Risk comparison of adverse reactions among gemcitabine monotherapy, gemcitabine combined with cisplatin, gemcitabine combined with PD-1/PD-L1 inhibitors treatment: insights from the FDA adverse event reporting system database

Risk comparison of adverse reactions among gemcitabine monotherapy, gemcitabine combined with cisplatin, gemcitabine combined with PD-1/PD-L1 inhibitors treatment: insights from the FDA adverse event reporting system database | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Risk comparison of adverse reactions among gemcitabine monotherapy, gemcitabine combined with cisplatin, gemcitabine combined with PD-1/PD-L1 inhibitors treatment: insights from the FDA adverse event reporting system database Zhineng Zhu, Ying Sun, Lei Lyu, Gaofeng Zhou, Jingdong Yuan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7907815/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background Although gemcitabine (GEM) has long been the standard treatment for cancer, its combination with other drugs has shown better therapeutic effects. Therefore, our study sought to evaluate and compare the risk of adverse events (AEs) with GEM, GEM combined with cisplatin, GEM combined with PD-1 inhibitors (pembrolizumab and nivolumab), and GEM combined with the PD-L1 inhibitor (durvalumab) treatment. Method Based on the data extracted from the FAERS database from Q1 2004 to Q4 2024, including GEM as the primary suspected (PS) drug and GEM as PS plus cisplatin/pembrolizumab/nivolumab/durvalumab as a secondary suspect (SS), concomitant drug (C), or interacting drug (I), the risk of AEs was investigated through reporting odds ratio (ROR), proportional reporting ratio (PRR), bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS). Furthermore, time-to-onset (TTO) analysis was carried out to further understand the pattern of AE occurrence. Results Between Q1 2004 and Q4 2024, a total of 20,135 GEM-related, 3,647 GEM combined with cisplatin-related, 152 GEM combined with pembrolizumab-related, 107 GEM combined with nivolumab-related, and 391 GEM combined with durvalumab-related AEs were collected. At the system organ categories (SOC) level, blood and lymphatic system disorders was the common positive SOC for five treatment groups. At the preferred terms (PT) level, there were three common AEs among five treatment groups, namely thrombocytopenia, neoplasm progression, and pneumonitis. Among the three AEs, the risk of thrombocytopenia was the highest in the GEMcombined with cisplatin treatment group [ROR(95%CI) = 18.12 (16.22-20.23)], and the risk of neoplasm progression and pneumonitis was the highest in the GEMcombined with durvalumab [neoplasm progression: ROR(95%CI) = 28.19 (16.62-47.83); pneumonitis: ROR(95%CI) = 31.41 (17.32-56.95)]. Notably, most AEs among five treatment groups occurred within 30 days. Conclusion These findings highlight the safety profiles of GEM, as well as GEM combination therapy, and offer important insights to enhance the clinical use and minimize potential adverse effects. Gemcitabine Cisplatin Pembrolizumab Nivolumab Durvalumab Adverse event FAERS Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1 Introduction Gemcitabine (GEM) is an anticancer agent derived from cytidine nucleosides, extensively utilized in the treatment of multiple malignancies, including pancreatic, bladder, breast, ovarian, and lung cancers, among others [ 1 ]. It predominantly inhibits nucleotide reductase to obstruct DNA synthesis, resulting in cell cycle arrest and apoptosis [ 2 ]. Nonetheless, in clinical application, the effectiveness of GEM is considerably constrained by factors such as drug resistance and toxicity [ 3 , 4 ]. Combination therapy can improve therapeutic efficacy and diminish the likelihood of drug resistance by utilizing various modes of action or signaling pathways, thus reducing necessary dosages and systemic toxicity; therefore, GEM is often utilized alongside other anticancer agents in clinical practice to enhance treatment efficacy [ 5 ]. Prior research has shown that the combination of gemcitabine and cisplatin significantly extends patient survival in the treatment of various malignancies compared to monotherapy with gemcitabine [ 6 – 9 ]. Additionally, GEM can regulate immune responses in the tumor microenvironment, therefore affecting anticancer immune responses [ 10 ]. Numerous clinical trials demonstrate that GEM has synergistic benefits with immune checkpoint inhibitors (ICIs) against cancer cells in comparison to monotherapy and can surmount resistance to ICI treatment [ 11 ]. Principe et al. conducted research indicating that in cases of TGF-β signaling deficiencies, a combination of GEM and anti-PD-1 therapy elicits strong CD8 + T cell responses and diminishes tumor size, therefore enhancing overall survival in pancreatic cancer patients [ 12 ]. Wang et al. demonstrated that the combination of GEM and anti-PD-L1 therapy (aPDL1-GEM@Gel) markedly inhibited tumor growth in the B16F10 mouse melanoma model, while also promoting CD4 + and CD8 + T cell infiltration and eliciting systemic immune responses [ 13 ]. Nevertheless, current research has predominantly concentrated on efficacy, whereas investigations assessing safety continue to exhibit specific shortcomings. Moreover, the safety statistics from current clinical trials may not accurately represent real-world conditions. The FAERS database documents all adverse events (AEs) and medication errors reported to the FDA, facilitating the discovery and quantitative analysis of signals that indicate irregularities in drug adverse reaction reports, thereby enabling the identification of correlations between particular medications and specific adverse occurrences [ 14 ]. Therefore, based on the FAERS database, we examined and contrasted the risks of AEs linked to GEM monotherapy and combination therapies (cisplatin, anti-PD-1 inhibitors [pembrolizumab and nivolumab], and anti-PD-L1 inhibitors [durvalumab]), and also investigated the characteristics of these AEs. This study seeks to identify potential safety disparities among treatment regimens, offering real-world data to enable the formulation of more tailored drug strategies and risk assessment processes in clinical practice. 2 Materials and Methods 2.1 Data extraction and processing The data for this study was extracted from the FAERS database ( https://www.fda.gov/drugs ), covering from the first quarter of 2004 to the fourth quarter of 2024, which contained seven datasets: demographic and administrative information (DEMO), drug information (DRUG), adverse drug reaction information (REAC), patient outcomes information (OUTC), reported sources (RPSR), drug therapy start dates and end dates (THER), and indications for drug administration (INDI) [ 15 ]. The keywords “Gemcitabine,” “Cisplatin,” “Pembrolizumab,” “Nivolumab,” and “Durvalumab” were utilized to retrieve associated AEs. The inclusion criteria for drugs were as follows: (1) GEM was the primary suspect (PS) for suspected drugs; (2) cases treated with GEM (PS) plus cisplatin/pembrolizumab/nivolumab/durvalumab (as a secondary suspect, SS; concomitant drug, C; or interacting drug, I). According to the FAERS database guide, duplicate AE reports were identified and deleted. Specifically, if CASEID matched, the latest FDA_DT was chosen; if CASEID and FDA_DT both matched, the higher PRIMARYID was preferred. Since the drug’s names were not standardized in the FAERS database, RxNorm was applied to standardize the drug’s names. The drug-related AE signals were standardized and categorized at the system organ class (SOC) and preferred term (PT) levels obtained from the MedDRA 26.0. 2.2 Disproportionality analysis Based on the classical four-fold table (Table 1 ), disproportional algorithms, including reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS), were applied to identify and compare correlations between drugs and AEs. The specific calculation formulas and thresholds of each algorithm were displayed in Table 2 . In our study, a positive signal was considered when the thresholds of the above four algorithms were satisfied simultaneously. The greater the value of the four algorithms, the stronger the signal intensity, which indicates that the stronger the correlation between the drug and the occurrence of AEs. Table 1 Four-grid table for signal detection Target adverse drug event Other adverse drug event Sums Gemcitabine combined with other drugs (Cisplatin/Pembrolizumab/Nivolumab/Durvalumab) a b a + b Gemcitabine c d c + d Sums a + c b + d a + b + c + d Table 2 Overview of the main algorithms used for signal detection Method Equation Criteria ROR ROR= \(\:\frac{\text{a}\text{d}}{bc}\) ROR 95%CI = e ln(ROR)±1.96 \(\:\sqrt{\frac{1}{a}+\frac{1}{b}+\frac{1}{c}+\frac{1}{d}}\) a ≥ 3 and 95%CI(lower limit) > 1 PRR PRR= \(\:\frac{\text{a}(\text{c}+\text{d})}{\text{c}(\text{a}+\text{b})}\) PRR 95%CI = eln(PRR) ± 1.96 \(\:\sqrt{(\frac{1}{\text{a}}-\frac{1}{\text{a}+\text{b}}+\frac{1}{\text{c}}-\frac{1}{\text{c}+\text{d}})}\) χ2=[(ad-bc)^2](a + b + c + d)/[(a + b)(c + d)(a + c)(b + d)] a ≥ 3, PRR ≥ 2, χ2 ≥ 4 BCPNN IC = log 2 \(\:\frac{\text{a}(\text{a}+\text{b}+\text{c}+\text{d})}{\begin{array}{c}(a+b)(a+c)\\\:\end{array}}\) IC 025 = e ln(IC)−1.96 \(\:\sqrt{(\frac{1}{a}+\frac{1}{b}+\frac{1}{c}+\frac{1}{d})}\) IC025>0 MGPS EBGM= \(\:\frac{\text{a}(\text{a}+\text{b}+\text{c}+\text{d})}{\begin{array}{c}(a+c)(a+b)\\\:\end{array}}\) EBGM05 = e ln(EBGM)±1.96 \(\:\sqrt{\frac{1}{a}+\frac{1}{b}+\frac{1}{c}+\frac{1}{d}}\) EBGM05>2 ROR: Reporting odds ratio; PRR: Proportional reporting ratio; BCPNN: Bayesian confidence propagation neural network; MGPS: Multi-item gamma Poisson shrinker; EBGM: Empirical Bayesian ensemble mean; IC: Information component; CI: Confidence interval. 2.3 Time-to-onset (TTO) analysis TTO was defined as the time interval between the AE start date (EVENT_DT) and the drug start date (START_DT). To further elucidate the temporal feature of drug-related significant AEs, TTO features were evaluated by the median, minima-maxima, quartile, and Weibull shape parameter. In our study, we only considered shape (β) in the Weibull shape parameter. When β < 1 and its 95%CI < 1, the risk of AEs is deemed to diminish over time (early failure-type curve); if β is approximately equal to 1 and its 95% CI encompasses the value 1, the risk will continue to occur over time (random failure-type curve); and if β > 1 and its 95% CI excludes the value 1, the risk is regarded as escalating over time (wear-out failure-type curve). 2.4 Statistical analysis Descriptive statistical analysis was employed to show a range of characteristic information of AE reports enrolled in our study. All analyses were carried out by R software (version 4.2.1). A P-value below 0.05 was deemed statistically significant. 3 Results 3.1 Descriptive analysis In the FAERS database, from Q1 2004 to Q4 2024, a total of 20,135 AEs with GEM as PS were collected, 3,647 AEs for GEM combined with cisplatin, 152 AEs for GEM combined with pembrolizumab, 107 AEs for GEM combined with nivolumab, and 391 AEs for GEM combined with durvalumab (Table 3 ). Excepting the GEM combined with pembrolizumab treatment group (male vs. female = 26.3% vs. 38.2%), the proportion of the male population was higher than that of the female population in the remaining four groups (GEM: male vs. female = 41.0% vs. 37.5%; GEM combined with cisplatin: male vs. female = 44.7% vs. 26.9%; GEM combined with nivolumab: male vs. female = 54.2% vs. 23.4%; GEM combined with durvalumab: male vs. female = 54.0% vs. 41.4%). Excepting missing data, the population using GEM, GEM combined with cisplatin, GEM combined with pembrolizumab, and GEM combined with nivolumab all accounted for the highest proportion in the 18–64 years group (GEM: 32.8%; GEM combined with cisplatin: 37.3%; GEM combined with pembrolizumab: 39.5%; GEM combined with nivolumab: 44.9%), while the highest proportion in the GEM combined with durvalumab treatment group was in the 65–85 years group (47.3%). In terms of reporting sources, physicians contributed more reports in the GEM (39.1%), GEM combined with cisplatin (39.8%), and GEM combined with durvalumab (39.1%), while in the remaining groups, other health-professionals contributed more reports (GEM combined with pembrolizumab: 27.0%; GEM combined with nivolumab: 33.6%). In terms of serious outcome, other serious outcomes accounted for the highest proportion in GEM (36.5%), GEM combined with cisplatin (40.0%), and GEM combined with pembrolizumab (39.5%), death for GEM combined with nivolumab (42.1%), and hospitalization for GEM combined with durvalumab (55.2%). For the source of reports, Table 4 displayed the top 5 countries. Specifically, most of AE reports in GEM, GEM combined with cisplatin, and GEM combined with pembrolizumab were sourced from the United States (29.0%, 17.6%, 34.9%), most AE reports in GEM combined with nivolumab from France (29.0%), and most AE reports in GEM combined with durvalumab from Canada (74.7%). Table 3 Baseline characteristics of reports in five treatment groups from the FAERS database Gemcitabine (N = 20,135) Gemcitabine combined with Cisplatin (N = 3,647) Gemcitabine combined with Pembrolizumab (N = 152) Gemcitabine combined with Nivolumab (N = 107) Gemcitabine combined with Durvalumab (N = 391) Gender F 7548(37.5%) 982(26.9%) 58 (38.2%) 25 (23.4%) 162 (41.4%) M 8247(41.0%) 1629(44.7%) 40 (26.3%) 58 (54.2%) 211 (54.0%) Unknown 4340(21.6%) 1036(28.4%) 54 (35.5%) 24 (22.4%) 18 (4.6%) Age 85 125(0.6%) 4(0.1%) / / / 18ཞ64 6597(32.8%) 1359(37.3%) 60 (39.5%) 48 (44.9%) 167 (42.7%) 65ཞ85 6483(32.2%) 971(26.6%) 30 (19.7%) 35 (32.7%) 185 (47.3%) Unknown 6747(33.5%) 1290(35.4%) 60 (39.5%) 24 (22.4%) 38 (9.7%) Reporter’s occupation Consumer (CN) 3965(19.7%) 580(15.9%) 31 (20.4%) 18 (16.8%) 101 (25.8%) Health-professional (HP) 1719(8.5%) 403(11.1%) 37 (24.3%) 25 (23.4%) 79 (20.2%) Lawyer (LW) 4(0.0%) 1(0.0%) / / / Physician (MD) 7880(39.1%) 1453(39.8%) 40 (26.3%) 28 (26.2%) 153 (39.1%) Other health-professional (OT) 5103(25.3%) 1044(28.6%) 41 (27.0%) 36 (33.6%) 43 (11.0%) Pharmacist (PH) 957(4.8%) 122(3.3%) 3 (2.0%) / 14 (3.6%) Registered Nurse (RN) 2(0.0%) / / / / Unknown 505(2.5%) 44(1.2%) / / 1 (0.3%) Serious outcome Death (DE) 4417(21.9%) 788(21.6%) 40 (26.3%) 45 (42.1%) 66 (16.9%) Disability (DS) 142(0.7%) 20(0.5%) 1 (0.7%) / 9 (2.3%) Hospitalization (HO) 6191(30.7%) 1026(28.1%) 30 (19.7%) 24 (22.4%) 216 (55.2%) Life-threatening (LT) 1120(5.6%) 225(6.2%) 14 (9.2%) 3 (2.8%) 7 (1.8%) Other serious outcomes (OT) 7344(36.5%) 1459(40.0%) 60 (39.5%) 33 (30.8%) 70 (17.9%) Required intervention (RI) 15(0.1%) 2(0.1%) / / / Missing 906(4.5%) 127(3.5%) 7 (4.6%) 2 (1.9%) 23 (5.9%) Table 4 The top 5 countries of reporting sources for five treatment groups Countries Drugs Gemcitabine UNITED STATES 5846 (29.0%) JAPAN 2202 (10.9%) FRANCE 2186 (10.9%) ITALY 1382 (6.9%) UNITED KINGDOM 1223 (6.1%) Gemcitabine combined with Cisplatin UNITED STATES 643 (17.6%) JAPAN 366 (10.0%) FRANCE 361 (9.9%) UNITED KINGDOM 279 (7.7%) ITALY 271 (7.4%) Gemcitabine combined with Pembrolizumab UNITED STATES 53 (34.9%) FRANCE 23 (15.1%) GERMANY 10 (6.6%) SPAIN 10 (6.6%) CHINA 9 (5.9%) Gemcitabine combined with Nivolumab FRANCE 31 (29.0%) UNITED STATES 16 (15.0%) GERMANY 12 (11.2%) AUSTRIA 6 (5.6%) JAPAN 6 (5.6%) UNITED KINGDOM 6 (5.6%) Gemcitabine combined with Durvalumab CANADA 292 (74.7%) FRANCE 53 (13.6%) JAPAN 7 (1.8%) KOREA, SOUTH 5 (1.3%) SPAIN 5 (1.3%) UNITED KINGDOM 5 (1.3%) Figure 1 visualized the number of reports between Q1 2004 and Q4 2024. For the GEM treatment group, the peak was in 2015 (n = 1,954). For the GEM combined with cisplatin treatment group, the number of reports was more than 300 from 2016 to 2020, reaching a peak of 345 in 2020. For the GEM combined with pembrolizumab treatment group, the peak was 2018 (n = 41), while the number of reports in 2019 was the smallest (n = 1). For the GEM combined with nivolumab treatment group, there were two peaks, one in 2018 (n = 32) and the other in 2021 (n = 25). For the GEM combined with durvalumab treatment group, the peak was in 2020 (n = 112). 3.2 Signal detection at the SOC level At the SOC level, AEs associated with GEM, GEM combined with cisplatin, GEM combined with pembrolizumab, GEM combined with nivolumab, and GEM combined with durvalumab affected 27, 27, 24, 22, and 21 SOCs, respectively ( Supplementary Table 1 ) (Fig. 2 ). Through comprehensive analysis, excepting the GEM combined with durvalumab treatment group, the SOC with the highest number of AEs was general disorders and administration site conditions (GEM: n = 8,922; GEM combined with cisplatin: n = 1,538; GEM combined with pembrolizumab: n = 109; GEM combined with nivolumab: n = 97). For the GEM combined with durvalumab treatment group, the top 1 SOC was infections and infestations (n = 127). For five treatment groups, 3 positive SOC for GEM, 3 positive SOC for GEM combined with cisplatin, 3 positive SOC for GEM combined with pembrolizumab, 2 positive SOC for GEM combined with nivolumab, and 3 positive SOC for GEM combined with durvalumab were identified (Fig. 3 ). The blood and lymphatic system disorders was the positive signal in all treatment groups [GEM: ROR (95%CI) = 8.23 (8.04–8.44); GEM combined with cisplatin: ROR (95%CI) = 9.64 (9.12–10.19); GEM combined with pembrolizumab: ROR (95%CI) = 6.88 (5.42–8.73); GEM combined with nivolumab: ROR (95%CI) = 4.4 (3.14–6.18); GEM combined with durvalumab: ROR (95%CI) = 4.84 (3.75–6.24)]. 3.3 Signal detection at the PT level At the PT level, a total of 574 positive AEs for GEM, 245 positive AEs for GEM combined with cisplatin, 38 positive AEs for GEM combined with pembrolizumab, 39 positive AEs for GEM combined with nivolumab, and 57 positive AEs for GEM combined with durvalumab were identified ( Supplementary Table 2 ) (Fig. 4 ). After integrating, three common AEs among five treatment groups were found: thrombocytopenia, neoplasm progression, and pneumonitis (Fig. 5 ). Among these AEs, thrombocytopenia exhibited the strongest correlation with GEM combined with cisplatin [ROR (95%CI): GEM vs. GEM combined with cisplatin vs. GEM combined with pembrolizumab vs. GEM combined with nivolumab vs. GEM combined with durvalumab = 12.81 (12.14–13.52) vs. 18.12 (16.22–20.23) vs. 14.93 (9.46–23.55) vs. 9.85 (5.09–19.04) vs. 8.71 (5.03–15.06)]. The neoplasm progression showed the highest association with GEM combined with durvalumab [ROR (95%CI): GEM vs. GEM combined with cisplatin vs. GEM combined with pembrolizumab vs. GEM combined with nivolumab vs. GEM combined with durvalumab = 14.5 (13.29–15.81) vs. 12.02 (9.56–15.12) vs. 9.23 (3.46–24.67) vs. 22.9 (10.86–48.3) vs. 28.19 (16.62–47.83)]. The pneumonitis was the most relevant to GEM combined with durvalumab [ROR (95%CI): GEM vs. GEM combined with cisplatin vs. GEM combined with pembrolizumab vs. GEM combined with nivolumab vs. GEM combined with durvalumab = 11.34 (10.09–12.74) vs. 6.21 (4.25–9.06) vs. 19.77 (8.85–44.15) vs. 13.85 (4.45–43.11) vs. 31.41 (17.32–56.95)]. Through comparing, we found some AEs were positive signals in the combination groups but not in the GEM treatment group, such as autoimmune haemolytic anaemia [GEM combined with cisplatin: ROR (95%CI) = 9.38 (3.9-22.56)], osteomyelitis [GEM combined with pembrolizumab: ROR (95%CI) = 13.81 (4.44–42.92)], pelvic venous thrombosis [GEM combined with nivolumab: ROR (95%CI) = 326.25 (121.79-873.97)], bacillus infection [GEM combined with durvalumab: ROR (95%CI) = 353.22 (113.34-1100.78)]. In blood and lymphatic system disorders, 38 AEs for GEM, 28 AEs for GEM combined with cisplatin, 4 AEs for GEM combined with pembrolizumab, 4 AEs for GEM combined with nivolumab, and 4 AEs for GEM combined with durvalumab were identified (Table 5 ). After analyzing data, we found the AE species of GEM contained all the AEs of each combination group. Although the number of AEs in the combination groups decreased, the risk increased, such as myelosuppression [ROR(95%CI): GEM vs. GEM combined with cisplatin vs. GEM combined with pembrolizumab vs. GEM combined with durvalumab = 8.98 (7.83–10.29) vs. 19.86 (15.88–24.82) vs. 10.81 (3.48–33.62) vs. 18.71 (8.38–41.77)], pancytopenia [ROR(95%CI): GEM vs. GEM combined with cisplatin vs. GEM combined with nivolumab vs. GEM combined with durvalumab = 8.06 (7.33–8.86) vs. 10.62 (8.7-12.98) vs. 10.96 (4.54–26.45) vs. 14.84 (8.19–26.91)], and so on. Additionally, we also found autoimmune haemolytic anaemia, immune thrombocytopenia, normocytic anaemia, and white blood cell disorder were positive signals in the GEM combined with cisplatin treatment group, but not in the GEM treatment group. Table 5 The single strength of blood and lymphatic system disorders-related AEs in each treatment group at the PT level Treatment Group PT n ROR(95%Cl) PRR(Chi-square) EBGM(EBGM05) IC(IC025) Gemcitabine Thrombocytopenia 1368 12.81 ( 12.14–13.52 ) 12.54 ( 14357.99 ) 12.38 ( 11.84 ) 3.63 ( 3.55 ) Neutropenia 1052 7.98 ( 7.5–8.48 ) 7.86 ( 6253.87 ) 7.8 ( 7.41 ) 2.96 ( 2.87 ) Anaemia 1035 5.47 ( 5.15–5.82 ) 5.4 ( 3697.3 ) 5.37 ( 5.1 ) 2.43 ( 2.33 ) Thrombotic microangiopathy 636 75.79 ( 69.87–82.21 ) 74.99 ( 42890.2 ) 69.34 ( 64.78 ) 6.12 ( 6 ) Leukopenia 442 9.02 ( 8.21–9.91 ) 8.96 ( 3099.69 ) 8.89 ( 8.21 ) 3.15 ( 3.01 ) Pancytopenia 435 8.06 ( 7.33–8.86 ) 8.01 ( 2646.59 ) 7.95 ( 7.34 ) 2.99 ( 2.85 ) Febrile neutropenia 423 6.58 ( 5.98–7.25 ) 6.54 ( 1974.73 ) 6.5 ( 6 ) 2.7 ( 2.56 ) Haemolytic uraemic syndrome 292 137.41 ( 121.47–155.45 ) 136.75 ( 34190.15 ) 118.95 ( 107.29 ) 6.89 ( 6.71 ) Bone marrow failure 225 10.7 ( 9.38–12.21 ) 10.67 ( 1949.18 ) 10.56 ( 9.45 ) 3.4 ( 3.21 ) Myelosuppression 209 8.98 ( 7.83–10.29 ) 8.95 ( 1461.79 ) 8.87 ( 7.91 ) 3.15 ( 2.95 ) Haematotoxicity 198 24.14 ( 20.96–27.8 ) 24.06 ( 4263.72 ) 23.46 ( 20.85 ) 4.55 ( 4.34 ) Disseminated intravascular coagulation 119 8.31 ( 6.94–9.96 ) 8.3 ( 756.78 ) 8.23 ( 7.07 ) 3.04 ( 2.78 ) Thrombocytosis 107 31.53 ( 25.99–38.23 ) 31.47 ( 3050.98 ) 30.45 ( 25.91 ) 4.93 ( 4.65 ) Thrombotic thrombocytopenic purpura 100 28.82 ( 23.62–35.18 ) 28.78 ( 2598.77 ) 27.92 ( 23.63 ) 4.8 ( 4.51 ) Haemolytic anaemia 83 9.33 ( 7.51–11.58 ) 9.31 ( 609.82 ) 9.23 ( 7.7 ) 3.21 ( 2.89 ) Leukocytosis 63 3.53 ( 2.76–4.53 ) 3.53 ( 113.85 ) 3.52 ( 2.86 ) 1.82 ( 1.45 ) Cytopenia 59 5.54 ( 4.29–7.16 ) 5.54 ( 218.17 ) 5.51 ( 4.45 ) 2.46 ( 2.09 ) Agranulocytosis 49 2.77 ( 2.09–3.66 ) 2.76 ( 55.05 ) 2.76 ( 2.18 ) 1.46 ( 1.06 ) Atypical haemolytic uraemic syndrome 45 64.26 ( 47.49–86.96 ) 64.22 ( 2615.18 ) 60.03 ( 46.61 ) 5.91 ( 5.47 ) Lymphopenia 43 3.1 ( 2.29–4.18 ) 3.09 ( 60.76 ) 3.09 ( 2.4 ) 1.63 ( 1.19 ) Microangiopathic haemolytic anaemia 37 49.41 ( 35.49–68.79 ) 49.38 ( 1663.18 ) 46.88 ( 35.54 ) 5.55 ( 5.07 ) Haemolysis 34 4.42 ( 3.15–6.19 ) 4.42 ( 89.42 ) 4.4 ( 3.32 ) 2.14 ( 1.65 ) Febrile bone marrow aplasia 29 7.26 ( 5.04–10.47 ) 7.26 ( 155.34 ) 7.21 ( 5.31 ) 2.85 ( 2.32 ) Blood disorder 24 2.97 ( 1.99–4.44 ) 2.97 ( 31.32 ) 2.97 ( 2.12 ) 1.57 ( 0.99 ) Erythropenia 22 73.32 ( 47.48–113.22 ) 73.29 ( 1451.38 ) 67.88 ( 47.19 ) 6.08 ( 5.46 ) Normochromic normocytic anaemia 19 6.2 ( 3.95–9.73 ) 6.2 ( 82.26 ) 6.16 ( 4.22 ) 2.62 ( 1.98 ) Bicytopenia 19 10.98 ( 6.98–17.26 ) 10.97 ( 170.17 ) 10.85 ( 7.43 ) 3.44 ( 2.79 ) Splenic infarction 17 9.9 ( 6.14–15.97 ) 9.9 ( 134.56 ) 9.8 ( 6.57 ) 3.29 ( 2.61 ) Platelet toxicity 11 138.47 ( 73.41–261.18 ) 138.44 ( 1302.04 ) 120.23 ( 70.7 ) 6.91 ( 6.02 ) Anaemia macrocytic 8 3.79 ( 1.89–7.59 ) 3.79 ( 16.37 ) 3.78 ( 2.11 ) 1.92 ( 0.95 ) Thrombocytopenic purpura 7 4.97 ( 2.37–10.45 ) 4.97 ( 22.09 ) 4.95 ( 2.66 ) 2.31 ( 1.28 ) Coombs negative haemolytic anaemia 5 26.65 ( 10.95–64.87 ) 26.65 ( 119.92 ) 25.92 ( 12.32 ) 4.7 ( 3.5 ) Hilar lymphadenopathy 4 4.64 ( 1.74–12.4 ) 4.64 ( 11.37 ) 4.62 ( 2.03 ) 2.21 ( 0.91 ) Intravascular haemolysis 4 7.12 ( 2.66–19.05 ) 7.12 ( 20.88 ) 7.07 ( 3.11 ) 2.82 ( 1.53 ) Pernicious anaemia 4 6.36 ( 2.38–17 ) 6.36 ( 17.94 ) 6.32 ( 2.78 ) 2.66 ( 1.36 ) Anaemia of malignant disease 3 10.83 ( 3.47–33.81 ) 10.83 ( 26.45 ) 10.71 ( 4.13 ) 3.42 ( 1.97 ) Hypersplenism 3 6.05 ( 1.95–18.85 ) 6.05 ( 12.58 ) 6.02 ( 2.33 ) 2.59 ( 1.14 ) Splenic vein thrombosis 3 5.77 ( 1.85–17.96 ) 5.77 ( 11.76 ) 5.74 ( 2.22 ) 2.52 ( 1.07 ) Gemcitabine combined with Cisplatin Thrombocytopenia 326 18.12 ( 16.22–20.23 ) 17.56 ( 5084.49 ) 17.51 ( 15.96 ) 4.13 ( 3.97 ) Neutropenia 207 9.29 ( 8.09–10.66 ) 9.11 ( 1496.34 ) 9.1 ( 8.11 ) 3.19 ( 2.98 ) Anaemia 179 5.6 ( 4.83–6.49 ) 5.51 ( 663.1 ) 5.51 ( 4.87 ) 2.46 ( 2.25 ) Febrile neutropenia 116 10.71 ( 8.92–12.87 ) 10.6 ( 1007.76 ) 10.58 ( 9.08 ) 3.4 ( 3.13 ) Pancytopenia 97 10.62 ( 8.7–12.98 ) 10.53 ( 835.78 ) 10.51 ( 8.89 ) 3.39 ( 3.1 ) Leukopenia 89 10.72 ( 8.7–13.21 ) 10.63 ( 775.98 ) 10.62 ( 8.91 ) 3.41 ( 3.1 ) Myelosuppression 78 19.86 ( 15.88–24.82 ) 19.71 ( 1380.76 ) 19.64 ( 16.3 ) 4.3 ( 3.97 ) Bone marrow failure 45 12.6 ( 9.4–16.9 ) 12.55 ( 477.45 ) 12.52 ( 9.8 ) 3.65 ( 3.22 ) Thrombotic microangiopathy 44 28.73 ( 21.35–38.66 ) 28.6 ( 1166.11 ) 28.46 ( 22.2 ) 4.83 ( 4.4 ) Haematotoxicity 35 24.8 ( 17.78–34.58 ) 24.72 ( 792.92 ) 24.61 ( 18.63 ) 4.62 ( 4.14 ) Thrombocytosis 21 35.75 ( 23.27–54.94 ) 35.68 ( 703.24 ) 35.45 ( 24.75 ) 5.15 ( 4.53 ) Atypical haemolytic uraemic syndrome 16 129.86 ( 79.06–213.31 ) 129.66 ( 1994.64 ) 126.63 ( 83.6 ) 6.98 ( 6.28 ) Agranulocytosis 15 5.02 ( 3.03–8.33 ) 5.02 ( 48.19 ) 5.01 ( 3.28 ) 2.33 ( 1.6 ) Leukocytosis 14 4.65 ( 2.75–7.86 ) 4.64 ( 40.01 ) 4.64 ( 2.99 ) 2.21 ( 1.47 ) Haemolytic anaemia 14 9.26 ( 5.48–15.65 ) 9.25 ( 102.85 ) 9.24 ( 5.95 ) 3.21 ( 2.46 ) Splenic infarction 13 44.9 ( 26–77.52 ) 44.84 ( 552.63 ) 44.48 ( 28.16 ) 5.48 ( 4.7 ) Disseminated intravascular coagulation 13 5.34 ( 3.1–9.21 ) 5.34 ( 45.79 ) 5.33 ( 3.38 ) 2.42 ( 1.64 ) Cytopenia 12 6.66 ( 3.78–11.74 ) 6.66 ( 57.63 ) 6.65 ( 4.14 ) 2.73 ( 1.93 ) Thrombotic thrombocytopenic purpura 9 14.96 ( 7.77–28.79 ) 14.95 ( 116.81 ) 14.91 ( 8.62 ) 3.9 ( 2.98 ) Microangiopathic haemolytic anaemia 6 45.5 ( 20.37–101.64 ) 45.47 ( 258.78 ) 45.1 ( 23.02 ) 5.5 ( 4.4 ) Febrile bone marrow aplasia 5 7.39 ( 3.07–17.77 ) 7.39 ( 27.57 ) 7.38 ( 3.54 ) 2.88 ( 1.7 ) Autoimmune haemolytic anaemia 5 9.38 ( 3.9–22.56 ) 9.38 ( 37.36 ) 9.36 ( 4.49 ) 3.23 ( 2.05 ) Bicytopenia 5 17 ( 7.07–40.92 ) 17 ( 75.04 ) 16.95 ( 8.13 ) 4.08 ( 2.9 ) Immune thrombocytopenia 5 7.89 ( 3.28–18.98 ) 7.89 ( 30.04 ) 7.88 ( 3.78 ) 2.98 ( 1.8 ) Normocytic anaemia 4 18.82 ( 7.05–50.24 ) 18.81 ( 67.24 ) 18.75 ( 8.25 ) 4.23 ( 2.94 ) Erythropenia 4 74.25 ( 27.67–199.21 ) 74.22 ( 285 ) 73.22 ( 32.06 ) 6.19 ( 4.89 ) Haemolytic uraemic syndrome 4 9.69 ( 3.63–25.83 ) 9.68 ( 31.09 ) 9.67 ( 4.25 ) 3.27 ( 1.98 ) White blood cell disorder 3 6.58 ( 2.12–20.42 ) 6.58 ( 14.17 ) 6.57 ( 2.55 ) 2.72 ( 1.27 ) Gemcitabine combined with Pembrolizumab Anaemia 23 10.4 ( 6.87–15.76 ) 10.1 ( 189.09 ) 10.1 ( 7.13 ) 3.34 ( 2.74 ) Thrombocytopenia 19 14.93 ( 9.46–23.55 ) 14.55 ( 240.2 ) 14.55 ( 9.94 ) 3.86 ( 3.21 ) Neutropenia 18 11.55 ( 7.24–18.45 ) 11.29 ( 169.1 ) 11.28 ( 7.63 ) 3.5 ( 2.83 ) Myelosuppression 3 10.81 ( 3.48–33.62 ) 10.77 ( 26.6 ) 10.77 ( 4.17 ) 3.43 ( 1.98 ) Gemcitabine combined with Nivolumab Thrombocytopenia 9 9.85 ( 5.09–19.04 ) 9.69 ( 70.24 ) 9.69 ( 5.58 ) 3.28 ( 2.35 ) Neutropenia 6 5.34 ( 2.39–11.94 ) 5.29 ( 20.9 ) 5.29 ( 2.7 ) 2.4 ( 1.3 ) Pancytopenia 5 10.96 ( 4.54–26.45 ) 10.86 ( 44.8 ) 10.86 ( 5.2 ) 3.44 ( 2.26 ) Febrile neutropenia 3 5.51 ( 1.77–17.15 ) 5.49 ( 11.01 ) 5.48 ( 2.12 ) 2.46 ( 1.01 ) Gemcitabine combined with Durvalumab Febrile neutropenia 14 15.96 ( 9.41–27.07 ) 15.7 ( 192.92 ) 15.7 ( 10.09 ) 3.97 ( 3.22 ) Thrombocytopenia 13 8.71 ( 5.03–15.06 ) 8.58 ( 87.26 ) 8.58 ( 5.43 ) 3.1 ( 2.32 ) Pancytopenia 11 14.84 ( 8.19–26.91 ) 14.66 ( 140.08 ) 14.65 ( 8.91 ) 3.87 ( 3.03 ) Myelosuppression 6 18.71 ( 8.38–41.77 ) 18.58 ( 99.81 ) 18.57 ( 9.48 ) 4.22 ( 3.12 ) 3.4 Onset time of positive signal Whether in the GEM alone treatment group or the combined treatment groups, the major AEs of cases occurred within the first 30 days (GEM: n = 2,893, 50.8%; GEM combined with cisplatin: n = 523, 55.5%; GEM combined with pembrolizumab: n = 7, 31.8%; GEM combined with nivolumab: n = 14, 87.5%; GEM combined with durvalumab: n = 43, 58.9%) (Fig. 6 ). The Weibull distribution test demonstrated an early failure type for GEM, GEM combined with cisplatin, and GEM combined with durvalumab, indicating a decline in the incidence of AEs over time (Table 6 ). The shape parameter (β) was 0.95 (95%CI = 0.69 ~ 1.22) in the GEM combined with pembrolizumab, indicating that the probability of an AE remained persistent over time. The β was 1.27 (95%CI = 0.91 ~ 1.62) in the GEM combined with nivolumab, suggesting an increase in the incidence of AEs over time. Table 6 Weibull distribution test of TTO analysis Drug Case TTO (days) Weibull distribution Failure type Scale parameter Shape parameter Media(IQR) Min ~ Max α 95% CI β 95% CI Gemcitabine 5800 30(9 ~ 87.25) 1 ~ 980 56.83 55.04 ~ 58.62 0.73 0.71 ~ 0.74 Early failure Gemcitabine combined with Cisplatin 940 24(9 ~ 67) 1 ~ 730 45.84 42.56 ~ 49.13 0.79 0.76 ~ 0.82 Early failure Gemcitabine combined with Pembrolizumab 22 61.5(14 ~ 109.5) 8 ~ 307 86.65 52.96 ~ 120.34 0.95 0.69 ~ 1.22 Random failure Gemcitabine combined with Nivolumab 16 19(19 ~ 28) 12 ~ 126 34.81 22.76 ~ 46.87 1.27 0.91 ~ 1.62 Wear-out failure Gemcitabine combined with Durvalumab 73 23(9–69) 1 ~ 392 43.54 32.97 ~ 54.11 0.84 0.72 ~ 0.96 Early failure 4 Discussion This study conducted an extensive, systematic analysis of AE signals for GEM monotherapy and its combination therapies with cisplatin, pembrolizumab, nivolumab, and durvalumab based on the data from the FAERS database. Findings demonstrate that the blood and lymphatic system disorders represent a common SOC positive signal across all regimens, whereas thrombocytopenia, neoplasm progression, and pneumonitis are identified as common AEs for all treatment groups at the PT level. Moreover, substantial variation is shown in the patterns of AEs’ occurrence across various treatment regimens. This study offers thorough and precise real-world evidence regarding the safety profiles of different treatment regimens, offering an essential data foundation for clinical practice and public health decision-making. Thrombocytopenia is a prevalent, significant hematologic AE of chemotherapy. The pathophysiology is linked to the suppression of bone marrow megakaryocytes, perhaps resulting in peripheral blood platelet counts dropping below 100 × 10⁹/L [ 16 ]. Statistics reveal that treatment-induced thrombocytopenia affects 10%–36% of patients with solid tumors and up to 75% of those with hematologic malignancies [ 17 ]. Subsequent research demonstrates that treatment protocols incorporating GEM or platinum drugs are markedly linked to the risk of thrombocytopenia, with an incidence of 64% in individuals undergoing GEM monotherapy and 56% in those getting platinum-based regimens [ 17 ]. Morabito et al. demonstrated that this AE primarily manifested on days 4–5 of GEM treatment, reaching its zenith during the second week [ 18 ]. The frequency of thrombocytopenia resulting from GEM monotherapy was lower than that associated with combination regimens involving cisplatin, and the occurrence of this AE was directly linked to medication dosage and administration cycles [ 19 , 20 ]. Our study found that the combination of GEM and cisplatin had the highest correlation with thrombocytopenia (ROR = 18.12, 95% CI: 16.22–20.23), corroborating prior findings. Mechanistically, the associated pathophysiological processes are intricate and diverse, largely including the following aspects: (1) direct cytotoxic effects on megakaryocytes and progenitor cells: chemotherapy can impair actively proliferating hematopoietic stem and progenitor cells, which leads to death of megakaryocyte precursors and induces DNA damage; (2) the destruction of the bone marrow microenvironment: chemotherapy agents damage stromal and endothelial cells, modify cytokine signaling pathways, and promote oxidative stress, ultimately compromising hematopoietic stem cell functionality and thrombopoiesis; (3) abnormal regulation of thrombopoietin and compromised megakaryopoiesis: chemotherapy disrupts thrombopoietin production and megakaryocyte sensitivity, hindering platelet recovery; and (4) chemotherapy-associated immune-mediated platelet destruction: specific chemotherapies and immunotherapies (e.g., the ICI nivolumab) may elicit immune responses against platelets, resulting in accelerated platelet destruction through reactive platelet antibodies or mechanisms akin to immune thrombocytopenia [ 21 ]. Immune thrombocytopenia was also observed in the group receiving GEM in conjunction with cisplatin therapy. Therefore, vigilant surveillance of platelet counts is necessary for patients undergoing chemotherapy, particularly those on regimens that include GEM and platinum drugs. Timely targeted treatments based on the previously outlined mechanisms are essential for mitigating bleeding risks and maintaining treatment safety. Pneumonitis related to GEM has been noted in individuals with several malignancies, including pancreatic, gallbladder, breast, ovarian, and lung cancers, and it may result in serious complications but seldom leads to death [ 22 – 29 ]. Previous studies indicate that the incidence of GEM-associated pneumonitis varies from 0.02% to 0.27%, with a heightened incidence observed when GEM is administered in conjunction with other medications [ 29 – 31 ]. Our study demonstrated that, in comparison to GEM monotherapy, the combination of GEM with PD-1/PD-L1 inhibitors markedly elevated the incidence of pneumonitis. Nevertheless, the exact mechanism remains inadequately comprehended. This may be associated with dysregulation of tissue repair due to GEM-induced proinflammatory cytokine release or to hypersensitive pathways shown by eosinophil infiltration in lung parenchyma post-GEM treatment [ 27 , 32 – 34 ]. Additional experimental investigations are required to thoroughly clarify the potential pathophysiology of this unpleasant event. Prior research has established that GEM-based combination therapy markedly enhances survival rates in patients with diverse malignancies, such as biliary tract cancer, pancreatic cancer, urothelial carcinoma, and non-muscle-invasive bladder cancer [ 31 , 35 – 37 ]. However, our study demonstrated that, in comparison to GEM monotherapy, the combination of GEM with nivolumab or durvalumab is linked to an increased risk of neoplasm progression. The mechanics underlying this occurrence are not fully understood, and pertinent research continues to have considerable limitations. Furthermore, our investigation has revealed distinct AEs linked to combination therapies, including autoimmune haemolytic anaemia (GEM + cisplatin), osteomyelitis (GEM + pembrolizumab), pelvic venous thrombosis (GEM + nivolumab), and bacillus infection (GEM + durvalumab). Nonetheless, the processes that govern these distinctive unfavorable reactions are still inadequately comprehended. These findings emphasize that, while progressing combination medicines to improve efficacy, we must equally prioritize mitigating their unique safety concerns. This study also conducted a TTO analysis of AEs and developed a Weibull distribution model to forecast occurrence patterns. Results demonstrate that for all treatment groups, most AEs occurred within the initial month of treatment, highlighting the necessity of early surveillance in detecting and addressing potential AEs. The Weibull distribution model indicated different temporal patterns of AEs’ occurrence in different treatment groups, offering essential time frame benchmarks for monitoring adverse events across various treatment regimens, highlighting the necessity for the creation of personalized, adaptive pharmacological monitoring strategies particular to each combination therapy. Nonetheless, our study still has some limitations. First, the restricted quantity of cases undergoing combination therapy in the FAERS database may affect the outcomes, requiring additional validation through alternative investigations. Second, as the FAERS database is curated by the U.S. Food and Drug Administration, it is devoid of case data from other nations. Moreover, differing levels of emphasis on bad occurrences among various countries and regions may generate bias when assessments are confined to particular populations. Additionally, while this study concentrated on certain medications and their AEs, thus increasing the specificity of the findings, a causal link between the pharmaceuticals and the AEs could not be determined. Therefore, future study should concentrate on the subsequent domains: firstly, extensive multicenter prospective clinical trials are required to corroborate the signals detected in this investigation and to precisely evaluate the incidence rates and risk variables of AEs associated with various combination medication regimens; secondly, data from pharmacovigilance databases in regions like Europe and Asia should be amalgamated to do cross-population and cross-regional comparative studies, thereby improving the generalizability and reliability of study outcomes; thirdly, molecular biology experiments or organoid models could be utilized to examine the mechanisms underlying drug-related AEs; Ultimately, investigating the integration of real-world data with machine learning techniques to develop prediction risk models for drug-related AEs may yield practical instruments for the early clinical identification of high-risk patients and the execution of tailored medication monitoring. 5 Conclusion In conclusion, this study concluded that GEM monotherapy and its combination with cisplatin or PD-1/PD-L1 inhibitors exhibit shared side effects, including thrombocytopenia, pneumonitis, and neoplasm progression. Concurrently, several treatment regimens demonstrate unique safety profiles, including particular immune-related side events noted in the gemcitabine combined with therapy cohort. The findings indicate that clinical application of these regimens necessitates targeted monitoring and preventive methods for adverse events, tailored to the specific therapy combination, with heightened awareness of highly correlated adverse events. This work gives empirical evidence regarding the safety profiles of GEM monotherapy and combination medications, while also providing a theoretical foundation for the formulation of precise risk management techniques and the enhancement of treatment safety for patients. Abbreviations GEM Gemcitabine ICIs immune checkpoint inhibitors AEs adverse events PS primary suspect SOC system organ class PT preferred term ROR reporting odds ratio PRR proportional reporting ratio BCPNN Bayesian confidence propagation neural network MGPS multi-item gamma Poisson shrinker Declarations Ethics Statement Not applicable. Conflict of Interest statement The authors declares that there is no conflict of interest. Funding This research received no specific grant from funding agencies in the public, commercial, or not-for-profit sectors Data Availability Statement The data for this study were sourced from FAERS database (https://www.fda.gov/drugs). Acknowledgments We would like to express our sincere gratitude to all individuals and organizations who supported and assisted us throughout this research. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7907815","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":532546836,"identity":"60fe5f45-55a4-4c39-8cae-cdfc04fcafbe","order_by":0,"name":"Zhineng Zhu","email":"","orcid":"","institution":"Wuhan No.1 Hospital (Traditional Chinese and Western Medicine Hospital of Wuhan), Huazhong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Zhineng","middleName":"","lastName":"Zhu","suffix":""},{"id":532546837,"identity":"ab26d734-55ee-4146-92cf-02b096dbe5e9","order_by":1,"name":"Ying 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07:12:36","extension":"xml","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":181532,"visible":true,"origin":"","legend":"","description":"","filename":"e17bef60a859426eb33ef097d67531c41structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7907815/v1/74bb18b64e985c2596cec0f8.xml"},{"id":94062596,"identity":"4d4dd620-dce4-445a-ad35-8baf54ee7475","added_by":"auto","created_at":"2025-10-22 07:12:36","extension":"html","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":184419,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7907815/v1/4e8a21bdba8972b2cba03bf6.html"},{"id":94062570,"identity":"60a7c3eb-57b1-42e5-85cb-dc9d64b95bd2","added_by":"auto","created_at":"2025-10-22 07:12:35","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1430358,"visible":true,"origin":"","legend":"\u003cp\u003eThe reported time of AEs\u003cstrong\u003e \u003c/strong\u003ein each treatment group. (\u003cstrong\u003eA\u003c/strong\u003e) Gemcitabine. (\u003cstrong\u003eB\u003c/strong\u003e) Gemcitabine combined with Cisplatin. (\u003cstrong\u003eC\u003c/strong\u003e) Gemcitabine combined with Pembrolizumab. (\u003cstrong\u003eD\u003c/strong\u003e) Gemcitabine combined with Nivolumab. (\u003cstrong\u003eE\u003c/strong\u003e) Gemcitabine combined with Durvalumab.\u003c/p\u003e","description":"","filename":"Figure1.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7907815/v1/05d6674c4ce28c539dad4947.jpg"},{"id":94062571,"identity":"5ca4db5a-1017-45ec-8ec0-9300cd06d22f","added_by":"auto","created_at":"2025-10-22 07:12:35","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":4883578,"visible":true,"origin":"","legend":"\u003cp\u003eForest map of SOCs in each treatment group. (\u003cstrong\u003eA\u003c/strong\u003e) Gemcitabine. (\u003cstrong\u003eB\u003c/strong\u003e) Gemcitabine combined with Cisplatin. (\u003cstrong\u003eC\u003c/strong\u003e) Gemcitabine combined with Pembrolizumab. (\u003cstrong\u003eD\u003c/strong\u003e) Gemcitabine combined with Nivolumab. (\u003cstrong\u003eE\u003c/strong\u003e) Gemcitabine combined with Durvalumab.\u003c/p\u003e","description":"","filename":"Figure2.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7907815/v1/d4564ff95e5e126d3f2c194a.jpg"},{"id":94062896,"identity":"0cf5056b-a247-4421-a87a-fcafc965e7c0","added_by":"auto","created_at":"2025-10-22 07:20:35","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2173112,"visible":true,"origin":"","legend":"\u003cp\u003eVenn diagram showing the positive signals at the SOC level in each treatment group. (\u003cstrong\u003eA\u003c/strong\u003e) Gemcitabine. (\u003cstrong\u003eB\u003c/strong\u003e) Gemcitabine combined with Cisplatin. (\u003cstrong\u003eC\u003c/strong\u003e) Gemcitabine combined with Pembrolizumab. (\u003cstrong\u003eD\u003c/strong\u003e) Gemcitabine combined with Nivolumab. (\u003cstrong\u003eE\u003c/strong\u003e) Gemcitabine combined with Durvalumab.\u003c/p\u003e","description":"","filename":"Figure3.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7907815/v1/63d369bf5b0da2fdbff0f994.jpg"},{"id":94063732,"identity":"a2707afb-c099-40ae-b1bd-4bd899d1b6b3","added_by":"auto","created_at":"2025-10-22 07:28:35","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2054455,"visible":true,"origin":"","legend":"\u003cp\u003eVenn diagram showing the positive AEs at the PT level in each treatment group. (\u003cstrong\u003eA\u003c/strong\u003e) Gemcitabine. (\u003cstrong\u003eB\u003c/strong\u003e) Gemcitabine combined with Cisplatin. (\u003cstrong\u003eC\u003c/strong\u003e) Gemcitabine combined with Pembrolizumab. (\u003cstrong\u003eD\u003c/strong\u003e) Gemcitabine combined with Nivolumab. (\u003cstrong\u003eE\u003c/strong\u003e) Gemcitabine combined with Durvalumab.\u003c/p\u003e","description":"","filename":"Figure4.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7907815/v1/44ce8f3af325e238dc5a5a2c.jpg"},{"id":94062573,"identity":"2a413068-bd7e-4b51-bc20-47697b6a7b86","added_by":"auto","created_at":"2025-10-22 07:12:35","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1007836,"visible":true,"origin":"","legend":"\u003cp\u003eThe common positive AEs among five treatment groups.\u003c/p\u003e","description":"","filename":"Figure5.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7907815/v1/2dd48e37f67c96efe6feea2a.jpg"},{"id":94063733,"identity":"9aba400a-5505-4c7b-9d25-20f42be6a609","added_by":"auto","created_at":"2025-10-22 07:28:35","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1795216,"visible":true,"origin":"","legend":"\u003cp\u003eTime-to onset (TTO) of AEs in each treatment group. (\u003cstrong\u003eA\u003c/strong\u003e) Gemcitabine. (\u003cstrong\u003eB\u003c/strong\u003e) Gemcitabine combined with Cisplatin. (\u003cstrong\u003eC\u003c/strong\u003e) Gemcitabine combined with Pembrolizumab. (\u003cstrong\u003eD\u003c/strong\u003e) Gemcitabine combined with Nivolumab. (\u003cstrong\u003eE\u003c/strong\u003e) Gemcitabine combined with Durvalumab.\u003c/p\u003e","description":"","filename":"Figure6.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7907815/v1/2f022073fb95aa2e09af4265.jpg"},{"id":94064793,"identity":"17f167b7-8fc3-4ed7-bf78-7ac711415716","added_by":"auto","created_at":"2025-10-22 07:44:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":16701434,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7907815/v1/a774d9d0-580b-4042-8302-eae44ab4ecdd.pdf"},{"id":94062893,"identity":"313da38c-3d8e-4760-b0f9-7d4bf2077dfe","added_by":"auto","created_at":"2025-10-22 07:20:35","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":21438,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7907815/v1/ccf7e691bf3345e37794cbbb.xlsx"},{"id":94062574,"identity":"b7daf39d-2961-47eb-8c92-4b5c93d0f23e","added_by":"auto","created_at":"2025-10-22 07:12:35","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":84512,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7907815/v1/ee9446dc66fb0d1ad9b74e29.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Risk comparison of adverse reactions among gemcitabine monotherapy, gemcitabine combined with cisplatin, gemcitabine combined with PD-1/PD-L1 inhibitors treatment: insights from the FDA adverse event reporting system database","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eGemcitabine (GEM) is an anticancer agent derived from cytidine nucleosides, extensively utilized in the treatment of multiple malignancies, including pancreatic, bladder, breast, ovarian, and lung cancers, among others [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. It predominantly inhibits nucleotide reductase to obstruct DNA synthesis, resulting in cell cycle arrest and apoptosis [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Nonetheless, in clinical application, the effectiveness of GEM is considerably constrained by factors such as drug resistance and toxicity [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Combination therapy can improve therapeutic efficacy and diminish the likelihood of drug resistance by utilizing various modes of action or signaling pathways, thus reducing necessary dosages and systemic toxicity; therefore, GEM is often utilized alongside other anticancer agents in clinical practice to enhance treatment efficacy [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Prior research has shown that the combination of gemcitabine and cisplatin significantly extends patient survival in the treatment of various malignancies compared to monotherapy with gemcitabine [\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Additionally, GEM can regulate immune responses in the tumor microenvironment, therefore affecting anticancer immune responses [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Numerous clinical trials demonstrate that GEM has synergistic benefits with immune checkpoint inhibitors (ICIs) against cancer cells in comparison to monotherapy and can surmount resistance to ICI treatment [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Principe et al. conducted research indicating that in cases of TGF-β signaling deficiencies, a combination of GEM and anti-PD-1 therapy elicits strong CD8\u003csup\u003e+\u003c/sup\u003e T cell responses and diminishes tumor size, therefore enhancing overall survival in pancreatic cancer patients [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Wang et al. demonstrated that the combination of GEM and anti-PD-L1 therapy (aPDL1-GEM@Gel) markedly inhibited tumor growth in the B16F10 mouse melanoma model, while also promoting CD4\u003csup\u003e+\u003c/sup\u003e and CD8\u003csup\u003e+\u003c/sup\u003e T cell infiltration and eliciting systemic immune responses [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Nevertheless, current research has predominantly concentrated on efficacy, whereas investigations assessing safety continue to exhibit specific shortcomings. Moreover, the safety statistics from current clinical trials may not accurately represent real-world conditions.\u003c/p\u003e\u003cp\u003eThe FAERS database documents all adverse events (AEs) and medication errors reported to the FDA, facilitating the discovery and quantitative analysis of signals that indicate irregularities in drug adverse reaction reports, thereby enabling the identification of correlations between particular medications and specific adverse occurrences [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Therefore, based on the FAERS database, we examined and contrasted the risks of AEs linked to GEM monotherapy and combination therapies (cisplatin, anti-PD-1 inhibitors [pembrolizumab and nivolumab], and anti-PD-L1 inhibitors [durvalumab]), and also investigated the characteristics of these AEs. This study seeks to identify potential safety disparities among treatment regimens, offering real-world data to enable the formulation of more tailored drug strategies and risk assessment processes in clinical practice.\u003c/p\u003e"},{"header":"2 Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Data extraction and processing\u003c/h2\u003e\u003cp\u003eThe data for this study was extracted from the FAERS database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.fda.gov/drugs\u003c/span\u003e\u003cspan address=\"https://www.fda.gov/drugs\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), covering from the first quarter of 2004 to the fourth quarter of 2024, which contained seven datasets: demographic and administrative information (DEMO), drug information (DRUG), adverse drug reaction information (REAC), patient outcomes information (OUTC), reported sources (RPSR), drug therapy start dates and end dates (THER), and indications for drug administration (INDI) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The keywords \u0026ldquo;Gemcitabine,\u0026rdquo; \u0026ldquo;Cisplatin,\u0026rdquo; \u0026ldquo;Pembrolizumab,\u0026rdquo; \u0026ldquo;Nivolumab,\u0026rdquo; and \u0026ldquo;Durvalumab\u0026rdquo; were utilized to retrieve associated AEs. The inclusion criteria for drugs were as follows: (1) GEM was the primary suspect (PS) for suspected drugs; (2) cases treated with GEM (PS) plus cisplatin/pembrolizumab/nivolumab/durvalumab (as a secondary suspect, SS; concomitant drug, C; or interacting drug, I). According to the FAERS database guide, duplicate AE reports were identified and deleted. Specifically, if CASEID matched, the latest FDA_DT was chosen; if CASEID and FDA_DT both matched, the higher PRIMARYID was preferred. Since the drug\u0026rsquo;s names were not standardized in the FAERS database, RxNorm was applied to standardize the drug\u0026rsquo;s names. The drug-related AE signals were standardized and categorized at the system organ class (SOC) and preferred term (PT) levels obtained from the MedDRA 26.0.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Disproportionality analysis\u003c/h2\u003e\u003cp\u003eBased on the classical four-fold table (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), disproportional algorithms, including reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS), were applied to identify and compare correlations between drugs and AEs. The specific calculation formulas and thresholds of each algorithm were displayed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. In our study, a positive signal was considered when the thresholds of the above four algorithms were satisfied simultaneously. The greater the value of the four algorithms, the stronger the signal intensity, which indicates that the stronger the correlation between the drug and the occurrence of AEs.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFour-grid table for signal detection\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTarget adverse drug event\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOther adverse drug event\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSums\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGemcitabine combined with other drugs (Cisplatin/Pembrolizumab/Nivolumab/Durvalumab)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eb\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ea\u0026thinsp;+\u0026thinsp;b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGemcitabine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ec\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ec\u0026thinsp;+\u0026thinsp;d\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSums\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ea\u0026thinsp;+\u0026thinsp;c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eb\u0026thinsp;+\u0026thinsp;d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ea\u0026thinsp;+\u0026thinsp;b\u0026thinsp;+\u0026thinsp;c\u0026thinsp;+\u0026thinsp;d\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eOverview of the main algorithms used for signal detection\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMethod\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEquation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCriteria\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eROR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eROR=\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{\\text{a}\\text{d}}{bc}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003cp\u003eROR 95%CI\u0026thinsp;=\u0026thinsp;e\u003csup\u003eln(ROR)\u0026plusmn;1.96\u003c/sup\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\sqrt{\\frac{1}{a}+\\frac{1}{b}+\\frac{1}{c}+\\frac{1}{d}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ea\u0026thinsp;\u0026ge;\u0026thinsp;3 and 95%CI(lower limit)\u0026thinsp;\u0026gt;\u0026thinsp;1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePRR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePRR=\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{\\text{a}(\\text{c}+\\text{d})}{\\text{c}(\\text{a}+\\text{b})}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003cp\u003ePRR 95%CI\u0026thinsp;=\u0026thinsp;eln(PRR)\u0026thinsp;\u0026plusmn;\u0026thinsp;1.96\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\sqrt{(\\frac{1}{\\text{a}}-\\frac{1}{\\text{a}+\\text{b}}+\\frac{1}{\\text{c}}-\\frac{1}{\\text{c}+\\text{d}})}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003cp\u003eχ2=[(ad-bc)^2](a\u0026thinsp;+\u0026thinsp;b\u0026thinsp;+\u0026thinsp;c\u0026thinsp;+\u0026thinsp;d)/[(a\u0026thinsp;+\u0026thinsp;b)(c\u0026thinsp;+\u0026thinsp;d)(a\u0026thinsp;+\u0026thinsp;c)(b\u0026thinsp;+\u0026thinsp;d)]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ea\u0026thinsp;\u0026ge;\u0026thinsp;3, PRR\u0026thinsp;\u0026ge;\u0026thinsp;2, χ2\u0026thinsp;\u0026ge;\u0026thinsp;4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBCPNN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIC\u0026thinsp;=\u0026thinsp;log\u003csub\u003e2\u003c/sub\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{\\text{a}(\\text{a}+\\text{b}+\\text{c}+\\text{d})}{\\begin{array}{c}(a+b)(a+c)\\\\\\:\\end{array}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003cp\u003eIC\u003csub\u003e025\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;e\u003csup\u003eln(IC)\u0026minus;1.96\u003c/sup\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\sqrt{(\\frac{1}{a}+\\frac{1}{b}+\\frac{1}{c}+\\frac{1}{d})}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIC025\u0026gt;0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMGPS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEBGM=\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{\\text{a}(\\text{a}+\\text{b}+\\text{c}+\\text{d})}{\\begin{array}{c}(a+c)(a+b)\\\\\\:\\end{array}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003cp\u003eEBGM05\u0026thinsp;=\u0026thinsp;e\u003csup\u003eln(EBGM)\u0026plusmn;1.96\u003c/sup\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\sqrt{\\frac{1}{a}+\\frac{1}{b}+\\frac{1}{c}+\\frac{1}{d}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEBGM05\u0026gt;2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003eROR: Reporting odds ratio; PRR: Proportional reporting ratio; BCPNN: Bayesian confidence propagation neural network; MGPS: Multi-item gamma Poisson shrinker; EBGM: Empirical\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003eBayesian ensemble mean; IC: Information component; CI: Confidence interval.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Time-to-onset (TTO) analysis\u003c/h2\u003e\u003cp\u003eTTO was defined as the time interval between the AE start date (EVENT_DT) and the drug start date (START_DT). To further elucidate the temporal feature of drug-related significant AEs, TTO features were evaluated by the median, minima-maxima, quartile, and Weibull shape parameter. In our study, we only considered shape (β) in the Weibull shape parameter. When β\u0026thinsp;\u0026lt;\u0026thinsp;1 and its 95%CI\u0026thinsp;\u0026lt;\u0026thinsp;1, the risk of AEs is deemed to diminish over time (early failure-type curve); if β is approximately equal to 1 and its 95% CI encompasses the value 1, the risk will continue to occur over time (random failure-type curve); and if β\u0026thinsp;\u0026gt;\u0026thinsp;1 and its 95% CI excludes the value 1, the risk is regarded as escalating over time (wear-out failure-type curve).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Statistical analysis\u003c/h2\u003e\u003cp\u003eDescriptive statistical analysis was employed to show a range of characteristic information of AE reports enrolled in our study. All analyses were carried out by R software (version 4.2.1). A P-value below 0.05 was deemed statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Descriptive analysis\u003c/h2\u003e\u003cp\u003eIn the FAERS database, from Q1 2004 to Q4 2024, a total of 20,135 AEs with GEM as PS were collected, 3,647 AEs for GEM combined with cisplatin, 152 AEs for GEM combined with pembrolizumab, 107 AEs for GEM combined with nivolumab, and 391 AEs for GEM combined with durvalumab (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Excepting the GEM combined with pembrolizumab treatment group (male vs. female\u0026thinsp;=\u0026thinsp;26.3% vs. 38.2%), the proportion of the male population was higher than that of the female population in the remaining four groups (GEM: male vs. female\u0026thinsp;=\u0026thinsp;41.0% vs. 37.5%; GEM combined with cisplatin: male vs. female\u0026thinsp;=\u0026thinsp;44.7% vs. 26.9%; GEM combined with nivolumab: male vs. female\u0026thinsp;=\u0026thinsp;54.2% vs. 23.4%; GEM combined with durvalumab: male vs. female\u0026thinsp;=\u0026thinsp;54.0% vs. 41.4%). Excepting missing data, the population using GEM, GEM combined with cisplatin, GEM combined with pembrolizumab, and GEM combined with nivolumab all accounted for the highest proportion in the 18\u0026ndash;64 years group (GEM: 32.8%; GEM combined with cisplatin: 37.3%; GEM combined with pembrolizumab: 39.5%; GEM combined with nivolumab: 44.9%), while the highest proportion in the GEM combined with durvalumab treatment group was in the 65\u0026ndash;85 years group (47.3%). In terms of reporting sources, physicians contributed more reports in the GEM (39.1%), GEM combined with cisplatin (39.8%), and GEM combined with durvalumab (39.1%), while in the remaining groups, other health-professionals contributed more reports (GEM combined with pembrolizumab: 27.0%; GEM combined with nivolumab: 33.6%). In terms of serious outcome, other serious outcomes accounted for the highest proportion in GEM (36.5%), GEM combined with cisplatin (40.0%), and GEM combined with pembrolizumab (39.5%), death for GEM combined with nivolumab (42.1%), and hospitalization for GEM combined with durvalumab (55.2%). For the source of reports, Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e displayed the top 5 countries. Specifically, most of AE reports in GEM, GEM combined with cisplatin, and GEM combined with pembrolizumab were sourced from the United States (29.0%, 17.6%, 34.9%), most AE reports in GEM combined with nivolumab from France (29.0%), and most AE reports in GEM combined with durvalumab from Canada (74.7%).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBaseline characteristics of reports in five treatment groups from the FAERS database\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGemcitabine (N\u0026thinsp;=\u0026thinsp;20,135)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGemcitabine combined with Cisplatin (N\u0026thinsp;=\u0026thinsp;3,647)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGemcitabine combined with Pembrolizumab (N\u0026thinsp;=\u0026thinsp;152)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eGemcitabine combined with Nivolumab (N\u0026thinsp;=\u0026thinsp;107)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGemcitabine combined with Durvalumab (N\u0026thinsp;=\u0026thinsp;391)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7548(37.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e982(26.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e58 (38.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e25 (23.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e162 (41.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8247(41.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1629(44.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e40 (26.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e58 (54.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e211 (54.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnknown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4340(21.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1036(28.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54 (35.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e24 (22.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e18 (4.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e183(0.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23(0.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (1.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e/\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (0.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e125(0.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4(0.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e/\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e/\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e/\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18ཞ64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6597(32.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1359(37.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e60 (39.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e48 (44.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e167 (42.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e65ཞ85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6483(32.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e971(26.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30 (19.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e35 (32.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e185 (47.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnknown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6747(33.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1290(35.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e60 (39.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e24 (22.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e38 (9.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReporter\u0026rsquo;s occupation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConsumer (CN)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3965(19.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e580(15.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31 (20.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18 (16.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e101 (25.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealth-professional (HP)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1719(8.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e403(11.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37 (24.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e25 (23.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e79 (20.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLawyer (LW)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4(0.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1(0.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e/\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e/\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e/\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysician (MD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7880(39.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1453(39.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e40 (26.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e28 (26.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e153 (39.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther health-professional (OT)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5103(25.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1044(28.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41 (27.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e36 (33.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e43 (11.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePharmacist (PH)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e957(4.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e122(3.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (2.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e/\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e14 (3.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegistered Nurse (RN)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2(0.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e/\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e/\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e/\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e/\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnknown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e505(2.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44(1.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e/\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e/\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (0.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerious outcome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDeath (DE)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4417(21.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e788(21.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e40 (26.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e45 (42.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e66 (16.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDisability (DS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e142(0.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20(0.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (0.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e/\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9 (2.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHospitalization (HO)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6191(30.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1026(28.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30 (19.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e24 (22.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e216 (55.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLife-threatening (LT)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1120(5.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e225(6.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14 (9.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3 (2.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7 (1.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther serious outcomes (OT)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7344(36.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1459(40.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e60 (39.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e33 (30.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e70 (17.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRequired intervention (RI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15(0.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2(0.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e/\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e/\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e/\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMissing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e906(4.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e127(3.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (4.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 (1.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e23 (5.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe top 5 countries of reporting sources for five treatment groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCountries\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDrugs\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGemcitabine\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUNITED STATES\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5846 (29.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJAPAN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2202 (10.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFRANCE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2186 (10.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eITALY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1382 (6.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUNITED KINGDOM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1223 (6.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGemcitabine combined with Cisplatin\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUNITED STATES\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e643 (17.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJAPAN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e366 (10.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFRANCE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e361 (9.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUNITED KINGDOM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e279 (7.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eITALY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e271 (7.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGemcitabine combined with Pembrolizumab\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUNITED STATES\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e53 (34.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFRANCE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23 (15.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGERMANY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSPAIN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCHINA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9 (5.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGemcitabine combined with Nivolumab\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFRANCE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e31 (29.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUNITED STATES\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16 (15.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGERMANY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12 (11.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAUSTRIA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 (5.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJAPAN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 (5.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUNITED KINGDOM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 (5.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGemcitabine combined with Durvalumab\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCANADA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e292 (74.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFRANCE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e53 (13.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJAPAN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (1.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKOREA, SOUTH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (1.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSPAIN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (1.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUNITED KINGDOM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (1.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e visualized the number of reports between Q1 2004 and Q4 2024. For the GEM treatment group, the peak was in 2015 (n\u0026thinsp;=\u0026thinsp;1,954). For the GEM combined with cisplatin treatment group, the number of reports was more than 300 from 2016 to 2020, reaching a peak of 345 in 2020. For the GEM combined with pembrolizumab treatment group, the peak was 2018 (n\u0026thinsp;=\u0026thinsp;41), while the number of reports in 2019 was the smallest (n\u0026thinsp;=\u0026thinsp;1). For the GEM combined with nivolumab treatment group, there were two peaks, one in 2018 (n\u0026thinsp;=\u0026thinsp;32) and the other in 2021 (n\u0026thinsp;=\u0026thinsp;25). For the GEM combined with durvalumab treatment group, the peak was in 2020 (n\u0026thinsp;=\u0026thinsp;112).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Signal detection at the SOC level\u003c/h2\u003e\u003cp\u003eAt the SOC level, AEs associated with GEM, GEM combined with cisplatin, GEM combined with pembrolizumab, GEM combined with nivolumab, and GEM combined with durvalumab affected 27, 27, 24, 22, and 21 SOCs, respectively (\u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Through comprehensive analysis, excepting the GEM combined with durvalumab treatment group, the SOC with the highest number of AEs was general disorders and administration site conditions (GEM: n\u0026thinsp;=\u0026thinsp;8,922; GEM combined with cisplatin: n\u0026thinsp;=\u0026thinsp;1,538; GEM combined with pembrolizumab: n\u0026thinsp;=\u0026thinsp;109; GEM combined with nivolumab: n\u0026thinsp;=\u0026thinsp;97). For the GEM combined with durvalumab treatment group, the top 1 SOC was infections and infestations (n\u0026thinsp;=\u0026thinsp;127). For five treatment groups, 3 positive SOC for GEM, 3 positive SOC for GEM combined with cisplatin, 3 positive SOC for GEM combined with pembrolizumab, 2 positive SOC for GEM combined with nivolumab, and 3 positive SOC for GEM combined with durvalumab were identified (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The blood and lymphatic system disorders was the positive signal in all treatment groups [GEM: ROR (95%CI)\u0026thinsp;=\u0026thinsp;8.23 (8.04\u0026ndash;8.44); GEM combined with cisplatin: ROR (95%CI)\u0026thinsp;=\u0026thinsp;9.64 (9.12\u0026ndash;10.19); GEM combined with pembrolizumab: ROR (95%CI)\u0026thinsp;=\u0026thinsp;6.88 (5.42\u0026ndash;8.73); GEM combined with nivolumab: ROR (95%CI)\u0026thinsp;=\u0026thinsp;4.4 (3.14\u0026ndash;6.18); GEM combined with durvalumab: ROR (95%CI)\u0026thinsp;=\u0026thinsp;4.84 (3.75\u0026ndash;6.24)].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Signal detection at the PT level\u003c/h2\u003e\u003cp\u003eAt the PT level, a total of 574 positive AEs for GEM, 245 positive AEs for GEM combined with cisplatin, 38 positive AEs for GEM combined with pembrolizumab, 39 positive AEs for GEM combined with nivolumab, and 57 positive AEs for GEM combined with durvalumab were identified (\u003cb\u003eSupplementary Table\u0026nbsp;2\u003c/b\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). After integrating, three common AEs among five treatment groups were found: thrombocytopenia, neoplasm progression, and pneumonitis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Among these AEs, thrombocytopenia exhibited the strongest correlation with GEM combined with cisplatin [ROR (95%CI): GEM vs. GEM combined with cisplatin vs. GEM combined with pembrolizumab vs. GEM combined with nivolumab vs. GEM combined with durvalumab\u0026thinsp;=\u0026thinsp;12.81 (12.14\u0026ndash;13.52) vs. 18.12 (16.22\u0026ndash;20.23) vs. 14.93 (9.46\u0026ndash;23.55) vs. 9.85 (5.09\u0026ndash;19.04) vs. 8.71 (5.03\u0026ndash;15.06)]. The neoplasm progression showed the highest association with GEM combined with durvalumab [ROR (95%CI): GEM vs. GEM combined with cisplatin vs. GEM combined with pembrolizumab vs. GEM combined with nivolumab vs. GEM combined with durvalumab\u0026thinsp;=\u0026thinsp;14.5 (13.29\u0026ndash;15.81) vs. 12.02 (9.56\u0026ndash;15.12) vs. 9.23 (3.46\u0026ndash;24.67) vs. 22.9 (10.86\u0026ndash;48.3) vs. 28.19 (16.62\u0026ndash;47.83)]. The pneumonitis was the most relevant to GEM combined with durvalumab [ROR (95%CI): GEM vs. GEM combined with cisplatin vs. GEM combined with pembrolizumab vs. GEM combined with nivolumab vs. GEM combined with durvalumab\u0026thinsp;=\u0026thinsp;11.34 (10.09\u0026ndash;12.74) vs. 6.21 (4.25\u0026ndash;9.06) vs. 19.77 (8.85\u0026ndash;44.15) vs. 13.85 (4.45\u0026ndash;43.11) vs. 31.41 (17.32\u0026ndash;56.95)]. Through comparing, we found some AEs were positive signals in the combination groups but not in the GEM treatment group, such as autoimmune haemolytic anaemia [GEM combined with cisplatin: ROR (95%CI)\u0026thinsp;=\u0026thinsp;9.38 (3.9-22.56)], osteomyelitis [GEM combined with pembrolizumab: ROR (95%CI)\u0026thinsp;=\u0026thinsp;13.81 (4.44\u0026ndash;42.92)], pelvic venous thrombosis [GEM combined with nivolumab: ROR (95%CI)\u0026thinsp;=\u0026thinsp;326.25 (121.79-873.97)], bacillus infection [GEM combined with durvalumab: ROR (95%CI)\u0026thinsp;=\u0026thinsp;353.22 (113.34-1100.78)].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn blood and lymphatic system disorders, 38 AEs for GEM, 28 AEs for GEM combined with cisplatin, 4 AEs for GEM combined with pembrolizumab, 4 AEs for GEM combined with nivolumab, and 4 AEs for GEM combined with durvalumab were identified (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). After analyzing data, we found the AE species of GEM contained all the AEs of each combination group. Although the number of AEs in the combination groups decreased, the risk increased, such as myelosuppression [ROR(95%CI): GEM vs. GEM combined with cisplatin vs. GEM combined with pembrolizumab vs. GEM combined with durvalumab\u0026thinsp;=\u0026thinsp;8.98 (7.83\u0026ndash;10.29) vs. 19.86 (15.88\u0026ndash;24.82) vs. 10.81 (3.48\u0026ndash;33.62) vs. 18.71 (8.38\u0026ndash;41.77)], pancytopenia [ROR(95%CI): GEM vs. GEM combined with cisplatin vs. GEM combined with nivolumab vs. GEM combined with durvalumab\u0026thinsp;=\u0026thinsp;8.06 (7.33\u0026ndash;8.86) vs. 10.62 (8.7-12.98) vs. 10.96 (4.54\u0026ndash;26.45) vs. 14.84 (8.19\u0026ndash;26.91)], and so on. Additionally, we also found autoimmune haemolytic anaemia, immune thrombocytopenia, normocytic anaemia, and white blood cell disorder were positive signals in the GEM combined with cisplatin treatment group, but not in the GEM treatment group.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe single strength of blood and lymphatic system disorders-related AEs in each treatment group at the PT level\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTreatment Group\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePT\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eROR(95%Cl)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePRR(Chi-square)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEBGM(EBGM05)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eIC(IC025)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"37\" rowspan=\"38\"\u003e\u003cp\u003eGemcitabine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThrombocytopenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1368\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e12.81 ( 12.14\u0026ndash;13.52 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e12.54 ( 14357.99 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e12.38 ( 11.84 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.63 ( 3.55 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeutropenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.98 ( 7.5\u0026ndash;8.48 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.86 ( 6253.87 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e7.8 ( 7.41 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.96 ( 2.87 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnaemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1035\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.47 ( 5.15\u0026ndash;5.82 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.4 ( 3697.3 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e5.37 ( 5.1 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.43 ( 2.33 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThrombotic microangiopathy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e636\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e75.79 ( 69.87\u0026ndash;82.21 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e74.99 ( 42890.2 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e69.34 ( 64.78 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e6.12 ( 6 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLeukopenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e442\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.02 ( 8.21\u0026ndash;9.91 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e8.96 ( 3099.69 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e8.89 ( 8.21 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.15 ( 3.01 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePancytopenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e435\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.06 ( 7.33\u0026ndash;8.86 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e8.01 ( 2646.59 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e7.95 ( 7.34 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.99 ( 2.85 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFebrile neutropenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e423\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.58 ( 5.98\u0026ndash;7.25 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e6.54 ( 1974.73 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6.5 ( 6 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.7 ( 2.56 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHaemolytic uraemic syndrome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e292\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e137.41 ( 121.47\u0026ndash;155.45 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e136.75 ( 34190.15 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e118.95 ( 107.29 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e6.89 ( 6.71 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBone marrow failure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e225\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.7 ( 9.38\u0026ndash;12.21 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10.67 ( 1949.18 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10.56 ( 9.45 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.4 ( 3.21 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMyelosuppression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e209\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.98 ( 7.83\u0026ndash;10.29 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e8.95 ( 1461.79 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e8.87 ( 7.91 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.15 ( 2.95 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHaematotoxicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e198\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e24.14 ( 20.96\u0026ndash;27.8 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e24.06 ( 4263.72 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e23.46 ( 20.85 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4.55 ( 4.34 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDisseminated intravascular coagulation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.31 ( 6.94\u0026ndash;9.96 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e8.3 ( 756.78 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e8.23 ( 7.07 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.04 ( 2.78 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThrombocytosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e31.53 ( 25.99\u0026ndash;38.23 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e31.47 ( 3050.98 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e30.45 ( 25.91 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4.93 ( 4.65 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThrombotic thrombocytopenic purpura\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e28.82 ( 23.62\u0026ndash;35.18 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e28.78 ( 2598.77 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e27.92 ( 23.63 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4.8 ( 4.51 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHaemolytic anaemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.33 ( 7.51\u0026ndash;11.58 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e9.31 ( 609.82 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e9.23 ( 7.7 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.21 ( 2.89 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLeukocytosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.53 ( 2.76\u0026ndash;4.53 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.53 ( 113.85 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.52 ( 2.86 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.82 ( 1.45 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCytopenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.54 ( 4.29\u0026ndash;7.16 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.54 ( 218.17 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e5.51 ( 4.45 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.46 ( 2.09 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAgranulocytosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.77 ( 2.09\u0026ndash;3.66 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.76 ( 55.05 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.76 ( 2.18 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.46 ( 1.06 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAtypical haemolytic uraemic syndrome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e64.26 ( 47.49\u0026ndash;86.96 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e64.22 ( 2615.18 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e60.03 ( 46.61 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e5.91 ( 5.47 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLymphopenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.1 ( 2.29\u0026ndash;4.18 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.09 ( 60.76 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.09 ( 2.4 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.63 ( 1.19 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicroangiopathic haemolytic anaemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e49.41 ( 35.49\u0026ndash;68.79 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e49.38 ( 1663.18 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e46.88 ( 35.54 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e5.55 ( 5.07 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHaemolysis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.42 ( 3.15\u0026ndash;6.19 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.42 ( 89.42 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.4 ( 3.32 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.14 ( 1.65 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFebrile bone marrow aplasia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.26 ( 5.04\u0026ndash;10.47 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.26 ( 155.34 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e7.21 ( 5.31 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.85 ( 2.32 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBlood disorder\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.97 ( 1.99\u0026ndash;4.44 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.97 ( 31.32 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.97 ( 2.12 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.57 ( 0.99 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eErythropenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e73.32 ( 47.48\u0026ndash;113.22 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e73.29 ( 1451.38 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e67.88 ( 47.19 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e6.08 ( 5.46 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormochromic normocytic anaemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.2 ( 3.95\u0026ndash;9.73 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e6.2 ( 82.26 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6.16 ( 4.22 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.62 ( 1.98 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBicytopenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.98 ( 6.98\u0026ndash;17.26 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10.97 ( 170.17 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10.85 ( 7.43 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.44 ( 2.79 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSplenic infarction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.9 ( 6.14\u0026ndash;15.97 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e9.9 ( 134.56 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e9.8 ( 6.57 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.29 ( 2.61 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePlatelet toxicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e138.47 ( 73.41\u0026ndash;261.18 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e138.44 ( 1302.04 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e120.23 ( 70.7 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e6.91 ( 6.02 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnaemia macrocytic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.79 ( 1.89\u0026ndash;7.59 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.79 ( 16.37 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.78 ( 2.11 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.92 ( 0.95 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThrombocytopenic purpura\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.97 ( 2.37\u0026ndash;10.45 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.97 ( 22.09 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.95 ( 2.66 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.31 ( 1.28 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCoombs negative haemolytic anaemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e26.65 ( 10.95\u0026ndash;64.87 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e26.65 ( 119.92 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e25.92 ( 12.32 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4.7 ( 3.5 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHilar lymphadenopathy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.64 ( 1.74\u0026ndash;12.4 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.64 ( 11.37 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.62 ( 2.03 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.21 ( 0.91 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIntravascular haemolysis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.12 ( 2.66\u0026ndash;19.05 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.12 ( 20.88 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e7.07 ( 3.11 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.82 ( 1.53 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePernicious anaemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.36 ( 2.38\u0026ndash;17 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e6.36 ( 17.94 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6.32 ( 2.78 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.66 ( 1.36 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnaemia of malignant disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.83 ( 3.47\u0026ndash;33.81 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10.83 ( 26.45 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10.71 ( 4.13 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.42 ( 1.97 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHypersplenism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.05 ( 1.95\u0026ndash;18.85 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e6.05 ( 12.58 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6.02 ( 2.33 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.59 ( 1.14 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSplenic vein thrombosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.77 ( 1.85\u0026ndash;17.96 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.77 ( 11.76 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e5.74 ( 2.22 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.52 ( 1.07 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"27\" rowspan=\"28\"\u003e\u003cp\u003eGemcitabine combined with Cisplatin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThrombocytopenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e326\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18.12 ( 16.22\u0026ndash;20.23 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e17.56 ( 5084.49 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e17.51 ( 15.96 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4.13 ( 3.97 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeutropenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e207\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.29 ( 8.09\u0026ndash;10.66 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e9.11 ( 1496.34 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e9.1 ( 8.11 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.19 ( 2.98 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnaemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e179\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.6 ( 4.83\u0026ndash;6.49 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.51 ( 663.1 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e5.51 ( 4.87 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.46 ( 2.25 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFebrile neutropenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e116\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.71 ( 8.92\u0026ndash;12.87 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10.6 ( 1007.76 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10.58 ( 9.08 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.4 ( 3.13 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePancytopenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.62 ( 8.7\u0026ndash;12.98 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10.53 ( 835.78 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10.51 ( 8.89 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.39 ( 3.1 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLeukopenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.72 ( 8.7\u0026ndash;13.21 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10.63 ( 775.98 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10.62 ( 8.91 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.41 ( 3.1 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMyelosuppression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19.86 ( 15.88\u0026ndash;24.82 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e19.71 ( 1380.76 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e19.64 ( 16.3 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4.3 ( 3.97 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBone marrow failure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e12.6 ( 9.4\u0026ndash;16.9 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e12.55 ( 477.45 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e12.52 ( 9.8 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.65 ( 3.22 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThrombotic microangiopathy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e28.73 ( 21.35\u0026ndash;38.66 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e28.6 ( 1166.11 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e28.46 ( 22.2 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4.83 ( 4.4 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHaematotoxicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e24.8 ( 17.78\u0026ndash;34.58 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e24.72 ( 792.92 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e24.61 ( 18.63 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4.62 ( 4.14 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThrombocytosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e35.75 ( 23.27\u0026ndash;54.94 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e35.68 ( 703.24 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e35.45 ( 24.75 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e5.15 ( 4.53 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAtypical haemolytic uraemic syndrome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e129.86 ( 79.06\u0026ndash;213.31 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e129.66 ( 1994.64 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e126.63 ( 83.6 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e6.98 ( 6.28 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAgranulocytosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.02 ( 3.03\u0026ndash;8.33 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.02 ( 48.19 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e5.01 ( 3.28 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.33 ( 1.6 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLeukocytosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.65 ( 2.75\u0026ndash;7.86 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.64 ( 40.01 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.64 ( 2.99 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.21 ( 1.47 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHaemolytic anaemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.26 ( 5.48\u0026ndash;15.65 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e9.25 ( 102.85 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e9.24 ( 5.95 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.21 ( 2.46 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSplenic infarction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e44.9 ( 26\u0026ndash;77.52 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e44.84 ( 552.63 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e44.48 ( 28.16 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e5.48 ( 4.7 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDisseminated intravascular coagulation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.34 ( 3.1\u0026ndash;9.21 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.34 ( 45.79 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e5.33 ( 3.38 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.42 ( 1.64 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCytopenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.66 ( 3.78\u0026ndash;11.74 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e6.66 ( 57.63 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6.65 ( 4.14 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.73 ( 1.93 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThrombotic thrombocytopenic purpura\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14.96 ( 7.77\u0026ndash;28.79 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e14.95 ( 116.81 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e14.91 ( 8.62 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.9 ( 2.98 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicroangiopathic haemolytic anaemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e45.5 ( 20.37\u0026ndash;101.64 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e45.47 ( 258.78 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e45.1 ( 23.02 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e5.5 ( 4.4 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFebrile bone marrow aplasia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.39 ( 3.07\u0026ndash;17.77 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.39 ( 27.57 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e7.38 ( 3.54 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.88 ( 1.7 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAutoimmune haemolytic anaemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.38 ( 3.9\u0026ndash;22.56 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e9.38 ( 37.36 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e9.36 ( 4.49 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.23 ( 2.05 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBicytopenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e17 ( 7.07\u0026ndash;40.92 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e17 ( 75.04 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e16.95 ( 8.13 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4.08 ( 2.9 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eImmune thrombocytopenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.89 ( 3.28\u0026ndash;18.98 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.89 ( 30.04 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e7.88 ( 3.78 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.98 ( 1.8 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormocytic anaemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18.82 ( 7.05\u0026ndash;50.24 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e18.81 ( 67.24 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e18.75 ( 8.25 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4.23 ( 2.94 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eErythropenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e74.25 ( 27.67\u0026ndash;199.21 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e74.22 ( 285 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e73.22 ( 32.06 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e6.19 ( 4.89 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHaemolytic uraemic syndrome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.69 ( 3.63\u0026ndash;25.83 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e9.68 ( 31.09 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e9.67 ( 4.25 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.27 ( 1.98 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWhite blood cell disorder\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.58 ( 2.12\u0026ndash;20.42 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e6.58 ( 14.17 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6.57 ( 2.55 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.72 ( 1.27 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eGemcitabine combined with Pembrolizumab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnaemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.4 ( 6.87\u0026ndash;15.76 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10.1 ( 189.09 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10.1 ( 7.13 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.34 ( 2.74 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThrombocytopenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14.93 ( 9.46\u0026ndash;23.55 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e14.55 ( 240.2 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e14.55 ( 9.94 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.86 ( 3.21 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeutropenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e11.55 ( 7.24\u0026ndash;18.45 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e11.29 ( 169.1 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e11.28 ( 7.63 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.5 ( 2.83 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMyelosuppression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.81 ( 3.48\u0026ndash;33.62 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10.77 ( 26.6 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10.77 ( 4.17 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.43 ( 1.98 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eGemcitabine combined with Nivolumab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThrombocytopenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.85 ( 5.09\u0026ndash;19.04 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e9.69 ( 70.24 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e9.69 ( 5.58 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.28 ( 2.35 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeutropenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.34 ( 2.39\u0026ndash;11.94 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.29 ( 20.9 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e5.29 ( 2.7 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.4 ( 1.3 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePancytopenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.96 ( 4.54\u0026ndash;26.45 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10.86 ( 44.8 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10.86 ( 5.2 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.44 ( 2.26 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFebrile neutropenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.51 ( 1.77\u0026ndash;17.15 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.49 ( 11.01 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e5.48 ( 2.12 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.46 ( 1.01 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eGemcitabine combined with Durvalumab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFebrile neutropenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e15.96 ( 9.41\u0026ndash;27.07 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e15.7 ( 192.92 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e15.7 ( 10.09 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.97 ( 3.22 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThrombocytopenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.71 ( 5.03\u0026ndash;15.06 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e8.58 ( 87.26 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e8.58 ( 5.43 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.1 ( 2.32 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePancytopenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14.84 ( 8.19\u0026ndash;26.91 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e14.66 ( 140.08 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e14.65 ( 8.91 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.87 ( 3.03 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMyelosuppression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18.71 ( 8.38\u0026ndash;41.77 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e18.58 ( 99.81 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e18.57 ( 9.48 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4.22 ( 3.12 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Onset time of positive signal\u003c/h2\u003e\u003cp\u003eWhether in the GEM alone treatment group or the combined treatment groups, the major AEs of cases occurred within the first 30 days (GEM: n\u0026thinsp;=\u0026thinsp;2,893, 50.8%; GEM combined with cisplatin: n\u0026thinsp;=\u0026thinsp;523, 55.5%; GEM combined with pembrolizumab: n\u0026thinsp;=\u0026thinsp;7, 31.8%; GEM combined with nivolumab: n\u0026thinsp;=\u0026thinsp;14, 87.5%; GEM combined with durvalumab: n\u0026thinsp;=\u0026thinsp;43, 58.9%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The Weibull distribution test demonstrated an early failure type for GEM, GEM combined with cisplatin, and GEM combined with durvalumab, indicating a decline in the incidence of AEs over time (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The shape parameter (β) was 0.95 (95%CI\u0026thinsp;=\u0026thinsp;0.69\u0026thinsp;~\u0026thinsp;1.22) in the GEM combined with pembrolizumab, indicating that the probability of an AE remained persistent over time. The β was 1.27 (95%CI\u0026thinsp;=\u0026thinsp;0.91\u0026thinsp;~\u0026thinsp;1.62) in the GEM combined with nivolumab, suggesting an increase in the incidence of AEs over time.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eWeibull distribution test of TTO analysis\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eDrug\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eCase\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c4\" namest=\"c3\" rowspan=\"2\"\u003e\u003cp\u003eTTO (days)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e\u003cp\u003eWeibull distribution\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eFailure type\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eScale parameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003eShape parameter\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMedia(IQR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMin\u0026thinsp;~\u0026thinsp;Max\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eα\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eβ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGemcitabine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5800\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30(9\u0026thinsp;~\u0026thinsp;87.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u0026thinsp;~\u0026thinsp;980\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e56.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e55.04\u0026thinsp;~\u0026thinsp;58.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.71\u0026thinsp;~\u0026thinsp;0.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eEarly failure\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGemcitabine combined with Cisplatin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e940\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24(9\u0026thinsp;~\u0026thinsp;67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u0026thinsp;~\u0026thinsp;730\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e45.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e42.56\u0026thinsp;~\u0026thinsp;49.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.76\u0026thinsp;~\u0026thinsp;0.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eEarly failure\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGemcitabine combined with Pembrolizumab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e61.5(14\u0026thinsp;~\u0026thinsp;109.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8\u0026thinsp;~\u0026thinsp;307\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e86.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e52.96\u0026thinsp;~\u0026thinsp;120.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.69\u0026thinsp;~\u0026thinsp;1.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eRandom failure\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGemcitabine combined with Nivolumab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19(19\u0026thinsp;~\u0026thinsp;28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12\u0026thinsp;~\u0026thinsp;126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e34.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e22.76\u0026thinsp;~\u0026thinsp;46.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.91\u0026thinsp;~\u0026thinsp;1.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWear-out failure\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGemcitabine combined with Durvalumab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23(9\u0026ndash;69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u0026thinsp;~\u0026thinsp;392\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e43.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e32.97\u0026thinsp;~\u0026thinsp;54.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.72\u0026thinsp;~\u0026thinsp;0.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eEarly failure\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThis study conducted an extensive, systematic analysis of AE signals for GEM monotherapy and its combination therapies with cisplatin, pembrolizumab, nivolumab, and durvalumab based on the data from the FAERS database. Findings demonstrate that the blood and lymphatic system disorders represent a common SOC positive signal across all regimens, whereas thrombocytopenia, neoplasm progression, and pneumonitis are identified as common AEs for all treatment groups at the PT level. Moreover, substantial variation is shown in the patterns of AEs\u0026rsquo; occurrence across various treatment regimens. This study offers thorough and precise real-world evidence regarding the safety profiles of different treatment regimens, offering an essential data foundation for clinical practice and public health decision-making.\u003c/p\u003e\u003cp\u003eThrombocytopenia is a prevalent, significant hematologic AE of chemotherapy. The pathophysiology is linked to the suppression of bone marrow megakaryocytes, perhaps resulting in peripheral blood platelet counts dropping below 100 \u0026times; 10⁹/L [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Statistics reveal that treatment-induced thrombocytopenia affects 10%\u0026ndash;36% of patients with solid tumors and up to 75% of those with hematologic malignancies [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Subsequent research demonstrates that treatment protocols incorporating GEM or platinum drugs are markedly linked to the risk of thrombocytopenia, with an incidence of 64% in individuals undergoing GEM monotherapy and 56% in those getting platinum-based regimens [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Morabito et al. demonstrated that this AE primarily manifested on days 4\u0026ndash;5 of GEM treatment, reaching its zenith during the second week [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The frequency of thrombocytopenia resulting from GEM monotherapy was lower than that associated with combination regimens involving cisplatin, and the occurrence of this AE was directly linked to medication dosage and administration cycles [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Our study found that the combination of GEM and cisplatin had the highest correlation with thrombocytopenia (ROR\u0026thinsp;=\u0026thinsp;18.12, 95% CI: 16.22\u0026ndash;20.23), corroborating prior findings. Mechanistically, the associated pathophysiological processes are intricate and diverse, largely including the following aspects: (1) direct cytotoxic effects on megakaryocytes and progenitor cells: chemotherapy can impair actively proliferating hematopoietic stem and progenitor cells, which leads to death of megakaryocyte precursors and induces DNA damage; (2) the destruction of the bone marrow microenvironment: chemotherapy agents damage stromal and endothelial cells, modify cytokine signaling pathways, and promote oxidative stress, ultimately compromising hematopoietic stem cell functionality and thrombopoiesis; (3) abnormal regulation of thrombopoietin and compromised megakaryopoiesis: chemotherapy disrupts thrombopoietin production and megakaryocyte sensitivity, hindering platelet recovery; and (4) chemotherapy-associated immune-mediated platelet destruction: specific chemotherapies and immunotherapies (e.g., the ICI nivolumab) may elicit immune responses against platelets, resulting in accelerated platelet destruction through reactive platelet antibodies or mechanisms akin to immune thrombocytopenia [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Immune thrombocytopenia was also observed in the group receiving GEM in conjunction with cisplatin therapy. Therefore, vigilant surveillance of platelet counts is necessary for patients undergoing chemotherapy, particularly those on regimens that include GEM and platinum drugs. Timely targeted treatments based on the previously outlined mechanisms are essential for mitigating bleeding risks and maintaining treatment safety.\u003c/p\u003e\u003cp\u003ePneumonitis related to GEM has been noted in individuals with several malignancies, including pancreatic, gallbladder, breast, ovarian, and lung cancers, and it may result in serious complications but seldom leads to death [\u003cspan additionalcitationids=\"CR23 CR24 CR25 CR26 CR27 CR28\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Previous studies indicate that the incidence of GEM-associated pneumonitis varies from 0.02% to 0.27%, with a heightened incidence observed when GEM is administered in conjunction with other medications [\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Our study demonstrated that, in comparison to GEM monotherapy, the combination of GEM with PD-1/PD-L1 inhibitors markedly elevated the incidence of pneumonitis. Nevertheless, the exact mechanism remains inadequately comprehended. This may be associated with dysregulation of tissue repair due to GEM-induced proinflammatory cytokine release or to hypersensitive pathways shown by eosinophil infiltration in lung parenchyma post-GEM treatment [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Additional experimental investigations are required to thoroughly clarify the potential pathophysiology of this unpleasant event.\u003c/p\u003e\u003cp\u003ePrior research has established that GEM-based combination therapy markedly enhances survival rates in patients with diverse malignancies, such as biliary tract cancer, pancreatic cancer, urothelial carcinoma, and non-muscle-invasive bladder cancer [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. However, our study demonstrated that, in comparison to GEM monotherapy, the combination of GEM with nivolumab or durvalumab is linked to an increased risk of neoplasm progression. The mechanics underlying this occurrence are not fully understood, and pertinent research continues to have considerable limitations. Furthermore, our investigation has revealed distinct AEs linked to combination therapies, including autoimmune haemolytic anaemia (GEM\u0026thinsp;+\u0026thinsp;cisplatin), osteomyelitis (GEM\u0026thinsp;+\u0026thinsp;pembrolizumab), pelvic venous thrombosis (GEM\u0026thinsp;+\u0026thinsp;nivolumab), and bacillus infection (GEM\u0026thinsp;+\u0026thinsp;durvalumab). Nonetheless, the processes that govern these distinctive unfavorable reactions are still inadequately comprehended. These findings emphasize that, while progressing combination medicines to improve efficacy, we must equally prioritize mitigating their unique safety concerns.\u003c/p\u003e\u003cp\u003eThis study also conducted a TTO analysis of AEs and developed a Weibull distribution model to forecast occurrence patterns. Results demonstrate that for all treatment groups, most AEs occurred within the initial month of treatment, highlighting the necessity of early surveillance in detecting and addressing potential AEs. The Weibull distribution model indicated different temporal patterns of AEs\u0026rsquo; occurrence in different treatment groups, offering essential time frame benchmarks for monitoring adverse events across various treatment regimens, highlighting the necessity for the creation of personalized, adaptive pharmacological monitoring strategies particular to each combination therapy.\u003c/p\u003e\u003cp\u003eNonetheless, our study still has some limitations. First, the restricted quantity of cases undergoing combination therapy in the FAERS database may affect the outcomes, requiring additional validation through alternative investigations. Second, as the FAERS database is curated by the U.S. Food and Drug Administration, it is devoid of case data from other nations. Moreover, differing levels of emphasis on bad occurrences among various countries and regions may generate bias when assessments are confined to particular populations. Additionally, while this study concentrated on certain medications and their AEs, thus increasing the specificity of the findings, a causal link between the pharmaceuticals and the AEs could not be determined. Therefore, future study should concentrate on the subsequent domains: firstly, extensive multicenter prospective clinical trials are required to corroborate the signals detected in this investigation and to precisely evaluate the incidence rates and risk variables of AEs associated with various combination medication regimens; secondly, data from pharmacovigilance databases in regions like Europe and Asia should be amalgamated to do cross-population and cross-regional comparative studies, thereby improving the generalizability and reliability of study outcomes; thirdly, molecular biology experiments or organoid models could be utilized to examine the mechanisms underlying drug-related AEs; Ultimately, investigating the integration of real-world data with machine learning techniques to develop prediction risk models for drug-related AEs may yield practical instruments for the early clinical identification of high-risk patients and the execution of tailored medication monitoring.\u003c/p\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eIn conclusion, this study concluded that GEM monotherapy and its combination with cisplatin or PD-1/PD-L1 inhibitors exhibit shared side effects, including thrombocytopenia, pneumonitis, and neoplasm progression. Concurrently, several treatment regimens demonstrate unique safety profiles, including particular immune-related side events noted in the gemcitabine combined with therapy cohort. The findings indicate that clinical application of these regimens necessitates targeted monitoring and preventive methods for adverse events, tailored to the specific therapy combination, with heightened awareness of highly correlated adverse events. This work gives empirical evidence regarding the safety profiles of GEM monotherapy and combination medications, while also providing a theoretical foundation for the formulation of precise risk management techniques and the enhancement of treatment safety for patients.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eGEM\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eGemcitabine\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eICIs\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eimmune checkpoint inhibitors\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAEs\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eadverse events\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eprimary suspect\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSOC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003esystem organ class\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003epreferred term\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eROR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ereporting odds ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePRR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eproportional reporting ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBCPNN\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBayesian confidence propagation neural network\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMGPS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003emulti-item gamma Poisson shrinker\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declares that there is no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from funding agencies in the public, commercial, or not-for-profit sectors\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data for this study were sourced from FAERS database (https://www.fda.gov/drugs).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to express our sincere gratitude to all individuals and organizations who supported and assisted us throughout this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZNZ and JDY: Conception and design; ZNZ and YS: Collection and assembly of data; LL and GFZ: Data analysis and interpretation; ZNZ: Writing-original draft; All authors: Writing-review and editing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBeutel AK, Halbrook CJ: \u003cstrong\u003eBarriers and opportunities for 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\u003c/em\u003e2025.\u003c/li\u003e\n\u003cli\u003eZaurito P, Scilipoti P, Montorsi F, Briganti A, Moschini M: \u003cstrong\u003eIntravesical chemotherapy combination treatments for BCG-unresponsive nonmuscle invasive bladder cancer\u003c/strong\u003e. \u003cem\u003eCurr Opin Urol \u003c/em\u003e2025.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Gemcitabine, Cisplatin, Pembrolizumab, Nivolumab, Durvalumab, Adverse event, FAERS","lastPublishedDoi":"10.21203/rs.3.rs-7907815/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7907815/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground \u003c/strong\u003eAlthough gemcitabine (GEM) has long been the standard treatment for cancer, its combination with other drugs has shown better therapeutic effects. Therefore, our study sought to evaluate and compare the risk of adverse events (AEs) with GEM, GEM combined with cisplatin, GEM combined with PD-1 inhibitors (pembrolizumab and nivolumab), and GEM combined with the PD-L1 inhibitor (durvalumab) treatment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod \u003c/strong\u003eBased on the data extracted from the FAERS database from Q1 2004 to Q4 2024, including GEM as the primary suspected (PS) drug and GEM as PS plus cisplatin/pembrolizumab/nivolumab/durvalumab as a secondary suspect (SS), concomitant drug (C), or interacting drug (I), the risk of AEs was investigated through reporting odds ratio (ROR), proportional reporting ratio (PRR), bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS). Furthermore, time-to-onset (TTO) analysis was carried out to further understand the pattern of AE occurrence.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults \u003c/strong\u003eBetween\u003cstrong\u003e \u003c/strong\u003eQ1 2004 and Q4 2024, a total of 20,135 GEM-related, 3,647 GEM combined with cisplatin-related, 152 GEM combined with pembrolizumab-related, 107 GEM combined with nivolumab-related, and 391 GEM combined with durvalumab-related AEs were collected. At the system organ categories (SOC) level, blood and lymphatic system disorders was the common positive SOC for five treatment groups. At the preferred terms (PT) level, there were three common AEs among five treatment groups, namely thrombocytopenia, neoplasm progression, and pneumonitis. Among the three AEs, the risk of thrombocytopenia was the highest in the GEMcombined with cisplatin treatment group [ROR(95%CI) = 18.12 (16.22-20.23)], and the risk of neoplasm progression and pneumonitis was the highest in the GEMcombined with durvalumab [neoplasm progression: ROR(95%CI) = 28.19 (16.62-47.83); pneumonitis: ROR(95%CI) = 31.41 (17.32-56.95)]. Notably, most AEs among five treatment groups occurred within 30 days.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion \u003c/strong\u003eThese findings highlight the safety profiles of GEM, as well as GEM combination therapy, and offer important insights to enhance the clinical use and minimize potential adverse effects.\u003c/p\u003e","manuscriptTitle":"Risk comparison of adverse reactions among gemcitabine monotherapy, gemcitabine combined with cisplatin, gemcitabine combined with PD-1/PD-L1 inhibitors treatment: insights from the FDA adverse event reporting system database","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-22 07:12:30","doi":"10.21203/rs.3.rs-7907815/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-11-17T00:51:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"187645837148651811765306592251364933146","date":"2025-11-16T23:32:58+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-14T12:01:52+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-22T12:08:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-21T00:38:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-21T00:38:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2025-10-20T16:53:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e801e727-af3e-455c-bd6a-b2dcb11ffada","owner":[],"postedDate":"October 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-11-14T12:08:26+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-22 07:12:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7907815","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7907815","identity":"rs-7907815","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}