Study selection
A total of 531 studies were retrieved from the initial broad search through April 2022. Based on the inclusion and exclusion criteria, 7 articles[11-13, 18-21] were eligible for quantitative analysis, with a total of 2690 patients (Figure 1). There were 620 opioid-treated patients and 2070 opioid-free patients. The most common cancer types were non-small cell lung cancer (NSCLC), melanoma, and renal cell carcinoma (RCC). Finally, five studies[11-13, 18, 20] provided both OS and PFS, and the other two[19, 21] only reported OS. The baseline characteristics of the included studies are shown in Table 1.
Table 1. The Baseline Characteristics of Included Studies
Source
|
Country
|
Study type
|
Cancer type
|
ICI type
|
Opioid type
|
Patients, No. (Y/N)
|
Male, No. (%)
|
Age,
Median, y
|
|
Outcome
|
Botticelli (2021)[13]
|
Italy
|
Retrospective
|
NSCLC, melanoma, renal cancer, Merkel tumor, and colon cancer
|
Nivolumab, pembrolizumab, atezolizumab, and avelumab
|
NR
|
193(42/151)
|
120(62.0)
|
70.0
|
6
|
OS, PFS
|
Cortellini (2020)[18]
|
Italy
|
Retrospective
|
NSCLC, melanoma, RCC, and other cancers
|
Pembrolizumab, nivolumab, atezolizumab, and others
|
NR
|
1012(68/944)
|
647 (63.9)
|
68.5
|
8
|
OS, PFS
|
Gaucher (2021)[19]
|
France
|
Retrospective
|
Lung cancer, melanoma, renal and urothelial cancer, head and neck cancer, and other cancers
|
Ipilimumab, nivolumab and pembrolizumab
|
NR
|
372(173/199)
|
244(65.6)
|
64.0
|
6
|
OS
|
Kostine (2021)[20]
|
France
|
Retrospective
|
Melanoma, NSCLC, renal cancer, and other cancers
|
Anti-PD-1/PD-L1, anti-CTLA-4, sequential CPI
|
Morphine
|
635(130/505)
|
443 (70.0)
|
64.5
|
7
|
OS, PFS
|
Miura (2021)
|
Japan
|
Retrospective
|
NSCLC
|
Nivolumab, pembrolizumab
|
NR
|
300(114/186)
|
226 (75.3)
|
65.0
|
7
|
OS
|
Santamaría (2019)[11]
|
Spain
|
Retrospective
|
NSCLC, renal cancer, bladder cancer, melanoma, head and neck cancer, and other cancers
|
Nivolumab, pembrolizumab, atezolizumab, and ipilimumab
|
NR
|
102(55/47)
|
84 (82.4)
|
66.0
|
9
|
OS, PFS
|
Taniguchi (2020)[12]
|
Japan
|
Retrospective
|
NSCLC
|
Nivolumab
|
Oxycodone, fentanyl, morphine, hydromorphone, tapentadol
|
76(38/38)
|
53 (67.9)
|
NR
|
7
|
OS, PFS
|
*Obtained via correspondence with primary author
Abbreviations: CTLA-4: Cytotoxic T lymphocyte-associated antigen-4; ICIs: Immune Checkpoint Inhibitors; NR, not reported; NSCLC: non-small cell lung cancer; OS, overall survival; PD-1/PD-L1: Programmed cell death protein-1/Programmed cell death-ligand1; PFS, progression-free survival; RCC, renal cell carcinoma; Y/N, opioids use/no opioids use
Quality assessment
According to the NOS criteria, two reviewers independently evaluated the methodological quality of the included studies. Overall, all studies were considered medium or high quality, which was indicated by scores of at least six (Table 1).
Impact of opioids on ICIs (OS)
Opioids were negatively correlated with OS (HR=1.75, 95% CI = 1.32-2.31, P<0.001) with high heterogeneity (I2=80.4%, P<0.001), as shown in Figure 2A. In the subgroup analysis of NSCLC (HR=1.83, 95% CI=1.46-2.28, P<0.001; I2=46.1%, P=0.157), opioids had negative effects on ICIs. Moreover, the results were consistent based on the ICI type, sample size, and country, indicating that opioids were significantly related to reduced OS (Table 2). Sensitivity analysis suggested that the studies by Botticelli[13] and Kostine[20] were strongly associated with heterogeneity (supplementary figure 1A). After excluding the two studies, the results of OS were HR=1.87, 95% CI = 1.38-2.52, P<0.001; I2=77.6%, P<0.001 and HR=1.54, 95% CI = 1.25-1.90, P<0.001; I2=51.6%, P=0.066, respectively.
Impact of opioids on ICIs (PFS)
Opioids significantly reduced the PFS of patients treated with ICIs (HR=1.61, 95% CI=1.41-1.83, P<0.001) without heterogeneity (I2=0.0%, P=0.629), as shown in Figure 2B. Subgroup analysis also showed that opioids significantly reduced PFS based on ICI type, sample size, and country obtained similar results (Table 2). Sensitivity analyses reported that the results were not dominated by any single study (supplementary figure 1B).
Impact of NSAIDs or aspirin on ICIs (OS and PFS)
To evaluate the efficacy of non-opioids on ICIs, we analyzed the impact of nonsteroidal anti-inflammatory drugs (NSAIDs) on OS and PFS and further focused on aspirin, which is representative but has been shown to be independent from NSAIDs in some studies. NSAIDs could lead to poor OS (HR= 1.25, 95% CI=1.03-1.51, P=0.02; I2 =0%, P=0.60) but not PFS (HR=1.11, 95% CI=0.89-1.39, P=0.36; I2=0.0%, P=0.75) for ICI patients (Figure 3A and B). While aspirin didn’t reduce the survival of patients treated with ICI therapy, no matter OS (HR= 0.93, 95% CI = 0.78-1.10, P=0.27; I2=17%, P=.39) or PFS (HR=0.89, 95% CI=0.69-1.16, P=0.12; I2=59%, P=0.40) (Figure 3C and D).
Risk of publication bias
The funnel chart (supplementary figure 2) and the results of Begg's test and Egger's test analysis (Table 2) suggested that there was no significant publication bias except for in the overall analysis of PFS (PBegg's =0.027, PEgger's =0.012). Trim-and-fill analysis showed that publication bias did not affect the PFS results (HR=1.55, 95% CI=1.38-1.74, P<0.001).