med Oral Pathol Oral Radiol
.
2020
;
130
:
e301
e307
.
9.
Sowerby
L,
Dewan
AK,
Granter
S,
et al
Rituximab treatment of nivolumab-induced bullous pemphigoid
.
JAMA Dermatol
.
2017
;
153
:
603
605
.
10.
Siegel
J,
Totonchy
M,
Damsky
W,
et al
Bullous disorders associated with anti-PD-1 and anti-PD-L1 therapy: A retrospective analysis evaluating the clinical and histopathologic features, frequency, and impact on cancer therapy
.
J Am Acad Dermatol
.
2018
;
79
:
1081
1088
.
11.
Naidoo
J,
Schindler
K,
Querfeld
C,
et al
Autoimmune bullous skin disorders with immune checkpoint inhibitors targeting PD-1 and PD-L1
.
Cancer Immunol Res
.
2016
;
4
:
383
389
.
12.
Fassler
M,
Rammlmair
A,
Feldmeyer
L,
et al
Mucous membrane pemphigoid and lichenoid reactions after immune checkpoint inhibitors: common pathomechanisms
.
J Eur Acad Dermatol Venereol
.
2020
;
34
:
e112
e115
.
13.
Haug
V,
Behle
V,
Benoit
S,
et al
Pembrolizumab-associated mucous membrane pemphigoid in a patient with Merkel cell carcinoma
.
Br J Dermatol
.
2018
;
179
:
993
994
.
14.
Zumelzu
C,
Alexandre
M,
Le Roux
C,
et al
Mucous membrane pemphigoid, bullous pemphigoid, and anti-programmed death-1/programmed death-ligand 1: a case report of an elderly woman with mucous membrane pemphigoid developing after pembrolizumab therapy for metastatic melanoma and review of the literature
.
Front Med (Lausanne)
.
2018
;
5
:
268
.
15.
Sibaud
V,
Vigarios
E,
Siegfried
A,
et al
Nivolumab-related mucous membrane pemphigoid
.
Eur J Cancer
.
2019
;
121
:
172
176
.
16.
Hwang
A,
Iskandar
A,
Dasanu
CA.
Stevens-Johnson syndrome manifesting late in the course of pembrolizumab therapy
.
J Oncol Pharm Pract
.
2019
;
25
:
1520
1522
.
17.
Cai
ZR,
Lecours
J,
Adam
JP,
et al
Toxic epidermal necrolysis associated with pembrolizumab
.
J Oncol Pharm Pract
.
2020
;
26
:
1259
1265
.
18.
Stone
PW.
Popping the (PICO) question in research and evidence-based practice
.
Appl Nurs Res
.
2002
;
15
:
197
198
.
19.
ClinicalTrials.gov protocol registration data element definitions for interventional and observational studies
.
20.
Chan
AW,
Altman
DG.
Identifying outcome reporting bias in randomised trials on PubMed: review of publications and survey of authors
.
BMJ
.
2005
;
330
:
753
.
21.
Greenland
S,
O’Rourke
K.
On the bias produced by quality scores in meta-analysis, and a hierarchical view of proposed solutions
.
Biostatistics
.
2001
;
2
:
463
471
.
22.
Harris
R,
Bradburn
M,
Deeks
J,
et al
metan: fixed- and random-effects meta-analysis
.
Stata J
.
2008
;
8
:
3
28
.
23.
Cheng
J,
Pullenayegum
E,
Marshall
JK,
et al
Impact of including or excluding both-armed zero-event studies on using standard meta-analysis methods for rare event outcome: a simulation study
.
BMJ Open
.
2016
;
6
:
e010983
.
24.
Sterne
JA,
Egger
M.
Funnel plots for detecting bias in meta-analysis: guidelines on choice of axis
.
J Clin Epidemiol
.
2001
;
54
:
1046
1055
.
25.
Egger
M,
Davey Smith
G,
Schneider
M,
Minder
C.
Bias in meta-analysis detected by a simple, graphical test
.
BMJ
.
1997
;
315
:
629
634
.
26.
Study of pembrolizumab (MK-3475) monotherapy in advanced solid tumors and pembrolizumab combination therapy in advanced non-small cell lung cancer/extensive-disease small cell lung cancer (MK-3475–011/KEYNOTE-011)
.
ClinicalTrials.gov identifier: NCT01840579
.
27.
Study to evaluate the safety and efficacy of two different dosing schedules of pembrolizumab (MK-3475) compared to ipilimumab in participants with advanced melanoma (MK-3475–006/KEYNOTE-006)
.
ClinicalTrials.gov identifier: NCT01866319
.
28.
Study of pembrolizumab (MK-3475) in participants with progressive locally advanced or metastatic carcinoma, melanoma, or non-small cell lung carcinoma (P07990/MK-3475–001/KEYNOTE-001)
.
ClinicalTrials.gov identifier: NCT01295827
.
29.
Study of pembrolizumab (MK-3475) versus chemotherapy in participants with advanced melanoma (MK-3475–002/P08719/KEYNOTE-002)
.
ClinicalTrials.gov identifier: NCT01704287
.
30.
Study of pembrolizumab (MK-3475) in participants with advanced solid tumors (MK-3475–012/KEYNOTE-012)
.
ClinicalTrials.gov identifier: NCT01848834
.
31.
Study of two doses of pembrolizumab (MK-3475) versus docetaxel in previously treated participants with non-small cell lung cancer (MK-3475–010/KEYNOTE-010)
.
ClinicalTrials.gov identifier: NCT01905657
.
32.
A trial of pembrolizumab (MK-3475) in participants with blood cancers (MK-3475–013/KEYNOTE-013)
.
ClinicalTrials.gov identifier: NCT01953692
.
33.
Study of pembrolizumab (MK-3475) in participants with advanced non-small cell lung cancer (MK-3475–025/KEYNOTE-025)
.
ClinicalTrials.gov identifier: NCT02007070
.
34.
Anti-PD-1 monoclonal antibody in advanced, trastuzumab-resistant, HER2-positive breast cancer
.
ClinicalTrials.gov identifier: NCT02129556
.
35.
Study of pembrolizumab (MK-3475) compared to platinum-based chemotherapies in participants with metastatic non-small cell lung cancer (MK-3475–024/KEYNOTE-024)
.
ClinicalTrials.gov identifier: NCT02142738
.
36.
Study of pembrolizumab (MK-3475) in participants with advanced melanoma (MK-3475–041/KEYNOTE-041)
.
ClinicalTrials.gov identifier: NCT02180061
.
37.
Study of MK-3475 (pembrolizumab) in recurrent or metastatic head and neck squamous cell carcinoma after treatment with platinum-based and cetuximab therapy (MK-3475–055/KEYNOTE-055)
.
ClinicalTrials.gov identifier: NCT02255097
.
38.
A Study of pembrolizumab (MK-3475) versus paclitaxel, docetaxel, or vinflunine for participants with advanced urothelial cancer (MK-3475–045/KEYNOTE-045)
.
ClinicalTrials.gov identifier: NCT02256436
.
39.
SARC028: A phase II study of the anti-PD1 antibody pembrolizumab (MK-3475) in patients with advanced sarcomas
.
ClinicalTrials.gov identifier: NCT02301039
.
40.
Neoadjuvant pembrolizumab for unresectable stage III and unresectable stage IV melanoma
.
ClinicalTrials.gov identifier: NCT02306850
.
41.
Phase 2 multi-center study of anti-PD-1 during lymphopenic state after HDT/ASCT for multiple myeloma
.
ClinicalTrials.gov identifier: NCT02331368
.
42.
Pembrolizumab +/− bevacizumab for recurrent GBM
.
ClinicalTrials.gov identifier: NCT02337491
.
43.
Study of the combination of ACP-196 and pembrolizumab in subjects with platinum resistant urothelial bladder cancer
.
ClinicalTrials.gov identifier: NCT02351739
.
44.
A study of pembrolizumab (MK-3475) versus paclitaxel for participants with advanced gastric/gastroesophageal junction adenocarcinoma that progressed after therapy with platinum and fluoropyrimidine (MK-3475–061/KEYNOTE-061)
.
ClinicalTrials.gov identifier: NCT02370498
.
45.
Study of pembrolizumab (MK-3475) monotherapy for metastatic triple-negative breast cancer (MK-3475–086/KEYNOTE-086)
.
ClinicalTrials.gov identifier: NCT02447003
.
46.
Pembrolizumab alone and in combination with acalabrutinib (ACP-196) in subjects with advanced non-small cell lung cancer
.
ClinicalTrials.gov identifier: NCT02448303
.
47.
Study of the combination of acalabrutinib (ACP-196) and pembrolizumab in advanced head and neck squamous cell carcinoma
.
ClinicalTrials.gov identifier: NCT02454179
.
48.
Pembrolizumab and cryosurgery in treating patients with newly diagnosed, oligo-metastatic prostate cancer
.
ClinicalTrials.gov identifier: NCT02489357
.
49.
Study of single agent pembrolizumab (MK-3475) versus single agent chemotherapy for metastatic triple negative breast cancer (MK-3475–119/KEYNOTE-119)
.
ClinicalTrials.gov identifier: NCT02555657
.
50.
Study of pembrolizumab (MK-3475) in participants with relapsed or refractory primary mediastinal large B-cell lymphoma or relapsed or refractory Richter syndrome (MK-3475–170/KEYNOTE-170)
.
ClinicalTrials.gov identifier: NCT02576990
.
51.
Pembrolizumab in patients failing to respond to or relapsing after CAR T cell therapy for relapsed or refractory lymphomas
.
ClinicalTrials.gov identifier: NCT02650999
.
52.
Pembrolizumab (Keytruda) in advanced hepatocellular carcinoma
.
ClinicalTrials.gov identifier: NCT02658019
.
53.
Efficacy and safety study of pembrolizumab (MK-3475) in participants with advanced recurrent ovarian cancer (MK-3475–100/KEYNOTE-100)
.
ClinicalTrials.gov identifier: NCT02674061
.
54.
Pembrolizumab with or without vismodegib in treating metastatic or unresectable basal cell skin cancer
.
ClinicalTrials.gov identifier: NCT02690948
.
55.
Study of pembrolizumab (MK-3475) vs. best supportive care in participants with previously systemically treated advanced hepatocellular carcinoma (MK-3475–240/KEYNOTE-240)
.
ClinicalTrials.gov identifier: NCT02702401.
56.
A phase II study of pembrolizumab as post-remission treatment of patients ≥ 60 with AML
.
ClinicalTrials.gov identifier: NCT02708641.
57.
A phase 3 study of pembrolizumab + epacadostat or placebo in subjects with unresectable or metastatic melanoma (Keynote-252 ECHO-301)
.
ClinicalTrials.gov identifier: NCT02752074.
58.
A study of pembrolizumab in patients with neuroendocrine tumors
.
ClinicalTrials.gov identifier: NCT02939651
.
59.
Pembrolizumab in recurrent or metastatic medullary thyroid cancer
.
ClinicalTrials.gov identifier: NCT03072160
.
60.
A study of cobimetinib plus atezolizumab versus pembrolizumab in participants with previously untreated advanced BRAFv600 wild-type melanoma
.
ClinicalTrials.gov identifier: NCT03273153
.
61.
Pembrolizumab plus epacadostat vs pembrolizumab plus placebo in metastatic non-small cell lung cancer (KEYNOTE-654–05/ECHO-305–05)
.
ClinicalTrials.gov identifier: NCT03322540
.
62.
Pembrolizumab in combination with epacadostat or placebo in cisplatin-ineligible urothelial carcinoma (KEYNOTE-672/ECHO-307)
.
ClinicalTrials.gov identifier: NCT03361865
.
63.
Pembrolizumab + epacadostat vs pembrolizumab + placebo in recurrent or progressive metastatic urothelial carcinoma
.
ClinicalTrials.gov identifier: NCT03374488
.
64.
A study of MDX-1106 in patients with selected refractory or relapsed malignancies
.
ClinicalTrials.gov identifier: NCT00441337.
65.
Phase I biomarker study (BMS-936558)
.
ClinicalTrials.gov identifier: NCT01358721
.
66.
PH 1 biomarker study of nivolumab and ipilimumab and nivolumab in combination with ipilimumab in advanced melanoma
.
ClinicalTrials.gov identifier: NCT01621490
.
67.
Study of nivolumab in patients with relapsed or refractory diffuse large B-cell lymphoma (DLBCL) that have either failed or are not eligible for autologous stem cell transplant (CheckMate 139)
.
ClinicalTrials.gov identifier: NCT02038933
.
68.
A phase 1/2, open-label study to evaluate the safety and antitumor activity of MEDI0680 (AMP-514) in combination with durvalumab versus nivolumab monotherapy in participants with select advanced malignancies
.
ClinicalTrials.gov identifier: NCT02118337
.
69.
A single-arm, open-label, multicenter clinical trial with nivolumab (BMS-936558) for subjects with histologically confirmed stage III (unresectable) or stage IV melanoma progressing post prior treatment containing an anti-CTLA4 monoclonal antibody (CheckMate 172)
.
ClinicalTrials.gov identifier: NCT02156804
.
70.
Nivolumab in treating patients with recurrent and/or metastatic nasopharyngeal cancer
.
ClinicalTrials.gov identifier: NCT02339558
.
71.
An open-label, multicenter clinical trial with nivolumab (BMS-936558) monotherapy in subjects with advanced or metastatic squamous cell (Sq) non-small cell lung cancer (NSCLC) who have received at least one prior systemic regimen for the treatment of stage IIIb/IV SqNSCLC
.
ClinicalTrials.gov identifier: NCT02409368
.
72.
A study of nivolumab in advanced non-small cell lung cancer (NSCLC)
.
ClinicalTrials.gov identifier: NCT02574078
.
73.
Nivolumab and yttrium Y 90 glass microspheres in treating patients with advanced liver cancer
.
ClinicalTrials.gov identifier: NCT02837029
.
74.
A Study of nivolumab in relapsed/refractory primary central nervous system lymphoma (PCNSL) and relapsed/refractory primary testicular lymphoma (PTL)
.
ClinicalTrials.gov identifier: NCT02857426
.
75.
Study to evaluate the efficacy and safety of andecaliximab combined with nivolumab versus nivolumab alone in adults with unresectable or recurrent gastric or gastroesophageal junction adenocarcinoma
.
ClinicalTrials.gov identifier: NCT02864381
.
76.
An investigational immuno-therapy study of nivolumab combined with ipilimumab compared to nivolumab by itself after complete surgical removal of stage IIIb/c/d or stage IV melanoma
.
ClinicalTrials.gov identifier: NCT03068455
.
77.
An investigational immuno-therapy study of BMS-986205 combined with nivolumab, compared to nivolumab by itself, in patients with advanced melanoma
.
ClinicalTrials.gov identifier: NCT03329846
.
78.
MDX-010 antibody, MDX-1379 melanoma vaccine, or MDX-010/MDX-1379 combination treatment for patients with unresectable or metastatic melanoma
.
ClinicalTrials.gov identifier: NCT00094653
.
79.
MDX-010 in treating patients with stage IV pancreatic cancer that cannot be removed by surgery
.
ClinicalTrials.gov identifier: NCT00112580
.
80.
A companion study for patients enrolled in prior/parent ipilimumab studies
.
ClinicalTrials.gov identifier: NCT00162123
.
81.
Study of MDX-010 in patients with metastatic hormone-refractory prostate cancer
.
ClinicalTrials.gov identifier: NCT00323882
.
82.
Evaluation of tumor response to ipilimumab in the treatment of melanoma with brain metastases
.
ClinicalTrials.gov identifier: NCT00623766
.
83.
Efficacy study of ipilimumab versus placebo to prevent recurrence after complete resection of high risk stage III melanoma
.
ClinicalTrials.gov identifier: NCT00636168
.
84.
Drug-drug interaction - 3 arm - carboplatin/paclitaxel, dacarbazine
.
ClinicalTrials.gov identifier: NCT00796991
.
85.
Comparison of ipilimumab manufactured by 2 different processes in participants with advanced melanoma
.
ClinicalTrials.gov identifier: NCT00920907
.
86.
Phase 3 study of immunotherapy to treat advanced prostate cancer
.
ClinicalTrials.gov identifier: NCT01057810
.
87.
Study of nivolumab (BMS-936558) in combination with gemcitabine/cisplatin, pemetrexed/cisplatin, carboplatin/paclitaxel, bevacizumab maintenance, erlotinib, ipilimumab or as monotherapy in subjects with stage IIIB/IV non-small cell lung cancer (NSCLC) (CheckMate 012)
.
ClinicalTrials.gov identifier: NCT01454102
.
88.
An efficacy study in gastric and gastroesophageal junction cancer comparing ipilimumab versus standard of care immediately following first line chemotherapy
.
ClinicalTrials.gov identifier: NCT01585987
.
89.
Phase II study of ipilimumab monotherapy in recurrent platinum-sensitive ovarian cancer
.
ClinicalTrials.gov identifier: NCT01611558
.
90.
Evaluation of circulating T cells and tumor infiltrating lymphocytes (TILs) during after pre-surgery chemotherapy in non-small cell lung cancer (NSCLC)
.
ClinicalTrials.gov identifier: NCT01820754
.
91.
Phase 2 study of ipilimumab in Japanese advanced melanoma patients
.
ClinicalTrials.gov identifier: NCT01990859
.
92.
Nab-paclitaxel and bevacizumab or ipilimumab as first-line therapy in treating patients with stage IV melanoma that cannot be removed by surgery
.
ClinicalTrials.gov identifier: NCT02158520
.
93.
Ipilimumab vs ipilimumab plus nivolumab in patients with stage III-IV melanoma who have progressed or relapsed on PD-1 inhibitor therapy
.
ClinicalTrials.gov identifier: NCT02731729
.
94.
A phase 1/2 study to evaluate MEDI4736
.
ClinicalTrials.gov identifier: NCT01693562
.
95.
Phase II study of MEDI4736 monotherapy in treatment of recurrent or metastatic squamous cell carcinoma of the head and neck
.
ClinicalTrials.gov identifier: NCT02207530
.
96.
Evaluate the efficacy of MEDI4736 in immunological subsets of advanced colorectal cancer
.
ClinicalTrials.gov identifier: NCT02227667
.
97.
Phase II study of MEDI4736, tremelimumab, and MEDI4736 in combination w/tremelimumab squamous cell carcinoma of the head and neck
.
ClinicalTrials.gov identifier: NCT02319044
.
98.
Phase 2 study of durvalumab (MEDI4736) in patients with glioblastoma
.
ClinicalTrials.gov identifier: NCT02336165
.
99.
A phase 1b/2 study of MEDI4736 with tremelimumab, MEDI4736 or tremelimumab monotherapy in gastric or GEJ adenocarcinoma
.
ClinicalTrials.gov identifier: NCT02340975
.
100.
Study of MEDI4736 monotherapy and in combination with tremelimumab versus standard of care therapy in patients with head and neck cancer
.
ClinicalTrials.gov identifier: NCT02369874
.
101.
Phase III open label study of MEDI 4736 with/without tremelimumab versus standard of care (SOC) in recurrent/metastatic head and neck cancer
.
ClinicalTrials.gov identifier: NCT02551159
.
102.
Phase II study of MEDI4736 monotherapy or in combinations with tremelimumab in metastatic pancreatic ductal carcinoma
.
ClinicalTrials.gov identifier: NCT02558894
.
103.
A study of atezolizumab in participants with programmed death-ligand 1 (PD-L1) positive locally advanced or metastatic non-small cell lung cancer (NSCLC) FIR
.
ClinicalTrials.gov identifier: NCT01846416
.
104.
A randomized phase 2 study of atezolizumab (an engineered anti-PDL1 antibody) compared with docetaxel in participants with locally advanced or metastatic non-small cell lung cancer who have failed platinum therapy - “POPLAR.”
ClinicalTrials.gov identifier: NCT01903993
.
105.
A Study of atezolizumab (an engineered anti-programmed death-ligand 1 PD-L1 antibody) as monotherapy or in combination with bevacizumab (Avastin®) compared to sunitinib (Sutent®) in participants with untreated advanced renal cell carcinoma
.
ClinicalTrials.gov identifier: NCT01984242
.
106.
A study of atezolizumab compared with docetaxel in participants with locally advanced or metastatic non-small cell lung cancer who have failed platinum-containing therapy
.
ClinicalTrials.gov identifier: NCT02008227
.
107.
A study of atezolizumab in participants with programmed death-ligand 1 (PD-L1) positive locally advanced or metastatic non-small cell lung cancer
.
ClinicalTrials.gov identifier: NCT02031458
.
108.
A study of atezolizumab compared with chemotherapy in participants with locally advanced or metastatic urothelial bladder cancer IMvigor211
.
ClinicalTrials.gov identifier: NCT02302807
.
109.
A study of atezolizumab in advanced solid tumors
.
ClinicalTrials.gov identifier: NCT02458638
.
110.
A study to investigate efficacy and safety of cobimetinib plus atezolizumab and atezolizumab monotherapy versus regorafenib in participants with metastatic colorectal adenocarcinoma (COTEZO IMblaze370)
.
ClinicalTrials.gov identifier: NCT02788279
.
111.
A study of atezolizumab as first-line monotherapy for advanced or metastatic non-small cell lung cancer
.
ClinicalTrials.gov identifier: NCT02848651
.
112.
A study of daratumumab in combination with atezolizumab compared with atezolizumab alone in participants with previously treated advanced or metastatic non-small cell lung cancer
.
ClinicalTrials.gov identifier: NCT03023423
.
113.
Avelumab in metastatic or locally advanced solid tumors (JAVELIN Solid Tumor JPN)
.
ClinicalTrials.gov identifier: NCT01943461
.
114.
Avelumab in non-small cell lung cancer (JAVELIN Lung 200)
.
ClinicalTrials.gov identifier: NCT02395172
.
115.
Avelumab in first-line maintenance gastric cancer (JAVELIN Gastric 100)
.
ClinicalTrials.gov identifier: NCT02625610
.
116.
Avelumab in third-line gastric cancer (JAVELIN Gastric 300)
.
ClinicalTrials.gov identifier: NCT02625623
.
117.
Avelumab for people with recurrent respiratory papillomatosis
.
ClinicalTrials.gov identifier: NCT02859454
.
118.
PD-L1 inhibition as checkpoint immunotherapy for neuroendocrine phenotype prostate cancer
.
ClinicalTrials.gov identifier: NCT03179410
.
119.
Hormone therapy and ipilimumab in treating patients with advanced prostate cancer
.
ClinicalTrials.gov identifier: NCT00170157
.
120.
Phase Ib/II study of carboplatin + M6620 + avelumab in PARPi-resistant ovarian cancer
.
ClinicalTrials.gov identifier: NCT03704467
.
121.
Berger
K,
Schopohl
D,
Bollig
A,
et al
Burden of oral mucositis: a systematic review and implications for future research
.
Oncol Res Treat
.
2018
;
41
:
399
405
.
122.
Goswami
ND,
Pfeiffer
CD,
Horton
JR,
et al
The state of infectious diseases clinical trials: a systematic review of ClinicalTrials.gov
.
PLoS One
.
2013
;
8
:
e77086
.
123.
Sibanda
M,
Summers
R,
Meyer
JC.
A comparison of five international clinical trial registers with the South African register for access to information and usability
.
Pan Afr Med J
.
2018
;
29
:
224
.
124.
Tse
T,
Fain
KM,
Zarin
DA.
How to avoid common problems when using ClinicalTrials.gov in research: 10 issues to consider
.
BMJ
.
2018
;
361
:
k1452
.
This work is published under a CC-BY-NC-ND 4.0 International License.

Supplementary data