Prevalence of antibody drug conjugated-induced nausea and vomiting (ADCINV) in patients with cancer.

Introduction

Nausea and vomiting are among the most distressing adverse effects of systemic therapy, with the ability to impact quality of life and even cause treatment non-adherence [ 1 ]. Nausea and vomiting are conventionally reported in the literature in the overall phase (0 to 120 h), and also three phases, after initiation of treatment: (i) acute phase, occurring in the first 24 h; (ii) delayed phase, occurring between 24 and 120 h; and (iii) long delayed phase, occurring after 120 h [ 2 ].

Chemotherapy-induced nausea and vomiting (CINV) has been extensively researched in the past decades. Different chemotherapies have varying emetogenic profiles; highly emetogenic agents (HEC) include cisplatin and anthracycline/cyclophosphamide combination (emesis risk > 90% of patients), and moderately emetogenic agents (MEC) include doxorubicin and carboplatin (emesis risk 30–90%) [ 3 ]. Despite guidelines recommending emetic prophylaxis, patients still experience CINV. Among patients receiving HEC, one-quarter (24%) experience CINV in the acute phase, half (49%) in the delayed phase and one-third (31%) in the long-delayed phase [ 2 ]. Among patients receiving MEC, less than one-tenth (7%) experience CINV in the acute phase, over one-third (38%) in the delayed phase and one-quarter (24%) in the long-delayed phase [ 2 ]. As a result, decades of research have focused on developing and testing antiemetic agents for prophylactic use [ 4 ].

In recent years, antibody–drug conjugates (ADC) have emerged as an important innovation in systemic cancer treatment [ 5 ]. By combining a monoclonal antibody with a cytotoxic payload, ADCs allow for more targeted delivery of chemotherapy, improving efficacy while potentially limiting systemic toxicity [ 6 ]. The hematologic and metabolic safety profile of ADCs are increasingly well described, but the burden of nausea and vomiting is not well characterized [ 7 ]. To date, there is no robust pooled prevalence estimate of ADC-induced nausea and vomiting (ADCINV).

The aim of this study is to systematically summarize all published primary research on ADC in cancer treatment, to summarize the prevalence of ADCINV.

Methods

This was a systematic review, prospectively registered on PROSPERO (CRD420251156227).

Outcomes

The primary outcomes were the prevalence of ADC-induced nausea, and prevalence of ADC-induced vomiting, among patients treated with ADCs. The secondary outcomes were the prevalence of severe nausea and prevalence of severe vomiting, defined as Grade ≥ 3 on the CTCAE grading tool [ 8 ].

Search strategy

Comprehensive searches were developed with an information specialist (RF), and conducted in Medline, Embase, the Cochrane Central Register of Controlled Trials (CENTRAL) and Web of Science from inception to September 24, 2025. Search strategies combined controlled vocabulary and free-text terms for the concepts of (i) nausea and vomiting, and (ii) antibody drug conjugates approved for the treatment of cancer, including both trade and generic names of individual drugs. ADCs approved for the treatment of cancer were noted from the US National Institutes of Health’s online database, accessed on August 20, 2025 [ 9 ]. Searches were restricted to human studies. Full search strategies are available in the Appendix .

Eligibility criteria

All search results underwent a two-stage screening process. At level 1 (title and abstract) screening, studies were eligible for further screening if they reported on the use of an ADC for the treatment of cancer and provided data on nausea and/or vomiting. At level 2 (full text) screening, studies were included if they were primary research articles; review articles, commentaries and editorials were excluded. When multiple publications reported on the same underlying study, the publication with the largest number of patients was included. Pooled analysis were excluded, if the individual studies were available for inclusion.

Screening was performed in duplicate and independently. One reviewer (DZ) developed a software environment in which search results were processed using the large language model (LLM) of ChatGPT-5, as per the specified eligibility criteria. ChatGPT-5 was provided the abstract (in level 1) and the full text article (in level 2), with a system prompt that asked it to extract specific data fields that were relevant to this study. The LLM returned extracted data in JSON format, and a corresponding reasoning summary and confidence score (low, medium, high). Similar methodology has been previously used, with high degree of sensitivity and specificity on-par to human reviewers [ 10 ]. Independent human screening (RC) was conducted in parallel. Discrepancies between LLM-assisted and human screening decisions were reviewed jointly. The human reviewer examined the model’s reasoning output, and, where necessary, ChatGPT was further queried to clarify its decision logic. Disagreements were resolved through discussion between human and ChatGPT, to achieve consensus. If consensus could not be achieved, a third reviewer (LE) assisted in discussions and achieving consensus.

Data extraction

For each included study, we noted study design, patient demographics (age, sex, cancer type), investigated ADC, use of antiemetic prophylaxis and our pre-specified primary and secondary outcomes. The primary and secondary outcomes were extracted for the overall study period and not according to the antiemetic endpoints of acute, delayed, long-delayed or overall phases, as this was not available in the underlying studies. Data extraction was likewise performed in duplicate and independently (DZ, RC), and disagreements resolved through consensus, with involvement of a third reviewer (LE) as needed.

Quality assessment

Studies were evaluated for quality based on study design. Observational studies were evaluated using the Cochrane Risk of Bias in Non-randomized Studies of Exposures (ROBINS-E) [ 11 ], while interventional studies were evaluated using either the Risk of Bias in Non-randomized Studies of Interventions (ROBINS-I) [ 12 ] or the Cochrane Risk of Bias tool version 2 (RoB 2) [ 13 ]. Quality assessment was visually presented using robvis [ 14 ].

Data synthesis

A descriptive synthesis was conducted of study and patient characteristics. Forest plots of study-specific prevalence estimates were generated. A pooled prevalence and corresponding 95% confidence interval (95%CI) was calculated per outcome, weighted based on study sample size and using a random effects model. Leave-one-out analysis was conducted to determine if there were any studies with significant weight to the pooled prevalence rate. Subgroup analyses were conducted by ADC, if more than one study reported on the outcome. Meta-regression was conducted by the study’s mean age, percentage of participants reported as female, number of patients in study and median follow-up duration of study. Type I error was set at 0.05. All analyses were conducted using Stata18.0 BE.

Results

A total 5714 references were identified through database search. After removal of duplicates, 4669 references underwent level 1 screening. A total of 517 full text articles underwent level 2 screening. Ultimately, 209 [ 15 – 222 ] were included in this review (Fig. 1 ).

Table 1 reports individual study characteristics. Eighty-four (41%) were international trials. Among single-country trials, 62 (30%) articles originated from the USA, 35 (17%) from China, 5 (2%) from Japan and 2 (1%) each from the UK, Italy and Australia. Among the 152 that reported a primary cancer site, the most studied cancer site group setting was lymphoma and myeloma ( n = 55, 36%), followed by breast ( n = 30, 20%), lung ( n = 17, 11%), genitourinary ( n = 17, 11%) and gastrointestinal ( n = 16, 11%). Across all studies, there were a total 15,493 patients. The mean number of patients per trial was 74 (standard deviation 99). The mean percentage of patients identified as female per trial was 53% (standard deviation 27%). Over two-thirds of studies ( n = 145, 69%) enrolled patients who had previously received systemic therapy. One-tenth ( n = 22, 11%) of studies administered ADCs alongside other systemic therapy. Only five studies explicitly reported using antiemetic prophylactic regimens—two reported using 5-HT 3 receptor antagonists, and three reported using steroids. Average follow-up ( n = 51 studies) was a median of 11.4 months.

The majority of studies ( n = 175, 84%) were non-randomized interventional studies. Ten (5%) were randomized controlled trials. The remaining were observational studies. Quality assessment is summarized in Fig. 2 and detailed by study in Appendix Table 2 .

A total of 159 studies reported on the prevalence of nausea. Thirty-nine percent (95%CI, 36–42%) of patients experience any grade of nausea (Fig. 3 (3.1); I 2 = 89%). There is variation by ADCs (Appendix Fig. 5 ). ADCs with higher relative risks of nausea are patritumab deruxtecan (59%, n = 4), trastuzumab deruxtecan (55%, n = 4), sacituzumab govitecan (51%, n = 8) and brentuximabvedotin (47%, n = 19). ADCs with lower relative risks of nausea are disitamab vedotin (28%, n = 4), telisotuzumab vedotin (22%, n = 5), rovalpituzumab tesirine (19%, n = 4) and belantamab mafodotin (6%, n = 3) (Table 2 ). There is some variation by cancer site, but not significant (Appendix Fig. 6 (4.1); p = 0.06). Older patients experience lower rates of nausea (Appendix Fig. 6 (4.2); p < 0.001); each 10-year increase in age is associated with a 12% decrease in nausea rates. Female patients may be at higher risk of ADCINV (Appendix Fig. 6 (4.3); p = 0.072). Also, studies with longer median follow-up reported greater prevalence rates of nausea (Appendix Fig. 6 (4.5); p = 0.035).

Eighty-four studies reported on the prevalence of severe nausea. One percent (95%CI, 0–1%) of patients experience severe nausea (Fig. 3 (3.2); I 2 = 11%). There is no significant difference on any subgroup analyses by ADCs, primary cancer site, age, sex, number of patients in study or follow-up duration of study (Appendix Figs. 7 – 8 ).

Eighty-two studies reported on the prevalence of vomiting. Twenty-six percent (95%CI, 23–29%) of patients experience any grade of vomiting (Fig. 4 (4.1); I 2 = 87%). There is variation by ADCs (Appendix Fig. 9 ). ADCs with higher relative risks of vomiting were seen in cofetuzumab pelidotin (38%) and BL-B01D1 (35%), and lower rates seen in loncastuximab tesirine (19%) and datopotamab deruxtecan (21%). There is variation by primary cancer site, with gynecologic patients experiencing higher rates (Appendix Fig. 10 (8.1), 39%). There is no difference by age, sex, number of patients in enrolled and follow-up duration of study (Appendix Fig. 10 (8.2–8.5)).

Fifty-nine studies reported on the prevalence of severe vomiting. One percent (95%CI, 0–2%) of patients experience severe vomiting (Fig. 4 (4.2); I 2 = 45%). There is no significant difference on any subgroup analyses by ADCs, primary cancer site, age, sex, number of patients in study or follow-up duration of study (Appendices 11 – 12 ).

Discussion

To our knowledge, this is the first pooled prevalence rate of ADCINV. We report that nausea occurs overall in 39% of patients, and vomiting in 26% of patients. The prevalence of severe nausea and vomiting is 1%.

Rates of CINV are reported to be 25–50% for patients receiving highly emetogenic chemotherapy, and up to 40% for patients receiving moderately emetogenic chemotherapy, despite antiemetic prophylaxis, which are comparable to rates of nausea and vomiting seen in our review [ 2 ]. The majority of the trials included in this review do not report use of antiemetic prophylaxis. A small proportion report ADCs used alongside other systemic therapies, but most report ADCs used alone. The reported rate of ADCINV of 26–40% from this study suggests that it is as prevalent issue that should be studied further as a prominent adverse effect and to tailor antiemetic prophylactic regimens towards.

There is much room for research on ADCINV. The data presented herein are not subdivided into the conventional nausea and vomiting time phases of acute, delayed or long delayed. This is expected, as the intent of clinical trials is much broader than just focusing on ADCINV. However, with future research in this field, efforts should be made to classify ADCINV into similar time phases of acute, delayed and long-delayed ADCINV. Also, future work can evaluate the use of rescue antiemetics, a topic that has been sparsely studied in ADCINV thus far.

In contrast with conventional chemotherapy, for which decades of research have defined emetogenic risk and established antiemetic prophylaxis guidelines, no specific guidance exists for ADCINV [ 3 , 4 ]. ADCs have been added to emetic classification alongside chemotherapies, but they may warrant separate studies altogether. It is unknown whether ADCs trigger the same central and gastrointestinal emetic pathway as for CINV, and whether the same prophylactic and rescue options are applicable.

Our results suggest that there may be some difference in ADCINV by drug. A preliminary framework of relative emetogenic potential among ADCs can be proposed based on the current pooled prevalence data. If one were to evaluate the ADCs relative to one another in terms of emetogenicity and classify them as having higher/moderate/lower emetogenic risk relative to the other ADCs, whereby those deemed as having higher or lower emetogenic risk have a prevalence rate greater than 2 standard deviation from the pooled mean, a preliminary emetogenicity risk ladder can be formulated (Table 2 ), where trastuzumab deruxtecan (55%), sacituzumab govitecan (51%) and brentuximab vedotin (47%) are higher emetogenic risk compared to disitimab vedotin (28%), telisotuzumab vedotin (22%) and rovalpituzumab tesirine (19%). While these exploratory categorizations, derived from heterogeneous prophylactic settings, do not yet correspond to established guideline-based risk levels such as HEC/MEC/LEC, they may provide a foundation for future consensus development of ADC-specific emetogenic risk classification. Future work can aim to examine for differences in ADCINV between ADCs, and further evaluate emetogenic risks to establish a framework for future work on antiemetic prophylaxis.

Also, there is no research on predictors for ADCINV, understandably because this phenomenon is only just now being described/highlighted as prevalent in this manuscript. Our results suggest that there may be some patients at higher risk of ADCINV, namely that those who are older experience lower rates of nausea—every 10 years is associated with a 12% decrease in the prevalence of nausea. Female patients may also be at greater risk. As with CINV where patients who are younger, female and have a history of nausea/vomiting are known to be higher risk of CINV [ 224 , 225 ], it can likewise be important to identify patients at higher risk of ADCINV and to provide appropriate prophylactic care for them.

There are strengths and limitations of this review. Strengths include a prospectively registered protocol, comprehensive search strategy across multiple databases, and duplicate independent screening and data extraction using both human reviewer and a large language model–assisted environment. Detailed quality assessment are presented transparently. Limitations include heterogeneity across studies in reporting nausea and vomiting, with inconsistent unstandardized documentation of antiemetic prophylaxis in clinical trials. Also, many studies were deemed to be of high risk of bias as they were conservatively evaluated and there were oftentimes insufficient granular detail to adhere to the Cochrane’s high standard of transparent reporting. For example, concerns were found for Domain 1 and 7 of ROBINS-I, as the statistical plan is oftentimes not reported a priori for observational studies and are not rigorously detailed to report controlling for all possible confounders. However, it is important to mention that this pertains to the study and its design as a whole, with notable issues known for statistical analysis; the concern of bias may or may not be directly attributed to the adverse effect outcome of nausea and vomiting. Finally, the screening criteria required manuscript’s abstracts to explicitly report nausea and/or vomiting to be included in this review, and there are likely other trials that also report nausea and/or vomiting as side effects. Some landmark trials report much higher rates of nausea (70%) and vomiting [ 223 , 226 ]. Unfortunately, it is impractical to include every trial ever conducted in level 2 full text screening to review all reported toxicities, and therefore the best compromise is to include articles whose abstracts report nausea, which has nevertheless generated a large collection of studies. Finally, it is important to note that these nausea/vomiting rates are observed during ADC therapy, but may not necessarily be unilaterally causal; there may be other concomitant therapies, disease burden and supportive medications that may also induce nausea/vomiting. Conservatively, these results should be viewed as hypothesis-generating, whereby ADCINV is identified as a prevalent issue warranting future research.

Our findings have implications for clinicians and researchers. For clinicians, ADCINV and specifically nausea should be anticipated as a common adverse event and discussed with patients considering ADCs. As with chemotherapy, prophylactic antiemetic strategies may improve tolerability, adherence and quality of life. There are no guidelines specifically focused on exclusively ADCINV, with some ADCs suggested into grouping with other chemotherapies based on emetogenic profiles [ 4 ]. For researchers, future research should be conducted to capture nausea and vomiting using standardized phase-specific definitions, and look to evaluate for variability in rates by ADC and individual patient risk factors. With this, preliminary guidelines may be formed to guide future clinical practice.

In conclusion, ADCINV is a prevalent and clinically significant toxicity, akin to CINV. Further research is needed to characterize phase-specific nausea and vomiting, categorize ADCs by emetogenicity, investigate patient related individual risk factors, and ultimately develop optimal management strategies.

Supplementary Information

Below is the link to the electronic supplementary material.

(DOCX 10.4 MB)

Author contribution

RC, FS and LE conceived the project. RC, DZ, SK, AM, CZ, AB, AD, ST and RT were involved in data acquisition. RC was involved in data analysis. All authors were involved in data interpretation and manuscript writing.

Funding

None.

Data availability

Data derived from a source in public domain (systematic review of published articles’ data).

Declarations

Conflict of interest

None.

Ethics declaration

Not applicable.

Footnotes

Florian Scotté and Lawson Eng are co-senior authors.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Data Availability Statement

Data derived from a source in public domain (systematic review of published articles’ data).