Abstract
Previous research shows that the benefits of phase-I oncology trials increased from 5 to 18% between 2000 and 2019 globally. However, the risk–benefit profile of phase-I trials in China is unclear. This study aims to analyze the risk–benefit profile of phase-I oncology trials in China and explore their correlation. We included adult phase-I oncology trials registered on the Chinese Clinical Trial Registry and Information Disclosure Platform between September 2013 and December 2021. Data on response rates and grade-3/4 adverse events were retrieved from PubMed, Google Scholar, and CNKI to assess their correlation. A total of 189 trials with 9591 patients were analyzed. The median response rate was 25.4% (IQR, 9.4–41.4%), and the overall incidence of grade-3/4 adverse events was 29.3% (IQR, 15.0–43.8%). No significant trends were observed over time. Subgroup analysis showed higher response rates in lymphoma (45.8%), cell therapies (80.0%), and biomarker trials (38.0%). Higher adverse event rates were seen in breast cancer (55.0%), chemical drugs (33.3%), cytotoxic drugs (73.3%), and combination therapies (35.7%). A weak correlation was found between response rates and grade-3/4 adverse events (ρ = 0.217; p = 0.003), with a moderate correlation in immunotherapy (ρ = 0.417; p < 0.001). This is the first assessment of early efficacy and safety signals of phase-I oncology trials in China. No significant temporal trends were identified. However, the correlation in immunotherapy suggests that higher benefits may be accompanied by greater risks.
Supplementary Information
The online version contains supplementary material available at 10.1007/s10637-025-01560-5.
Keywords: Phase-I clinical trials, Benefit and risk, New drugs, Oncology, China
Introduction
Phase-I clinical trials are fundamental to drug development as the outcome of risk–benefit assessments conducted during phase-I trials guides the decision of whether an investigational new drug could proceed to later stages [1]. In clinical practice, cancer patients frequently have limited treatment options other than first-line therapies, who could benefit from participating in trials of investigational new drugs [2–4]. The American Society of Clinical Oncology (ASCO) suggests that while drugs undergoing phase-I clinical trials entail great risks, they also have the potential to provide clinical benefits that other treatment options failed to provide [5]. Thus, a comprehensive assessment of a drug’s risk–benefit profile during phase-I trials cannot only inform decisions on drug development and regulation but also facilitate the informed decision of patients about trial participation [6, 7].
International research has documented a notable increase in the objective response rate (ORR) of phase-I oncology clinical trials over recent decades. The number increased from 5% during 1991–2002 [8], to 9.6% during 2000–2005, and to 18% during 2013–2019. Mortality rates remained relatively stable despite significant surges in ORR over similar periods [9]. The incidence of grade-4 treatment-related adverse events was 14.3% during 1991–2001, while the incidence of grade-3/4 treatment-related adverse events declined to 13.2% during 2015–2018 [10]. This downward trend suggests a gradual enhancement in the safety profile of these trials, indicating that the efficacy and safety of phase-I clinical trials for oncology drugs are improving, thereby elucidating their potential therapeutic benefits.
In China, the landscape of phase-I clinical trials has substantially shifted as the annual number of such trials increased from fewer than 30 in 2009 to over 300 in 2020 [11]. Simultaneously, the approval rate of anti-cancer drugs has markedly increased, with the number of approved agents rising from 57 during 2011–2013 to 161 during 2018–2021 [12]. However, the risk–benefit profile of phase-I oncology clinical trials conducted in China remains inadequately characterized. We aimed to evaluate the risk–benefit profile of phase-I clinical trials for adult oncology drugs registered in China and investigate correlations between these parameters to better inform patients and healthcare providers likely to engage in these trials.
Methods
Data sources
We collected data on clinical trials registered in the Chinese Clinical Trial Registry and Information Disclosure Platform (Chinadrugtrials.org.cn) as of December 31, 2021. This platform, established by the former China Food and Drug Administration (CFDA, now the National Medical Products Administration) on September 6, 2013, mandates that all investigational new drugs authorized by the CFDA to register and disclose their information, including the Clinical Trial Registration (CTR) number, drug name, drug type, indication, trial design, and other study identifiers (Name/Acronym).
Sample selection
We identified adult phase-I clinical trials of anticancer therapeutic drugs registered between September 6, 2013 and December 31, 2021. Non-phase-I trials, including phase-I/II trials, post-marketing studies, pharmacokinetic trials, supportive care trials (e.g., pain management and granulocyte colony-stimulating factor), bioequivalence studies, trials of traditional Chinese medicines, and studies involving pediatric participants were excluded.
Identification of publication
Since the Chinese Clinical Trial Registry and Information Disclosure Platform contains only basic information on clinical trials at the time of registration and does not require the disclosure of trial results, we conducted searches in external databases to identify published clinical trial results. Given that phase-I trial results are sometimes disseminated in the form of conference abstracts, we also included a search for conference abstracts as a supplementary source of data.
We searched PubMed for published results and Google Scholar for conference abstracts, using CTR, NCT, and ChiCTR numbers. Additionally, we searched the China National Knowledge Infrastructure (CNKI) for results published in Chinese, using keywords such as drug name, indication, and trial design. The cutoff date for retrieving clinical trial results was December 31, 2023.
To identify the NCT number, we searched the study title or acronym in clinicaltrials.gov, the US National Library of Medicine database of clinical trials. For the ChiCTR number, we utilized keywords including drug name, indication, trial phase, trial name, and study design in the Chinese Clinical Trial Registry (chictr.org.cn) which is established by West China Hospital, Sichuan University.
Data extraction
Data extracted from Chinadrugtrials.org.cn included drug name, drug type, indication, registration date, and data pertaining to trial design, such as the inclusion of patients’ performance score (PS) scores. Additionally, we extracted indicators such as response rate (RR) and incidence of adverse events from the latest publications and conference abstracts.
Outcome measure
The outcomes of this study measured the benefits of phase-I trials, specifically RR and disease control rate (DCR) [8, 13, 14]. Established efficacy endpoint measures included the Response Evaluation Criteria in Solid Tumors (RECIST) for solid tumors, while various researcher-specific guidelines, such as the 2014 Lugano Criteria for lymphomas and International Workshop Criteria, were used for hematological malignancies.
Risk was assessed by the incidence of adverse events, specifically the incidence of grade-3/4 adverse events, overall adverse event incidence, and treatment-related deaths [9, 10, 15]. We extracted data for these three indicators, which are commonly evaluated using the Common Terminology Criteria for Adverse Events (CTCAE) developed by the National Cancer Institute (NCI). The version of CTCAE used depends on the protocol of the clinical trial.
Data analysis
Descriptive statistics were employed to characterize the trials, summarizing RR, DCR, and incidence of grade-3/4 adverse events at both the trial level and median [IQR]. Due to the infrequent occurrence of treatment-related deaths, the indicator was aggregated as total counts and proportions within each trial subgroup. Furthermore, the non-parametric Kruskal–Wallis test and Wilcoxon test were computed to assess differences in probability distributions between groups, given the non-normality of the data (Supplementary e-Fig. 1and e-Fig. 2). Spearman correlation analysis was conducted to explore the relationship between RR and the incidence of grade-3/4 adverse events. All statistical analyses were performed using SAS 9.4 (level 1M7), with a two-tailed p-value of less than 0.05 deemed statistically significant.
Results
Characteristics
We identified 15,499 clinical trials registered on Chinadrugtrials.org.cn between September 6, 2013 and December 31, 2021, of which 1071 met our inclusion criteria. Ultimately, 189 trials (encompassing 9591 patients) with published results or conference abstracts reporting both the RR and the incidence of grade-3/r 4 adverse events were included in the analysis (Fig. 1).
Fig. 1.
Flowchart for phase-I clinical trial selection
Among these trials, nearly half (80 trials; 42.3%) focused on solid tumors, followed by lung cancer (24 trials; 12.7%) and lymphoma (17 trials; 9.0%). The majority of trials evaluated targeted therapies (109 trials; 56.1%) and monotherapies (141 trials; 74.6%). More than half of the trials (117 trials; 61.9%) did not require biomarker testing. Furthermore, most trials enrolled patients with a PS of 0–1 (160 trials; 84.7%) (Table 1).
Table 1.
Characteristics of trials and univariate analysis of clinical benefit and risk
| Variate | No. trials (%) | No. patients enrolled in RR assessment (%) | Median RR (%; IQR) | P value | No. patients enrolled in 3/4AER assessment (%) | Median 3/4AER (%; IQR) | P value | |||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Total | 189 | (100) | 8404 | (100) | 25.4 | (9.4–41.4) | 9439 | (100) | 29.3 | (15.0–43.8) | ||
| Trial registration date | ||||||||||||
| 2013 | 15 | (7.9) | 532 | (6.3) | 11.1 | (0.0–45.8) | 0.392 | 539 | (5.7) | 25.0 | (15.0–35.7) | 0.453 |
| 2014 | 5 | (2.6) | 201 | (2.4) | 30.4 | (19.2–31.3) | 213 | (2.3) | 21.9 | (0.0–26.8) | ||
| 2015 | 7 | (3.7) | 177 | (2.1) | 28.6 | (5.2–60.0) | 184 | (1.9) | 20.0 | (6.3–45.0) | ||
| 2016 | 22 | (11.6) | 884 | (10.5) | 16.3 | (8.0–35.3) | 977 | (10.4) | 41.4 | (16.1–55.0) | ||
| 2017 | 22 | (11.6) | 1388 | (16.5) | 38.1 | (18.2–59.3) | 1487 | (15.8) | 29.7 | (17.4–36.5) | ||
| 2018 | 32 | (16.9) | 1575 | (18.7) | 28.3 | (16.0–42.1) | 1882 | (19.9) | 29.0 | (19.6–38.8) | ||
| 2019 | 27 | (14.3) | 771 | (9.2) | 25.0 | (6.3–40.0) | 870 | (9.2) | 28.3 | (15.2–50.0) | ||
| 2020 | 27 | (14.3) | 1578 | (18.8) | 20.4 | (13.6–45.5) | 1757 | (18.6) | 33.3 | (18.5–62.0) | ||
| 2021 | 32 | (16.9) | 1298 | (15.4) | 18.2 | (7.2–37.8) | 1530 | (16.2) | 27.7 | (12.6–38.8) | ||
| Cancer site | ||||||||||||
| Solid tumora | 80 | (42.3) | 3801 | (45.2) | 15.9 | (6.5–31.9) | < 0.001 | 4287 | (45.4) | 30.4 | (14.1–39.9) | 0.002 |
| Lung | 24 | (12.7) | 1332 | (15.8) | 37.2 | (10.6–55.4) | 1494 | (15.8) | 24.2 | (18.1–33.2) | ||
| Lymphoma | 17 | (9.0) | 565 | (6.7) | 45.8 | (37.1–84.0) | 697 | (7.4) | 33.3 | (27.3–54.5) | ||
| Breast | 13 | (6.9) | 327 | (3.9) | 34.8 | (19.2–42.9) | 348 | (3.7) | 55.0 | (42.9–62.5) | ||
| Mixedb | 12 | (6.3) | 743 | (8.8) | 18.0 | (5.2–33.7) | 780 | (8.3) | 15.9 | (0.0–34.4) | ||
| Melanoma | 9 | (4.8) | 263 | (3.1) | 21.1 | (13.9–26.5) | 306 | (3.2) | 9.3 | (2.8–15.2) | ||
| Othersc | 34 | (18.0) | 1373 | (16.3) | 34.2 | (18.2–42.1) | 1527 | (16.2) | 27.1 | (18.5–46.7) | ||
| Drug classification | ||||||||||||
| Chemical molecule | 90 | (47.6) | 3034 | (36.1) | 31.4 | (8.0–50.0) | 0.296 | 3624 | (38.4) | 33.3 | (17.4–49.4) | 0.035 |
| Biological product | 99 | (52.4) | 5370 | (63.9) | 24.4 | (11.1–37.1) | 5815 | (61.6) | 25.0 | (13.3–38.6) | ||
| Drug mechanism | ||||||||||||
| Targeted | 106 | (56.1) | 3981 | (47.4) | 33.3 | (10.0–45.8) | 0.003 | 4655 | (49.3) | 31.7 | (19.4–45.5) | < 0.001 |
| Immunology | 75 | (39.7) | 4216 | (50.2) | 19.3 | (9.0–31.8) | 4540 | (48.1) | 22.0 | (8.9–33.7) | ||
| Cytotoxicity | 6 | (3.2) | 175 | (2.1) | 38.5 | (17.9–84.0) | 210 | (2.2) | 73.3 | (62.5–84.6) | ||
| Cell therapy | 2 | (1.1) | 32 | (0.4) | 80.0 | (75.0–85.0) | 34 | (0.4) | 41.7 | (0.0–83.3) | ||
| Therapy type | ||||||||||||
| Monotherapy | 141 | (74.6) | 6071 | (72.2) | 24.4 | (9.1–41.2) | 0.321 | 6939 | (73.5) | 27.0 | (13.3–38.2) | 0.003 |
| Combination therapy | 48 | (25.4) | 2333 | (27.8) | 26.6 | (14.7–42.3) | 2500 | (26.5) | 35.7 | (19.7–57.2) | ||
| Performance status | ||||||||||||
| 0 ~ 1 | 160 | (84.7) | 7321 | (87.1) | 25.0 | (9.3–41.3) | 0.525 | 8094 | (85.8) | 29.7 | (15.0–44.2) | 0.919 |
| 0 ~ 2 | 29 | (15.3) | 1083 | (12.9) | 34.5 | (10.0–45.5) | 1345 | (14.2) | 27.8 | (20.0–39.0) | ||
| Biomarker-selected | ||||||||||||
| Selection needed | 72 | (38.1) | 3197 | (38.0) | 38.0 | (19.1–51.0) | < 0.001 | 3613 | (38.3) | 28.0 | (15.2–41.6) | 0.973 |
| No requirement | 117 | (61.9) | 5207 | (62.0) | 17.9 | (7.1–17.9) | 5826 | (61.7) | 30.8 | (15.0–44.0) | ||
IQR interquartile range, RR response rate, 3/4AER incidence of grade-3 or-4 adverse events
The discrepancy in the number of participants included in the analysis of RR and the number included in the analysis of 34AER is attributed to variations in the inclusion of participants for safety analysis and efficacy analysis within some trials
aThe term “Solid tumor” means patients recruited for the clinical trial should have solid tumors without specifying any specific type of cancer site
bThe term “Mixed” means patients recruited for the clinical trial are required to have either solid tumors or hematologic malignancies
cOther trials included four trials for liver cancer, three trials for colorectal cancer, and three trials for gastric cancer. Details are provided in the supplement
Response rate
We observed an overall RR with a median value of 25.4% [IQR, 9.4–41.4%], and no statistically significant trend in RR over time (p = 0.392). However, a significant disparity in RR was observed across different indications (p < 0.001), with trials targeting lymphoma, lung cancer, and breast cancer showing the highest RR, each with a median RR of 45.8% [IQR, 37.1–84.0%], 37.2% [IQR, 10.6–55.4%], and 34.8% [IQR, 19.2–42.9%] respectively. Further analysis revealed that the two trials involving cell therapy exhibited the highest RR, with a median of 80% [IQR, 75.0–85.0%], followed by cytotoxicity drugs at 38.5% [IQR, 17.9–84.0%], and targeted therapies at 33.3% [IQR, 10.0–45.8%]. The inclusion of patients with a PS of 0–2 did not significantly impact the RR observed in the study (p = 0.525). However, trials that required biomarker testing demonstrated a significantly higher RR, compared with those that did not (38.0% [IQR, 19.1–51.0%]; p < 0.001) (Table 1).
Incidence of adverse events
Among all trials included in the analysis, the median overall incidence of grade-3/4 adverse events was 29.3% [IQR, 15.0–43.8%]. No statistically significant trend was observed over the study period (p = 0.453). Univariate analysis indicated significant variations in the incidence rate across different indications (p < 0.001). Specifically, breast cancer trials exhibited the highest incidence, with a median of 55.0% [IQR, 42.9–62.5%], followed by lymphoma trials at 33.3% [IQR, 27.3–54.5%] and trials of solid tumors at 30.4% [IQR, 14.1–39.9%]. Additionally, trials evaluating biological products exhibited a higher incidence of grade-3/4 adverse events, compared with those assessing chemical molecules (p = 0.035). Moreover, trials examining cytotoxicity and combination therapies also reported higher incidence rates (p < 0.001 and p = 0.003, respectively), when compared with other treatment modalities. The overall treatment-related mortality rate was 1%, with a subgroup analysis revealing elevated mortality rates in the immunotherapy group (1.4%) and among trials with mixed indications (2.4%) (Supplementary e-Table 4).
Correlation between benefit and risk
In the analysis of the correlation between RR and the incidence of grade-3/4 adverse events, a weak positive correlation was identified (ρ= 0.217; p = 0.003). However, the subgroup analysis revealed a significant positive linear correlation exclusively within immunotherapy trials (p = 0.417; p < 0.001) (Fig. 2). A multivariate interaction analysis showed that the interaction term between RR and drug mechanism was significantly correlated with the incidence of grade-3/4 adverse events (p = 0.003) (Supplementary e-Table 5).
Fig. 2.
Correlation between response rate and incidence of grade-3/4 adverse events. In certain trials, some patients achieved the best response of stable disease, resulting in a RR (complete response and partial response) of 0 for those trials. aOnly two trials in the “Cell therapy” sub-group reported both RR and incidence of grade-3/4 adverse events, so a straight line could not be fitted and Spearman correlation coefficient cannot be calculated
Discussion
Our analysis of 189 phase-I trials registered in China revealed a higher median overall RR of 25.4%, compared with RRs of 18.0% and 6.4% reported in international studies [8, 14]. Furthermore, we observed a higher incidence of grade-3/4 adverse events, with a rate of 29.3%, in contrast to 13.2% and 17% found in previous research [8, 15]. The RR showed a correlation with the incidence of grade-3/4 adverse events. Notably, no statistically significant trends were observed for efficacy and safety over time.
The higher median RR of phase-I trials registered in China could be attributed in part to publication bias, as previous research indicates that trials with negative results are less frequently published [16], potentially inflating RR values. Among the 1071 studies meeting our inclusion criteria, only 189 trials (17.6%) had publicly available results that disclosed both benefits and risks entailed in the drug examined. This underscores the need for more comprehensive reporting to ensure an accurate assessment and synthesis of clinical efficacy and safety. In our data analysis, we examined trends in RR over time; yet, no statistically significant changes were observed (p = 0.392). Previous studies, however, have reported an upward trend in RR in early-phase trials, likely due to the emergence of various new therapies [14]. Our study, constrained by limited data access from trials transitioning from cytotoxic drugs to targeted therapies and immunotherapies in mainstream anticancer treatments, did not observe these temporal trends in RR.
The observed discrepancy in the incidence of adverse events between our review and international studies previously conducted likely stems from variations in reporting standards across the studies included in our analysis. Most studies reported treatment-emergent adverse events (TEAE), rather than treatment-related adverse events (TRAE), though the latter is more commonly reported in international studies. This distinction may account for the higher incidence of adverse events noted in our findings [17].
Another intriguing finding from our analysis is the higher RR observed among cytotoxic drugs. We found that four out of the six cytotoxic trials included in our analysis specifically investigated liposomal mitoxantrone hydrochloride, which reported RRs of 87.1%, 84.0%, 42.1%, and 17.8%, respectively. This enhanced efficacy may be attributed to the passive targeting capacity of liposomal formulations, which can facilitate drug delivery to tumor sites and improve therapeutic outcomes [18].
Our correlation analysis revealed a weak association between the overall RR and the incidence of grade-3/4 adverse events. Subgroup analysis indicated that this correlation is primarily driven by trials of immunotherapies. Further interaction analysis confirmed that immunotherapy is the primary factor linking RR with the incidence of grade-3/4 adverse events, which is consistent with findings in previous research [19–21].
Our findings indicate that including patients with a PS of 2 was not associated with a worse risk–benefit profile in phase-I clinical trials of anticancer therapies. While the prognostic impact of PS scores on RR is still debated, particularly as patient-level studies in specific cancer types have shown varied outcomes [22–25], our analysis did not differentiate by cancer type. Despite this limitation, our data supports the potential for early-phase clinical trials to consider relaxing PS requirements.
Our findings reinforce the ASCO statement that “phase-I clinical trials potentially provide patients [who enroll] with clinical benefit” [2, 26]. This leads us to several recommendations for patient enrollment and trial design. First, future trials that require biomarker testing during patient enrollment shall be prioritized as they are likely to entail greater treatment efficacy than those that do not set such an inclusion criterion. Second, trials that investigate therapies for specific monogenic cancers could also be prioritized, given that clinical trials involving multiple types of solid tumors tend to demonstrate lower RR. Therefore, it is advisable that early-phase clinical trials be tailored to a specific cancer type, taking into account relevant preclinical research findings.
This study has several limitations. Firstly, we excluded publications and conference abstracts that reported the incidence of adverse events by type as we were unable to obtain the exact number of patients experiencing grade-3/4 adverse events from these reports. Secondly, despite our thorough search efforts, the trials included in our analysis accounted for only 17.6% of all studies meeting our inclusion criteria. This limited representation may introduce selection bias, potentially affecting the generalizability of our findings. Thirdly, as this study is a secondary analysis based on published clinical trial results, it is subject to publication bias. Negative clinical trial findings often receive little attention from the academic community and may also have adverse implications for the journals that publish them [26]. Consequently, the actual benefit of phase-I oncology trials may be lower, and the associated risks potentially greater than indicated by our findings. Fourthly, we selected the incidence of grade-3/4 adverse events as the main safety endpoint; however, this outcome may compete with trial discontinuation due to AEs. As a result, the true burden of severe adverse events could be underestimated. Lastly, the benefit and risk data utilized in our study are aggregated at the trial level, resulting in the loss of detailed information about specific patient cases. To assess the risk–benefit profile of drugs that underwent phase-I clinical trials, future studies should be conducted using patient-level data.
In summary, our trial-level analysis found that the early efficacy and safety profiles of phase-I clinical trials conducted in China are broadly comparable to those reported in international studies. As phase-I trials primarily focus on preliminary efficacy signals and short-term safety outcomes, our findings reflect these early-stage characteristics rather than a comprehensive risk–benefit evaluation. We observed that risks and benefits associated with anticancer therapies tend to be correlated, particularly among immunotherapies, suggesting that improved efficacy may come at the expense of increased toxicity. However, a more precise understanding of this relationship, especially across different drug classes, requires further investigation using patient-level data to better characterize the full risk–benefit profile of these treatments.
Supplementary Information
Below is the link to the electronic supplementary material.
Author contributions
ZL, YY, YZ and XG designed the study and were involved in the interpretation of the results. ZL and YY collected the data and organized data set. ZL, YY and YZ conducted the data analysis. KH, HL drafted the manuscript. YZ and XG provided critical revision of the manuscript. All authors provided constructive input and approved the final version for publication. LS supervised the study.
Funding
Funding was provided by the National Natural Science Foundation of China (Grant No. 72274004). The funders had no involvement in study design, data collection and analysis, decisions regarding publication, or manuscript preparation.
Data availability
Data is provided within the supplementary information files.
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
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Data Availability Statement
Data is provided within the supplementary information files.