A real-world analysis of FDA Adverse Event Reporting System (FAERS) events for liposomal and conventional doxorubicins.

Introduction

Doxorubicin (DOX) works by intercalating into the DNA and subsequently inhibiting topoisomerase-II-mediated DNA repair 1 . It was a major component of many chemotherapy treatment regimens in clinical use 2 . According to the National Cancer Institute(NCI, https://www.cancer.gov ), Dox was approved to be used alone or with other drugs to treat:acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), breast cancer, gastric (stomach) cancer, hodgkin lymphoma, neuroblastoma, non-Hodgkin lymphoma, non-small cell lung cancer, ovarian cancer, small cell lung cancer, soft tissue and bone sarcomas, thyroid cancer, transitional cell bladder cancer, and wilms tumor. However, CDOX, either used alone or in combination with other chemotherapy drugs 3 , induces dose-dependent cardiotoxicity 4 , hematopoietic toxicity, hepatotoxicity, nephrotoxicity, and central neurotoxicity 5 , 6 . As a result, nano-scale delivery systems have been developed to reverse drug resistance and enhance the efficacy of doxorubicin. Several liposomal doxorubicin products, including but not limited to Doxil/Caelyx, and Myocet, have been marketed. While pegylated liposomal (Doxil) and non-pegylated liposomal (Myocet) formulations have unquestionably reduced drug toxicity, they have also introduced new toxicity issues.

Doxil (USA) and Caelyx (Europe and Canada) were the same liposomal doxorubicin approved in different countries 7 . In 1995, Doxil received FDA approval for the treatment of various cancer types 8 . Doxil was a useful option in the treatment of various malignancies, including metastatic breast cancer 9 , ovarian cancer, multiple myeloma and AIDS-related kaposi's sarcoma 10 . Doxil was a liposomal formulation that modified surface properties using PEGylation based on CDOX 11 . This revolutionized the field of surface functionalization for liposomes 12 . This greatly reduced the risk of cardiotoxicity, no acute emesis, and lower alopecia, nausea 13 or extravasation necrosis 14 (Fig. 1 ). Numerous clinical research examined the therapeutic efficacy of Doxil in elderly patients with locally-advanced or metastatic breast cancer, with side effects including anaemia, mocusal inflammation 15 , PPE, infection and pulmonary embolism 16 , but no significant cardiotoxicity. The main toxicity of Doxil was mucocutaneous toxicity, such as PPE, also known as hand-foot syndrome 11 , 12 . Previous studies have demonstrated that this adverse reaction was caused by the toxic effect of polyethylene glycol-modified agent 15 . Myocet was a liposome-encapsulated formulation of the cytotoxic anthracycline doxorubicin, which differs from Doxil and CDOX 17 . Preclinical and clinical results showed that Myocet has similar drug efficacy and reduced PPE 12 compared with Doxil 18 – 20 . Doxil significantly decreased cardiactoxicity and gastrointestinal toxicity 21 . Figure 1 Drug nanocrystallization of DOX and tumor application. ( a ), nanocrystallization process of CDOX. ( b ), mechanisms of liposomal doxorubicin in enhancing permeation and retention and reducing cardiotoxicity. ( c ), mechanism of liposomal doxorubicin and CDOX inhibiting various solid tumors.

Meta-analyses of adverse events related to Doxil have primarily focused on side effects in ovarian cancer and breast cancer cardiotoxicity. In recurrent ovarian cancer, the toxicity profile of Doxil compared favorably with that of the comparator, despite PPE sometimes leading to treatment discontinuation. Doxil combined with carboplatin was associated with significantly more anemia and thrombocytopenia 22 , 23 . A meta-analysis of breast cancer based on 48 randomized controlled trials found that Doxil showed a trend towards lower cardiotoxic and cardiac event rates compared to CDOX 24 – 26 .

This study aims to use data mining to comprehensively evaluate and characterize the adverse events of liposomal doxorubicin compared to CDOX, using the Food and Drug Adverse Event Reporting System (FAERS) database. This will assist in establishing a set of evidence and expert consensus-based prevention and management recommendations.

Results

General characteristics

We analyzed a total of 68,803 (0.43%) adverse event reports associated with liposomal doxorubicin and conventional doxorubicin (CDOX), including 61,709 (89.69%) CDOX cases, 6663 (9.68%) Doxil cases, and 431 (0.63%) Myocet cases. The majority of the reports were submitted by physicians (42.63%) and other healthcare professionals (22.98%). The clinical characteristics of the events involving liposomal doxorubicin and CDOX were summarized in Table 1 . The average onset age was slightly above 50 years and the mean weight was 59.6 kg, with more reports involving male than female patients (49.28% vs. 33.33%). The reports for CDOX and Doxil primarily came from the United States (31.50%, 39.80%), Canada (7.89%, 7.58%), and Germany (6.78%, 5.76%), while the reports for Myocet mainly originated from Germany (38.54%), Italy (17.20%), and Poland (11.15%). In terms of cancer prevalence, patients with malignant lymphoma (32.16%) showed the highest case rates, followed by breast cancer (10.56%). Notably, diffuse large B-cell lymphoma accounted for up to 40.91% of malignant lymphoma cases. The number of cases gradually increased over the years, with the largest increases observed between 2016 and 2019 (32.44%), followed by the period 2020–2022 (29.64%). Table 1 Clinical characteristics. Characteristics CDOX Doxil Myocet Total Patient age, years Mean 49.24 57.37 54.64 50.14 < 18, n (%) 650 (1.77) 9 (0.21) 3 (0.96) 662 (1.60) 18–64, n (%) 3321 (9.05) 378 (8.96) 9 (2.87) 3708 (8.99) ≥ 65, n (%) 1174 (3.20) 181 (4.29) 14 (4.46) 1369 (3.32) Unknown 31,570 (85.99) 3653 (86.54) 288 (91.72) 35,511 (86.09) Wt, kg Mean 57.68 72.22 70.80 59.61 Reporting country, n (%) Austria 244 (0.66) 70 (1.66) 18 (5.73) 332 (0.80) Canada 2895 (7.89) 320 (7.58) (0) 3215 (7.79) China 798 (2.17) 15 (0.36) (0) 813 (1.97) Germany 2490 (6.78) 243 (5.76) 121 (38.54) 2854 (6.92) Spain 893 (2.43) 141 (3.34) 32 (10.19) 1066 (2.58) France 2160 (5.88) 271 (6.42) 13 (4.14) 2444 (5.92) United Kingdom 2169 (5.91) 168 (3.98) 6 (1.91) 2343 (5.68) Italy 1791 (4.88) 204 (4.83) 54 (17.20) 2049 (4.97) Japan 2033 (5.54) 183 (4.34) 2 (0.64) 2218 (5.38) Poland 638 (1.74) 55 (1.30) 35 (11.15) 728 (1.76) United states 11,564 (31.50) 1680 (39.80) 4 (1.27) 13,248 (32.12) Other countries 9040 (24.62) 871 (20.63) 29 (9.24) 9940 (24.10) Reporters, n (%) Consumer 3433 (9.35) 513 (12.15) 8 (2.55) 3954 (9.59) Health-professional 4681 (12.75) 569 (13.48) 24 (7.64) 5274 (12.79) Lawyer 266 (0.72) 228 (5.40) (0) 494 (1.20) Physician 15,609 (42.51) 1753 (41.53) 224 (71.34) 17,586 (42.63) Other health-professional 8749 (23.83) 685 (16.23) 47 (14.97) 9481 (22.98) Pharmacist 1626 (4.43) 237 (5.61) 10 (3.18) 1873 (4.54) Unknown 2351 (6.40) 236 (5.59) 1 (0.32) 2588 (6.27) Indications, n (%) Acute leukaemia 1747 (4.76) 66 (1.56) 17 (5.41) 1830 (4.44) Acute lymphocytic leukaemia 1187 (67.95) 25 (37.88) 17 (100.00) 1229 (67.16) Other acute leukaemia 560 (32.05) 41 (62.12) (0) 601 (32.84) Malignant lymphoma 12,448 (33.90) 755 (17.89) 63 (20.06) 13,266 (32.16) Diffuse large B-cell lymphoma 4999 (40.16) 400 (52.98) 28 (44.44) 5427 (40.91) B-cell lymphoma 1773 (14.24) 47 (6.23) 9 (14.29) 1829 (13.79) Non-Hodgkin's lymphoma 1689 (13.57) 76 (10.07) 13 (20.63) 1778 (13.40) Other lymphoma 3987 (32.03) 232 (30.72) 13 (20.64) 4232 (31.9) Breast cancer 3787 (10.31) 400 (9.48) 170 (54.14) 4357 (10.56) Lung cancer 89 (0.24) 11 (0.26) 1 (0.32) 101 (0.24) Ovarian cancer 671 (1.83) 807 (19.12) 2 (0.64) 1480 (3.59) Sarcoma 1943 (5.29) 161 (3.81) (0) 2104 (5.10) Osteosarcoma 345 (17.76) 19 (11.80) (0) 364 (17.30) Ewing's sarcoma 352 (18.12) 14 (8.70) (0) 366 (17.40) Kaposi's sarcoma 84 (4.32) 37 (22.98) (0) 121 (5.75) Other sarcoma 1162 (59.8) 91 (56.52) (0) 1253 (59.55) Nephroblastoma 86 (0.23) 3 (0.07) (0) 89 (0.22) Renal cancer 143 (0.39) 9 (0.21) (0) 152 (0.37) Multiple myeloma 1325 (3.61) 334 (7.91) 2(0.64) 1661 (4.03) Other cancer/unkown indication 14,476 (39.43) 1675 (39.68) 59(3.64) 16,210 (7.03) Reporting year, n (%) 2004–2007 3042 (8.29) 577 (13.67) 4 (1.27) 3623 (8.78) 2008–2011 4006 (10.91) 502 (11.89) 33 (10.51) 4541 (11.01) 2012–2015 6721 (18.31) 626 (14.83) 134 (42.68) 7481 (18.14) 2016–2019 12,164 (33.13) 1143 (27.08) 73 (23.25) 13,380 (32.44) 2020–2022 10,782 (29.37) 1373 (32.53) 70 (22.29) 12,225 (29.64) Sex, n (%) Female 17,331 (47.20) 2751 (65.17) 248 (78.98) 20,330 (49.28) Male 12,724 (34.66) 993 (23.53) 33 (10.51) 13,750 (33.33) Unknown 6660 (18.14) 477 (11.30) 33 (10.51) 7170 (17.38) Total 36,715 (100.00) 4221 (100.00) 314 (100.00) 41,250 (100.00) CDOX conventional doxorubicin, Doxil pegylated-liposome doxorubicin, Myocet non-pegylated-liposome doxorubicin, n the number of cases.

Signal detection

Distinct risks of adverse events associated with liposomal doxorubicin and CDOX were identified (Table 2 ). Adverse events for liposomal doxorubicin and CDOX were analyzed using the reporting odds ratio (ROR), proportional reporting ratio (PRR), and Bayesian confidence propagation neural network (BCPNN). In total, 32 ROR signals were detected for all drugs, with CDOX, Doxil, and Myocet respectively accounting for 19, 18, and 11 positive signals. The results for the positive signals for liposomal doxorubicin and CDOX were summarized in Table 3 . Table 2 Signal detection. SOC Adverse events Total CDOX Doxil Myocet n ROR 95%CI n ROR 95%CI n ROR 95%CI PT code PTs 68,803 61,709 6663 431 Blood and lymphatic system disorders 10002034 Anaemia 4055 3609 4.24 4.10; 4.39 422 4.57 4.15; 5.04 24 4.01 2.67; 6.02 10033661 Pancytopenia 2414 2166 9.36 8.96; 9.78 236 9.13 8.02; 10.39 12 7.13 4.03; 12.63 10029354 Neutropenia 6991 6461 12.97 12.64; 13.31 474 8.18 7.45; 8.97 56 15.58 11.84; 20.49 10043554 Thrombocytopenia 4041 3653 7.91 7.65; 8.18 360 7.00 6.30; 7.78 28 8.49 5.81; 12.40 Cardiac disorders 10007636 Cardiomyopathy 900 845 12.87 12.00; 13.81 53 7.05 5.38; 9.24 2 4.10 1.02; 16.44 10048610 Cardiotoxicity 1192 1116 38.87 36.41; 41.49 67 17.96 14.10; 22.86 9 37.36 19.34; 72.17 Gastrointestinal disorders 10012735 Diarrhoea 3276 2972 1.06 1.02; 1.10 280 0.93 0.82; 1.05 24 1.25 0.83; 1.88 10028813 Nausea 4180 3636 1.02 0.98; 1.05 533 1.41 1.29; 1.54 11 0.43 0.24; 0.79 10047700 Vomiting 3284 2900 1.39 1.34; 1.45 372 1.68 1.51; 1.86 12 0.82 0.46; 1.46 General disorders and administration site conditions 10016288 Febrile neutropenia 9427 8868 42.45 41.44; 43.48 498 17.53 16.02; 19.20 61 34.68 26.63; 45.15 10028116 Mucosal inflammation 2426 2214 21.68 20.74; 22.67 197 16.18 14.04; 18.65 15 19.02 11.40; 31.75 10037660 Pyrexia 4997 4538 3.00 2.91; 3.09 405 2.45 2.22; 2.71 54 5.31 4.02; 7.01 Infections and infestations 10040047 Sepsis 3137 2940 6.05 5.82; 6.28 177 3.26 2.81; 3.78 20 5.79 3.71; 9.03 Metabolism and nutrition disorders 10059512 Apoptosis 6 6 4.30 1.91; 9.68 0 – – 0 – – 10057248 Cell death 12 7 0.80 0.38; 1.68 5 5.35 2.22; 12.88 0 – – Musculoskeletal and connective tissue disorders 10003239 Arthralgia 854 754 0.42 0.39; 0.45 99 0.51 0.42; 0.63 1 0.08 0.01; 0.57 10003988 Back pain 1018 819 0.76 0.71; 0.82 194 1.71 1.48; 1.97 5 0.67 0.28; 1.62 10005956 Bone disorder 282 237 2.59 2.28; 2.95 44 4.47 3.32; 6.01 1 1.57 0.22; 11.16 10006002 Bone pain 891 835 3.14 2.93; 3.36 52 1.79 1.37; 2.36 4 2.14 0.80; 5.72 10031264 Osteonecrosis 593 526 3.06 2.81; 3.34 65 3.49 2.74; 4.46 2 1.66 0.41; 6.65 Neoplasms benign, malignant and unspecified (incl cysts and polyps) 10051398 Malignant neoplasm progression 2180 1795 4.36 4.16; 4.58 369 8.40 7.57; 9.32 16 5.56 3.38; 9.13 Nervous system disorders 10008190 Cerebrovascular accident 292 254 0.30 0.27; 0.34 34 0.38 0.27; 0.53 4 0.70 0.26; 1.86 10019211 Headache 1249 1094 0.37 0.35; 0.39 151 0.48 0.41; 0.57 4 0.20 0.07; 0.52 10024382 Leukoencephalopathy 153 139 8.19 6.91; 9.72 14 7.42 4.39; 12.55 0 – – 10033775 Paraesthesia 605 507 0.67 0.62; 0.73 93 1.16 0.94; 1.42 5 0.97 0.40; 2.33 10044565 Tremor 257 223 0.28 0.25; 0.32 30 0.35 0.25; 0.50 4 0.73 0.27; 1.96 Psychiatric disorders 10002855 Anxiety 1614 1409 1.04 0.99; 1.10 204 1.42 1.23; 1.63 1 0.11 0.01; 0.75 Respiratory, thoracic and mediastinal disorders 10022611 Interstitial lung disease 1649 1355 6.81 6.44; 7.19 291 13.49 12.00; 15.17 3 2.09 0.67; 6.50 10035598 Pleural effusion 1315 1148 4.12 3.88; 4.37 162 5.36 4.59; 6.27 5 2.54 1.05; 6.12 10035664 Pneumonia 3214 2914 1.93 1.86; 2.00 278 1.70 1.51; 1.92 22 2.11 1.38; 3.22 Skin and subcutaneous tissue disorders 10033553 Palmar-plantar erythrodysaesthesia syndrome 1024 626 6.16 5.69; 6.68 384 36.14 32.60; 40.06 14 19.69 11.59; 33.44 Vascular disorders 10037377 Pulmonary embolism 1275 1143 2.48 2.34; 2.63 120 2.41 2.02; 2.89 12 3.77 2.13; 6.67 SOC system organ class, n the number of cases, 95% CI 95%CI lower and 95% CI upper, PT preferred terms. Table 3 Positive signal detection results of liposomal doxorubicin and CDOX. SOC PTs CDOX Doxil Myocet ROR (95%CI) PRR (X 2 ) IC025 ROR (95%CI) PRR (X 2 ) IC025 ROR (95%CI) PRR (X 2 ) IC025 Blood and lymphatic system disorders Anaemia 4.24 (4.10; 4.39) 4.12 (8402.09) 1.90 4.57 (4.15; 5.04) 4.42 (1125.53) 1.81 4.01 (2.67; 6.02) 3.89 (52.13) 0.47 Pancytopenia 9.36 (8.96; 9.78) 9.17 (14,995.22) 2.98 9.13 (8.02; 10.39) 8.94 (1659.32) 2.68 7.13 (4.03; 12.63) 7.02 (62.09) 0.44 Neutropenia 12.97 (12.64; 13.31) 12.14 (62,022.04) 3.42 8.18 (7.45; 8.97) 7.84 (2829.84) 2.64 15.58 (11.84; 20.49) 14.31 (697.06) 2.63 Thrombocytopenia 7.91 (7.65; 8.18) 7.64 (20,281.80) 2.76 7.00 (6.30; 7.78) 6.79 (1778.29) 2.39 8.49 (5.81; 12.40) 8.16 (176.88) 1.47 Cardiac disorders Cardiomyopathy 12.87 (12.00; 13.81) 12.76 (8528.89) 3.33 7.05 (5.38; 9.24) 7.02 (272.40) 1.76 – – – Cardiotoxicity 38.87 (36.41; 41.49) 38.41 (33,183.86) 4.73 17.96 (14.10; 22.86) 17.84 (1053.77) 3.03 37.36 (19.34; 72.17) 36.85 (313.55) 0.93 General disorders and administration site conditions Febrile neutropenia 42.45 (41.44; 43.48) 38.51 (264,943.39) 4.90 17.53 (16.02; 19.20) 16.71 (7301.35) 3.70 34.68 (26.63; 45.15) 31.49 (1803.81) 3.53 Mucosal inflammation 21.68 (20.74; 22.67) 21.19 (37,920.92) 4.09 16.18 (14.04; 18.65) 15.88 (2723.60) 3.40 19.02 (11.40; 31.75) 18.60 (249.98) 1.50 Pyrexia 3.00 (2.91; 3.09) 2.90 (5662.74) 1.42 2.45 (2.22; 2.71) 2.39 (333.59) 0.92 5.31 (4.02; 7.01) 4.95 (172.95) 1.29 Infections and infestations Sepsis 6.04 (5.82; 6.28) 5.89 (11,590.60) 2.39 3.26 (2.81; 3.78) 3.22 (271.75) 1.17 5.78 (3.71; 9.03) 5.64 (76.70) 0.76 Musculoskeletal and connective tissue disorders Bone disorder 2.59 (2.28; 2.95) 2.59 (228.21) 0.92 4.47 (3.32; 6.01) 4.46 (117.72) 1.07 – – – Bone pain 3.14 (2.93; 3.36) 3.12 (1181.85) 1.39 – – – – – – Osteonecrosis 3.06 (2.81; 3.34) 3.05 (712.26) 1.30 3.49 (2.74; 4.46) 3.48 (114.72) 0.94 – – – Neoplasms benign, malignant and unspecified (incl cysts and polyps) Malignant neoplasm progression 4.36 (4.16; 4.58) 4.30 (4453.89) 1.92 8.40 (7.57; 9.32) 8.13 (2305.32) 2.64 5.56 (3.38; 9.13) 5.44 (58.30) 0.51 Nervous system disorders leukoencephalopathy 8.19 (6.91; 9.72) 8.18 (836.43) 2.34 7.42 (4.39; 12.55) 7.41 (77.29) 0.69 – – – Respiratory, thoracic and mediastinal disorders Interstitial lung disease 6.81 (6.44; 7.19) 6.72 (6361.84) 2.51 13.49 (12.00; 15.17) 13.13 (3241.89) 3.26 – – – Pleural effusion 4.12 (3.88; 4.37) 4.08 (2615.42) 1.80 5.36 (4.59; 6.27) 5.29 (563.81) 1.85 – – – Skin and subcutaneous tissue disorders Palmar-plantar erythrodysaesthesia syndrome 6.16 (5.69; 6.68) 6.13 (2596.88) 2.30 36.13 (32.60; 40.06) 34.78 (12,345.37) 4.63 19.69 (11.59; 33.44) 19.28 (242.77) 1.42 Vascular disorders Pulmonary embolism 2.48 (2.34; 2.63) 2.46 (986.82) 1.09 2.41 (2.02; 2.89) 2.40 (98.07) 0.65 – – – ROR reporting odds ratio, PRR proportional reporting ratio, IC025 the lower limit of the 95% two-sided CI of the IC.

The RORs (95% CI) for febrile neutropenia associated with CDOX, Doxil, and Myocet were 42.45 (41.44; 43.48), 17.53 (16.02; 19.20), and 34.68 (26.63; 45.15) respectively. For cardiotoxicity, the RORs (95%CI) were 38.87 (36.41; 41.49), 17.96 (14.10; 22.86), and 37.36 (19.34; 72.17) respectively. The RORs (95% CI) for PPE were 6.16 (5.69; 6.68), 36.13 (32.60; 40.06), and 19.69 (11.59; 33.44) respectively. Additionally, the RORs (95% CI) for cardiomyopathy associated with CDOX and Doxil were 12.87 (12.00; 13.81) and 7.05 (5.38; 9.24), and for leukoencephalopathy associated with CDOX and Doxil were 8.19 (6.91; 9.72) and 7.42 (4.39; 12.55). The RORs (95% CI) for interstitial lung diseases with CDOX and Doxil were 6.81 (6.44; 7.19) and 13.49 (12.00; 15.17).

For CDOX and Myocet, the RORs for cardiotoxicity and febrile neutropenia ranked highly. For Doxil, the ROR for PPE ranked highly. Analysis of the FAERS data suggests that the RORs for cardiomyopathy, febrile neutropenia, mucosal inflammation, and pyohemia associated with the use of Doxil were lower than those associated with CDOX. However, the RORs for PPE and interstitial lung diseases associated with Doxil treatment were higher than those associated with CDOX. The primary adverse events of liposomal doxorubicin and CDOX were summarized in Fig. 2 . Figure 2 Summary of main adverse events of liposomal doxorubicin and CDOX.

Onset time of events

In total, 13 cases reported the onset time. Upon comparing liposomal doxorubicin and CDOX, we found significant differences in 5 adverse events, namely neutropenia, palmar-plantar erythrodysesthesia (PPE), pneumonia, pulmonary embolism, and malignant neoplasm progression (Table 4 ). Myocet was excluded from the discussion for malignant neoplasm progression as the number of cases was less than 2. Table 4 Onset time of events (days). SOC PTs CDOX Doxil Myocet n Median (IQR) Mean n Median (IQR) Mean n Median (IQR) Mean Blood and lymphatic system disorders Neutropenia 75 35 (14; 273) 90.85 59 17 (10; 47) 66.35 25 30 (11.5; 78.5) 79.68 Pancytopenia 44 58.5(15; 123) 57.89 61 50 (15; 133.5) 55.06 6 80.5 (6.5; 121.5) 51.75 Thrombocytopenia 32 14 (8; 91) 39.67 52 45 (14.25; 102) 53.74 11 16 (14; 59) 45.09 Febrile neutropenia 124 33 (11; 77.25) 123.37 92 34 (12; 80.5) 128.23 29 12 (9; 86.5) 104.83 Cardiac disorders Cardiomyopathy 24 126 (89; 325.5) 19.79 16 230 (121.5; 252) 21.56 1 – – General disorders and administration site conditions Mucosal inflammation 24 15 (8; 29) 22.77 16 11 (6.25; 66) 23.41 7 20 (14; 50) 29.57 Infections and infestations Sepsis 19 24 (9; 101) 24.82 26 51.5 (17.75; 107.5) 31.4 11 61 (10; 61) 28 Neoplasms benign, malignant and unspecified (incl cysts and polyps) Malignant neoplasm progression 11 427 (153; 1371) 52.41 63 142 (56; 445) 34.9 1 – – Respiratory, thoracic and mediastinal disorders Interstitial lung disease 24 105 (51.5; 114) 37.94 58 99 (42; 120.25) 46.33 3 49 (9; .) 19.17 Pneumonia 43 159 (16; 365) 52.15 37 17 (4; 290) 35.91 9 90 (41;116) 48.22 Pleural effusion 12 62 (20.75; 250) 22.75 28 79 (19.25; 177.5) 19.54 1 – – Skin and subcutaneous tissue disorders Palmar-plantar erythrodysaesthesia syndrome 11 60 (30; 72) 46.86 74 46 (30; 67.75) 45.28 10 72 (56.5;96.75) 69.4 Vascular disorders Pulmonary embolism 16 96.5 (86; 1611) 29.84 25 49 (15.5; 95) 19.46 6 85 (49.5;200.25) 27.33 n number of cases with available time-to-onset, IQR interquartile range, Mean rank average, CI confidence interval, IC information component, ROR reporting odds ratio, PRR proportional reporting ratio, IC025 the lower limit of the 95%two-sided CI of the IC, bold said statistical results have significant difference, p < 0.05.

The median (IQR) for neutropenia associated with CDOX, Doxil, and Myocet were 35 (14; 273), 17 (10; 47), and 30 (11.5; 78.5), respectively. For PPE, the median (IQR) was 60 (30; 72), 46 (30; 67.75), and 72 (56.5; 96.75). For pneumonia, the median (IQR) was 159 (16; 365), 17 (4; 290), and 90 (41; 116). For pulmonary embolism, the median (IQR) was 96.5 (86; 1611), 49 (15.5; 95), and 85 (49.5; 200.25).

Mucosal inflammation had the shortest onset time, while malignant neoplasm progression had the longest. The onset times for malignant neoplasm progression and pneumonia for Doxil were significantly shorter than those for CDOX. Additionally, the onset times for cardiomyopathy, sepsis, and thrombocytopenia were longer for Doxil compared to CDOX. Conversely, for Myocet, the onset times for PPE, pancytopenia, and sepsis were longer than those for CDOX, while the onset time for febrile neutropenia was shorter than for CDOX (Fig. 3 ). Figure 3 The onset time chart of liposomal doxorubicin and CDOX.

Outcome events

We evaluated the outcomes reported to determine the prognosis of patients who experienced adverse events following liposomal doxorubicin and CDOX treatments (Table 5 ). Among all adverse events, the lowest risk was for disability (0.62%, 1.04%, and 1.27%), while the highest was for initial or prolonged hospitalization (36.88%, 31.20%, and 43.95%). The highest proportion of fatalities occurred in CDOX patients, followed by Doxil (17.34%), with the lowest observed in Myocet patients (13.38%) (Fig. 4 ). Table 5 Outcome events. CDOX Doxil Myocet Total reports 36,715 4221 314 Outcome events, n (%) Death 6700 (18.25) 732 (17.34) 42 (13.38) Disability 226 (0.62) 44 (1.04) 4 (1.27) Hospitalization-initial or prolonged 13,542 (36.88) 1317 (31.20) 138 (43.95) Life-threatening 2507 (6.83) 233 (5.52) 30 (9.55) Other serious (important medical event) 12,742 (34.71) 1584 (37.53) 100 (31.85) Unknown 998 (2.72) 311 (7.36) (0) Figure 4 The outcome events chart of liposomal doxorubicin and CDOX.

Discussion

This study provides an updated, comprehensive analysis of the characteristics and differences in adverse events following treatment with liposomal doxorubicin compared to CDOX. Due to its enhanced permeability, retention, and lower cardiotoxicity, Doxil plays a significant role in the clinical setting. The majority of preferred terms (PTs) were chosen based on previous reports by Fukuda et al. 7 , thus complementing findings that were previously unattainable due to a lack of cases. Despite its benefits, liposomal doxorubicin can cause additional discomfort to patients, thereby reducing their quality of life. Consequently, a comprehensive disproportionality analysis for liposomal doxorubicin and CDOX was crucial for optimal clinical application and management.

Regarding the study of adverse events of CDOX and liposomal doxorubicin, our results were different from those of Fukuda et al. We identified several significant differences. Overall, the response to adverse events was better with liposomal DOX and CDOX, and several key findings emerged that warrant further discussion.

Randomized controlled trials have demonstrated that Doxil exhibits comparable anti-tumor activity and significantly reduced cardiotoxicity compared to CDOX in multiple breast cancer patients 13 , 27 . PPE, frequently observed in Doxil usage, was not seen with Myocet 21 . However, our results showed that the ROR for PPE was noticeably higher with Doxil compared to CDOX. The ROR for PPE in patients receiving Myocet was also high and could potentially be closely related to the dose or duration of Myocet treatment 28 , 29 . A retrospective trial of Myocet in lymphoma patients revealed that the most common grade 3/4 toxicity was hematological, including leukopenia, neutropenia, thrombocytopenia, and febrile neutropenia. In contrast, the main toxicity of Doxil was mucocutaneous 27 , 30 . Our study showed that the reporting odds ratios (RORs) for cardiotoxicity and febrile neutropenia were significantly lower for Doxil, compared to CDOX. However, Myocet did not appear to reduce the risk of cardiotoxicity and febrile neutropenia as effectively. Fukuda et al. suggested that Doxil and Myocet had lower RORs for cardiotoxicity and higher RORs for PPE compared to CDOX 7 . Our results of Doxil were largely consistent with Fukuda, and the PPE deserved attention when using Doxil. Interestingly, our results on Myocet in terms of cardiotoxicity were diametrically opposed to those of Fukuda et al. reported fewer than two cases of cardiotoxicity for Myocet, while the RORs for cardiotoxicity were considered low for Myocet. Our data suggested that Myocet appeared to have little advantage over CDOX. In the retrospective and prospective study of Sancho et al., it was found that using Myocet instead of CDOX was not associated with reduced early cardiotoxicity, although some reduced cardiac safety signals were observed 31 . Our results were consistent with that of Sancho et al. Age was one of the risk factors for cardiotoxicity. This may be related to the number of cases and the patient's age.

In our analysis, the age of most patients was concentrated between 18 and 64, with a mean onset age just over 50 years and a mean weight of 59.6 kg. Over the past 19 years, the number of reported cases has steadily increased. It was reported that the first exposure to Doxil can lead to immediate hypersensitivity reactions (HSRs) 32 . The symptoms include dyspnea, tachypnea, facial flushing, facial swelling, headache, hypertension or hypotension, chills, chest pain and back pain 32 . We have analyzed the adverse events of headache, back pain and paraesthesia caused by liposomal doxorubicin and CDOX, but they did not show significant differences in these adverse events. First of all, it may be that this adverse reaction can be pre-treated with corticosteroids and antihistamines 32 . Secondly, most patients with an initial reaction can finish the first infusion at a slower infusion rate after interruption and recovery, and usually tolerate further infusions 32 . Finally, the occurrence of HSRs depends on Doxil with high doses or short dosing intervals 29 . Because the FAERS database does not count dosages of Doxil used by patients, we were unable to collect data. Therefore, the HSRs of Doxil cannot be accurately interpreted.

The indications of DOX in this paper include approved and off-label cancer types. According to the National Cancer Institute (NCI, https://www.cancer.gov ), Dox was approved to be used alone or with other drugs to treat: acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), breast cancer, gastric (stomach) cancer, hodgkin lymphoma, neuroblastoma, non-Hodgkin lymphoma, non-small cell lung cancer, ovarian cancer, small cell lung cancer, soft tissue and bone sarcomas, thyroid cancer, transitional cell bladder cancer, and wilms tumor. In 1995, Doxil received FDA approval for the treatment of various disease types 8 including Ovarian cancer 33 , Multiple myeloma, and AIDS-related Kaposi sarcoma. In addition, there were many clinical trials and literatures supporting Doxil for breast cancer 9 , lung cancer 34 , soft tissue and bone sarcoma 35 , renal cancer 36 , prostate cancer 37 , and cervical squamous cell carcinoma 38 .

In terms of cancer prevalence, patients with malignant lymphoma exhibited the highest reporting rate, especially those with diffuse large B-cell lymphoma. The combination of Doxil and carboplatin resulted in a higher incidence but shorter duration of mucosal perfusion and PPE 30 . In our study, the onset time for mucosal inflammation after treatment with liposomal doxorubicin and CDOX was the shortest, while that for malignant neoplasm progression was the longest. The onset times for cardiomyopathy, sepsis, and thrombocytopenia were longer for Doxil compared to CDOX. Moreover, the onset times for PPE, pancytopenia, and sepsis were longer for Myocet compared to CDOX. The onset time of PPE for Myocet was longer than that for CDOX, whereas the onset time for Doxil was shorter. This suggests that Doxil more readily and quickly induces mucosal inflammation and PPE. Additionally, the onset times of malignant neoplasm progression and lung disease for Doxil were shorter than for CDOX, indicating these conditions were more easily triggered by Doxil.

The Myocet did not reduce cardiotoxicity while maintaining efficacy and appeared to have no advantage. Compared to CDOX, Doxil shows equivalent antitumor activity with fewer side effects, but further strategies were needed to mitigate these adverse reactions. Continuous monitoring, risk evaluations, and additional comparative studies of liposomal doxorubicin and CDOX should be considered. This will provide a reference for the safe and effective clinical use of liposomal doxorubicin and CDOX.

Due to inherent limitations of clinical trials, such as patients having multiple disease types, some patients experiencing several adverse events simultaneously, the relatively small sample size for certain adverse events, differences in the occupation and professional levels of the reporters, non-standardized time recording, and the possibility of false positive signals in the signal detection method, we may not be able to fully unravel the intricacies of this study. Thus, further clinical trials were required to inform drug selection in clinical practice.

Conclusions

Liposomal doxorubicin and CDOX must be applied with caution. Our analysis of FAERS data indicates that the RORs for cardiomyopathy, febrile neutropenia, mucosal inflammation, and pyohemia resulting from Doxil use were lower than those associated with CDOX. Moreover, the ROR for PPE was higher in patients treated with Doxil than those treated with Myocet, and the ROR for interstitial lung diseases was higher in patients treated with Doxil than those treated with CDOX. The RORs for cardiotoxicity, febrile neutropenia, pyrexia, and neutropenia were higher in patients treated with Myocet than those treated with Doxil.

We found that the onset time for malignant neoplasm progression and pneumonia was significantly shorter with Doxil than with CDOX through examining the onset time of adverse events. Conversely, the onset times for cardiomyopathy, sepsis, and thrombocytopenia were longer for Doxil than for CDOX. In the case of Myocet, the onset times for PPE, pancytopenia, and sepsis were longer than those for CDOX and Doxil, while the onset time for febrile neutropenia was shorter. In evaluating the outcome of events, liposomal doxorubicin and CDOX presented a lower risk of disability as an adverse event. However, the risk of initial or prolonged hospitalization was the highest, followed by other serious adverse events. The death rate for patients using CDOX and Doxil was slightly higher than for those using Myocet, although the opposite was found in life-threatening reports.

The results of this study show that cardiotoxicity and febrile neutropenia should be carefully monitored when using CDOX and Myocet. In the case of Doxil, it was particularly necessary to monitor PPE and interstitial lung disease. Additionally, the onset time of febrile neutropenia, malignant neoplasm progression, and pneumonia caused by liposomal doxorubicin requires careful attention. Continuous monitoring, risk assessments, and further comparative studies of liposomal doxorubicin and CDOX should be considered.

Materials and methods

Data source. The FAERS database ( https://fis.fda.gov/extensions/FPD-QDE-FAERS/FPD-QDE-FAERS.html ) encompasses demographic and administrative details, drug information, Medical Dictionary for Regulatory Activities’ (MedDRA) preferred terminology (PT) for adverse event (REAC) coding, patient outcomes, reporting sources, initiation and end dates of treatment reports, and indications for use. We carried out a retrospective study utilizing data from the FAERS database, spanning from January 2004 to December 2022. Initially, we downloaded data pertaining to liposomal doxorubicin and conventional doxorubicin (CDOX), which included case ID, primary ID, indications, suspected drugs, adverse events, outcome events, reporter country, reporter type, sex, age, report date, start date, and event date. Following the FDA’s recommendations, we removed duplicate records from the "DEMO" table, retaining only one, and deleted the earliest "FDA_DT" column when the "CASEID" column was identical. We also removed the lesser "PRIMARYID" column when both the "CASEID" and "FDA_DT" columns matched.

Adverse events and drug identification

MedDRA keywords such as "Anaemia (10002034)", "Back pain (10003988)", "Interstitial lung disease (20000042)", "Pancytopenia (10033661)", "Vomiting (10047700)", among others, were utilized to identify adverse events. Reports involving liposomal doxorubicin and conventional doxorubicin (CDOX) were pinpointed by conducting text string searches for each drug by their generic names, brand names, and abbreviations. We excluded drugs reported in conjunction with the eligible drug listed as interacting or concomitant. DrugBank (The Metabolomics Innovation Centre, Canada, https://go.drugbank.com/ ) served as a source for batch conversion and compilation of drug names.

Data mining

Disproportionality analysis and Bayesian analysis comprise four algorithms: the reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma poisson shrinker (MGPS). Three of these algorithms were used to establish a connection between liposomal doxorubicin and conventional doxorubicin (CDOX) and adverse events. The equations and standards for these three algorithms were presented in Table 6 23 – 28 , 30 . Unless otherwise specified, the current study employs an adjusted disproportionality (adjusted ROR) that accounts for the use of concurrent agents. In addition, the onset time and outcomes of the adverse events associated with liposomal doxorubicin and CDOX were collected and compared. Table 6 Summary of major algorithms used for signal detection. Algorithms Equation Criteria ROR ROR = (a/b)/(c/d) 95% CI > 1, N ≥ 2 PRR PRR = (a/(a + c))/(b/(b + d)); χ 2 = Σ ((O − E)2/E); (O = a, E = (a + b) (a + c)/(a + b + c + d)) PRR ≥ 2, χ 2 ≥ 4, N ≥ 3 BCPNN IC = log2a (a + b + c + d)/((a + c) (a + b)) IC025 > 0 a number of reports containing both the suspect drug and the suspect adverse drug reaction, b number of reports containing the suspect adverse drug reaction with other medications (except the drug of interest), c number of reports containing the suspect drug with other adverse drug reactions (except the event of interest), d number of reports containing other medications and other adverse drug reactions. ROR reporting odds ratio, CI confidence interval, N the number of co-occurrences, PRR proportional reporting ratio, BCPNN Bayesian confidence propagation neural network, IC information component, IC025 the lower limit of the 95% two-sided CI of the IC, 95% CI = eIn (ROR) ± 1.96√(1/a + 1/b + 1/c + 1/d).

Statistical analysis

The clinical characteristics of patients extracted from the FAERS database were summarized and compared using descriptive analysis. The onset time of adverse events across different drugs was compared using nonparametric tests (Mann–Whitney test for two groups, and the Kruskal–Wallis test for three groups). Fisher’s exact test or Pearson’s chi-square test was employed to compare outcome events across different drugs. Statistical significance was determined with a 95% confidence interval (CI) and p < 0.05. Both data mining and statistical analyses were conducted using Excel and SPSS version 25.0 (IBM Corporation, Armonk, New York, United States).

Publisher's note

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

These authors contributed equally: Huiling Su, Jing Jia and Yuxiang Mao.

Acknowledgements

This study was performed using the FDA Adverse Event Reporting System (FAERS) database that was provided by the FDA. The information, results, or interpretation of the current study do not represent any opinion of the FDA.

Author contributions

Conceptualization, Z.J.L.; Data curation, H.L.S., Y.X.M. and R.R.Z.; Formal analysis, Y.X.M. and R.R.Z.; Funding acquisition, Z.J.L. and J.J.; Investigation, H.L.S.; Methodology, Z.J.L. and H.L.S.; Project administration, Z.J.L. and J.J.; Resources, H.L.S.; Software, Y.X.M.; Supervision, Z.J.L. and J.J.; Validation, H.L.S. and Y.X.M.; Visualization, R.R.Z.; Writing original draft, H.L.S. and Y.X.M.; Writing review & editing, J.J. and R.R.Z.

Funding

This study was supported by China Postdoctoral Science Foundation (2022M711909), Shandong Provincial Natural Science Foundation (ZR2022MH068), Shandong Provincial Traditional Chinese Medicine Technology Project (Q-2022066) and Shandong Provincial Postdoctoral Science Foundation (SDCX-ZG-202203066).

Data availability

The FAERS database utilized in this study was available at: https://fis.fda.gov/extensions/FPD-QDE-FAERS/FPD-QDE-FAERS.html .

Competing interests

The authors declare no competing interests.

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