| Literature DB >> 35685507 |
Jun Xia1, Jiping Zhu1, Lei Li1, Shiqin Xu2.
Abstract
Background: The influence of concomitant use of gastric acid suppressants (AS) on survival of patients with non-small-cell lung cancer (NSCLC) treated with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) is inconsistent according to previous studies. We performed a meta-analysis to evaluate the effect of additional AS in patients with NSCLC taking TKIs.Entities:
Mesh:
Substances:
Year: 2022 PMID: 35685507 PMCID: PMC9159195 DOI: 10.1155/2022/3102641
Source DB: PubMed Journal: Int J Clin Pract ISSN: 1368-5031 Impact factor: 3.149
Figure 1Flowchart of the database search and study identification.
Characteristics of the included studies.
| Study | Country | Design | Patient characteristics | Sample size | Mean age (years) | Male (%) | TKI used | Definition of AS use | Number of AS users | Outcomes and main results reported: HR (95% CI) | Variables adjusted |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Hilton 2013 | Canada | R | Advanced or metastatic NSCLC after standard chemotherapy had failed | 485 | 62 | 65 | Erlotinib | Self-reported PPIs or H2RAs users at baseline or during follow-up | 190 | PFS: 1.75 (1.43∼2.13), OS: 1.67 (1.34∼2.05) | Age, sex, PS, weight loss, time from diagnosis, response to prior therapy, histologic subtype, race, HGB, LDH, and current smoking |
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| Chu 2015 | Canada | R | Stage IIIB/IV NSCLC patients | 544 | 64 | 50 | Erlotinib | PPIs or H2RAs user confirmed by the database of prescription medications | 124 | PFS: 1.83 (1.48∼2.25), OS: 1.37 (1.11∼1.69) | Age, sex, PS, and histologic subtype |
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| Zenke 2016 | Japan | R | Patients with advanced NSCLC with EGFR mutations | 130 | 64 | 37 | Erlotinib or gefitinib | Medical records approved users of PPIs or H2RAs | 47 | PFS: 1.15 (0.73∼1.79), OS: 1.41 (0.83∼2.35) | Age, sex, PS, smoking, prior therapy, and bone metastasis |
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| Kumarakulasinghe 2016 | Singapore | R | Patients with advanced NSCLC with EGFR mutations | 157 | 62 | 53 | Erlotinib or gefitinib | Medical records approved users of PPIs or H2RAs | 55 | PFS: 1.37 (0.89∼2.12), OS: 1.47 (0.92∼2.35) | Age, sex, race, PS, CCI, smoking, brain and liver metastasis |
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| Chen 2016 | China | R | Patients with advanced NSCLC with EGFR mutations | 269 | 65 | 42 | First-generation EGFR-TKIs | Medical records approved users of PPIs or H2RAs | 57 | For PPIs: PFS: 1.42 (0.81∼2.49), OS: 2.27 (1.26∼4.11); for H2RAs: PFS: 1.19 (0.55∼2.57), OS: 1.46 0.92∼2.33); | Age, sex, DM, smoking, PS, histologic type, and bone, liver, or pleura metastasis |
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| Sedano 2018 | Spain | R | Stage III/IV NSCLC patients | 163 | 70 | 64 | Erlotinib or gefitinib | Medical records approved users of PPIs or H2RAs | 118 | PFS: 2.5 (1.61∼3.88) | Age, sex, PS, and treatment line |
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| Sharma 2019 | US | R | Old NSCLC patients | 7448 | 76 | 48 | Erlotinib | PPIs user confirmed by the database of prescription medications | 1616 | OS: 1.11 (1.02∼1.20) | Age, sex, and comorbidities |
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| Fang 2019 | China | R | NSCLC patients | 1278 | NR | 36 | Gefitinib | PPIs user confirmed by the database of prescription medications | 309 | OS: 1.67 (1.33∼2.09) | Age, sex, comorbidities, and income |
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| Kwok 2020 | China | R | Advanced lung AC with EGFR mutations | 193 | 68 | 28 | Gefitinib | Medical records approved users of PPIs or H2RAs | 61 | For PPIs: PFS: 3.38 (2.18∼5.25), OS: 2.52 (1.67∼3.79); for H2RAs: PFS: 2.27 (1.54∼3.52), OS: 1.30 (0.74∼2.62); | Age, sex, smoking, primary EGFR mutation and presence of brain metastasis |
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| Guo 2020 | China | R | Stage IIIB/IV NSCLC patients | 188 | 61 | 42 | Gefitinib | Medical records approved users of PPIs or H2RAs | 49 | PFS: 1.33 (0.78∼1.98) | Age, sex, PS, EGFR mutation, cancer stage, and brain metastasis |
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| Su 2020 | China | R | Stage IIIB/IV NSCLC patients with EGFR mutations | 853 | 66 | 36 | Gefitinib, erlotinib, and afatinib | Medical records approved users of PPIs or H2RAs | 92 | OS: 1.01 (0.75∼1.36) | Age, sex, PS, smoking, clinical stage, previous therapy, CCI, and histologic type |
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| Saito 2021 | Japan | R | Stage IIIB/IV NSCLC patients | 87 | 63 | 45 | Gefitinib | Medical records approved users of H2RAs | 31 | PFS: 0.95 (0.60∼1.48), OS: 0.86 (0.52∼1.43) | Age, sex, PS, smoking, EGFR mutation, clinical stage, histologic type, previous chemotherapy, and liver dysfunction |
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| Li 2021a | US | R | Patients with advanced NSCLC with EGFR-activating mutations | 235 | 64 | 37 | Dacomitinib | Medical records approved users of PPIs | 83 | PFS: 1.24 (0.84∼1.81), OS: 1.04 (0.70∼1.55) | Age, sex, race, baseline BW, PS, smoking, EGFR mutation type, number of target lesions, and organs with metastases |
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| Li 2021b | US | R | Patients with advanced NSCLC with EGFR-activating mutations | 229 | 63 | 42 | Gefitinib | Medical records approved users of PPIs | 70 | PFS: 1.13 (0.80∼1.59), OS:1.31 (0.89∼1.93) | Age, sex, race, baseline BW, PS, smoking, EGFR mutation type, number of target lesions, and organs with metastases |
The study by Li et al. (2021) included two cohorts using dacomitinib or gefitinib, respectively, and these two datasets were included independently. TKI, tyrosine kinase inhibitor; AS, acid suppressants; R, randomized; NSCLC, non-small-cell lung cancer; AC, adenocarcinoma; EGFR, epithelial growth factor receptor; PPIs, proton pump inhibitors; H2RAs, histamine type-2 receptor antagonists; PFS, progression-free survival; OS, overall survival; PS, performance status; HGB, hemoglobin; LDH, lactate dehydrogenase; CCI, Charlson Comorbidity Index; BW, body weight; DM, diabetes mellitus.
Details of study quality evaluation via the Newcastle–Ottawa scale.
| Study | Representativeness of the exposed cohort | Selection of the nonexposed cohort | Ascertainment of exposure | Outcome not present at baseline | Control for age | Control for other confounding factors | Assessment of outcome | Enough long follow-up duration | Adequacy of follow-up of cohorts | Total |
|---|---|---|---|---|---|---|---|---|---|---|
| Hilton 2013 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 8 |
| Chu 2015 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 9 |
| Zenke 2016 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 9 |
| Kumarakulasinghe 2016 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 9 |
| Chen 2016 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 9 |
| Sedano 2018 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 9 |
| Sharma 2019 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 7 |
| Fang 2019 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 8 |
| Kwok 2020 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 8 |
| Guo 2020 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 9 |
| Su 2020 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 9 |
| Saito 2021 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 9 |
| Li 2021 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 9 |
Figure 2Forest plots for the meta-analysis of the association between concomitant AS use and PFS in NSCLC patients taking TKIs. (a) Forest plots for the overall meta-analysis, (b) forest plots for the sensitivity analysis in patients with EGFR mutation, and (c) forest plots for the subgroup analysis according to AS used.
Figure 3Forest plots for the subgroup analyses of the association between concomitant AS use and PFS in NSCLC patients taking TKIs. (a) Subgroup analysis according to the country of the study and (b) subgroup analysis according to TKIs used.
Figure 4Forest plots for the meta-analysis of the association between concomitant AS use and OS in NSCLC patients taking TKIs. (a) Forest plots for the overall meta-analysis, (b) forest plots for the sensitivity analysis in patients with EGFR mutation, and (c) forest plots for the subgroup analysis according to AS used.
Figure 5Forest plots for the subgroup analyses of the association between concomitant AS use and OS in NSCLC patients taking TKIs. (a) Subgroup analysis according to the country of the study and (b) subgroup analysis according to TKIs used.
Figure 6Funnel plots for the publication bias underlying the meta-analyses. (a) funnel plots for the meta-analysis of the association between concomitant AS use and PFS in NSCLC patients taking TKIs and (b) funnel plots for the meta-analysis of the association between concomitant AS use and OS in NSCLC patients taking TKIs.