Impact of Use of Gastric-Acid Suppressants and Oral Anti-Cancer Agents on Survival Outcomes: A Systematic Review and Meta-Analysis
Abstract
:1. Introduction
2. Results
2.1. Overall Survival and Progression-Free Survival with GAS vs. no GAS
2.2. Subgroup Analysis
2.3. Overall Response Rate
2.4. Publication Bias
3. Discussion
4. Materials and Methods
4.1. Data Extraction and Quality Assessment
4.2. Statistical Analysis
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Author | Principal Institution(s) Involved | Study Design | Study Period | Number of Patients | Patients’ Disease Characteristics | Oral Anti-cancer Drug | Type of GAS |
---|---|---|---|---|---|---|---|
Ha, 2014 [23] | Cross Cancer Institute, Department of Oncology, Edmonton, Alberta, Canada | retrospective | 2006–2013 | 383 | mRCC | Sunitinib | PPI |
Sun, 2016 [27] | Cross Cancer Institute, Department of Oncology, Edmonton, Alberta, Canada | retrospective | 2008–2012 | 298 | Early stage CRC | Capecitabine | PPI |
Chu, 2015 [19] | Cross Cancer Institute, Department of Oncology, Edmonton, Alberta, Canada | retrospective | 2007–2012 | 507 | EGFR mutant advanced NSCLC | Erlotinib | PPI, H2RA |
Zenke, 2016 [30] | Department of Thoracic Oncology, National Cancer Center Hospital East, Kashiwa, Japan | retrospective | 2008–2011 | 130 | EGFR mutant advanced NSCLC | Gefitinib Erlotinib | PPI, H2RA |
Kumarakulasinghe, 2016 [24] | Department of Haematology-Oncology, National University Cancer Institute, Singapore | retrospective | 2008–2013 | 157 | EGFR mutant advanced NSCLC | Gefitinib Erlotinib | PPI, H2RA |
Chen, 2016 [18] | Chang Gung Memorial Hospital-Kaohsiung Medical Center, Chang Gung University College of Medicine, Kaohsiung, Taiwan | retrospective | 2010–2013 | 269 | EGFR mutant advanced NSCLC | EGFR TKIs NOS | PPI |
Graham, 2016 [21] | Department of Oncology, Cancer Centre of Southeastern Ontario, Queen’s University, Kingston | retrospective | 2005–2011 | 117 | CRC | NA | PPI |
Chu, 2017 [20] | Cross Cancer Institute, Department of Oncology, Edmonton, Alberta, Canada | retrospective analysis (phase III trial) | 2008–2012 | 545 | GEJC | Capecitabine | PPI |
Zhang, 2017 [31] | Guangdong Medical University Affiliated Longhua Central Hospital, Shenzhen, China | retrospective | 2008–2016 | 125 | CRC | Capecitabine | PPI |
Lalani, 2017 [16] | Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, USA | pooled analysis (phase II/III studies) | 2003–2013 | 2188 | mRCC | Sunitinib Axitinib Sorafenib | PPI |
McAlister, 2018 [25] | Vanderbilt-Ingram Cancer Center, Nashville, USA | retrospective | 2010–2015 | 90 | mRCC | Pazopanib | PPI, H2RA |
Tvingsholm, 2018 [28] | Danish Cancer Society Research Center, Copenhagen, Denmark (Danish Cancer Registry) | retrospective | 1995–2011 | 353,071 | Solid Tumors (Danish Cancer Registry) | NA | PPI |
Wong, 2019 [29] | Cross Cancer Institute, Department of Oncology, Edmonton, Alberta, Canada | retrospective | 2004–2013 | 389 | stage II-III CRC | Capecitabine | PPI |
Fang, 2019 [21] | Chang Gung Memorial Hospital, Chiayi Branch, Puzi City, Chiayi County, Taiwan | retrospective | 1997–2013 | 1278 | EGFR mutant advanced NSCLC | Gefitinib | PPI |
Mir, 2019 [17] | Gustave Roussy, Sarcoma Group, Villejuif, France | retrospective | 2005–2007 2008–2010 | 333 | STS | Pazopanib | PPI, H2RA |
Sharma, 2019 [26] | The University of Mississippi, Oxford, Mississippi, USA (SEER Database) | retrospective | 2007–2012 | 12,538 | Solid Tumors (SEER Database) | TKIs | PPI |
Authors, Year | Median Follow-Up, Months | Criteria for Overlapping between GAS and Anti-cancer Treatment (Time Overlapping %) | Therapeutic Approach, n (%) | ORR | OS HR (95% CI) * | PFS HR (95% CI) * | Type of Analysis | Quality NOS Score |
---|---|---|---|---|---|---|---|---|
Ha, 2014 [23] | NA | GAS: 45 (20%) | NA | 1.43 (0.95–2.15) | 1.36 (0.92–2.01) | UVA | 5 | |
100 | No GAS: 186 (80%) | NA | ||||||
Sun, 2016 [27] | NA | GAS: 77 (26%) | NA | 0.94 (0.49–1.78) | 0.61 (0.34–1.08) | MVA | 5 | |
Any PPI prescription | No GAS: 202 (74%) | NA | ||||||
Chu, 2015 [19] | NA | GAS: 124 (25%) | 5.6% | 1.37 (1.11–1.69) | 1.83 (1.48–2.25) | MVA | 6 | |
≥20 | No GAS: 383 (75%) | 18.5% | ||||||
Zenke, 2016 [30] | 36 (10.1–85.2) | GAS: 47 (36%) | 64% | 1.41 (0.83–2.35) | 1.15 (0.73–1.79) | MVA | 7 | |
PPI/H2RA sequentially or concurrently to anti-EGFR | No GAS: 83 (64%) | 63% | ||||||
Kumarakulasinghe, 2016 [24] | 50 | GAS: 55 (35%) | NA | 1.37 (0.89–2.12) | 1.47 (0.92–2.35) | MVA | 7 | |
≥30 | No GAS: 102 (65%) | NA | ||||||
Chen, 2016 [18] | 24.5 | GAS: 57 (21%) | NA | 2.27 (1.26–4.11) | 2.00 (0.96–4.17) | MVA | 6 | |
≥30 | No GAS: 212 (79%) | NA | ||||||
Graham, 2016 [21] | NA | GAS: 117 (9%) | NA | 1.34 (1.01–1.79) | NA | MVA | 7 | |
NA | No GAS: 1187 (91%) | NA | ||||||
Chu, 2017 [20] | NA | GAS: 119 (44%) | 36% | 1.41 (1.11–1.71) | 1.68 (1.42–1.94) | MVA | 5 | |
≥20 | No GAS: 155 (56%) | 42% | ||||||
Zhang, 2017 [31] | 66 | GAS: 29 (23%) | 52.2% | 0.30 (0.09–0.99) | 0.37 (0.11–1.23) * | UVA *, MVA | 7 | |
≥200 mg PPI | No GAS: 96 (77%) | 36.5% | ||||||
Lalani, 2017 [16] | NA | GAS: 120 (5%) | 23.3% | 1.05 (0.77–1.44) | 1.02 (0.79–1.30) | MVA | 5 | |
≥1 dose PPI | No GAS: 2068(95%) | 27.4% | ||||||
McAlister, 2018 [25] | NA | GAS: 66 (73%) | NA | 0.99 (0.51–1.93) | 1.25 (0.76–2.07) | MVA | 5 | |
≥90 days | No GAS: 24 (27%) | NA | ||||||
Tvingsholm, 2018 [28] | 1.52 (0.50–3.89) | GAS: 41,218 (11.7%) | NA | 1.29 (1.27–1.31) | NA | MVA | 7 | |
≥2 prescriptions within 6 months | No GAS: 311,853 (88.3%) | NA | ||||||
Wong, 2019 [29] | NA | GAS: 50 (23.4%) | NA | 1.68 (0.75–3.80) | 2.20 (1.14–4.25) | MVA | 5 | |
Any time PPI during capecitabine | No GAS: 164 (76.6%) | NA | ||||||
Fang, 2019 [21] | NA | GAS: 309 (24%) | NA | 1.67 (1.33–2.09) | 0.99 (0.80–1.23) | MVA | 7 | |
≥20 | No GAS: 969 (76%) | NA | ||||||
Mir, 2019 [17] | 27.6 (22.9–35.4) | GAS: 59 (18%) | NA | 1.81 (1.31–2.49) | 1.49 (1.11–1.99) | MVA | 6 | |
≥80 | No GAS: 273 (82%) | NA | ||||||
Sharma, 2019 [26] | NA | GAS: 2843 (22.7%) | NA | 1.10 (1.04–1.17) | NA | MVA | 8 | |
≥30 days within 3 months | No GAS: 9695 (77.3%) | NA |
Item No | Recommendation | Reported on Page No |
---|---|---|
Reporting of background should include | ||
1 | Problem definition | 1,2 |
2 | Hypothesis statement | 1,2 |
3 | Description of study outcome(s) | 11 |
4 | Type of exposure or intervention used | 11 |
5 | Type of study designs used | 11 |
6 | Study population | 11 |
Reporting of search strategy should include | ||
7 | Qualifications of searchers (e.g., librarians and investigators) | 1 |
8 | Search strategy, including time period included in the synthesis and key words | 11 |
9 | Effort to include all available studies, including contact with authors | 11 |
10 | Databases and registries searched | 11 |
11 | Search software used, name and version, including special features used (e.g., explosion) | 11 |
12 | Use of hand searching (e.g., reference lists of obtained articles) | 11, Figure 1 |
13 | List of citations located and those excluded, including justification | 11, Figure 1 |
14 | Method of addressing articles published in languages other than English | 11 |
15 | Method of handling abstracts and unpublished studies | 11 |
16 | Description of any contact with authors | 11 |
Reporting of methods should include | ||
17 | Description of relevance or appropriateness of studies assembled for assessing the hypothesis to be tested | 11 |
18 | Rationale for the selection and coding of data (e.g., sound clinical principles or convenience) | 11 |
19 | Documentation of how data were classified and coded (e.g., multiple raters, blinding and interrater reliability) | 11 |
20 | Assessment of confounding (e.g., comparability of cases and controls in studies where appropriate) | 11 |
21 | Assessment of study quality, including blinding of quality assessors, stratification or regression on possible predictors of study results | 11 |
22 | Assessment of heterogeneity | 7,8, Figure 5 |
23 | Description of statistical methods (e.g., complete description of fixed or random effects models, justification of whether the chosen models account for predictors of study results, dose-response models, or cumulative meta-analysis) in sufficient detail to be replicated | 12 |
24 | Provision of appropriate tables and graphics | Figure 1 |
Reporting of results should include | ||
25 | Graphic summarizing individual study estimates and overall estimate | Table 1 and Table 2 |
26 | Table giving descriptive information for each study included | Table 1 and Table 2 |
27 | Results of sensitivity testing (e.g., subgroup analysis) | 2, 6–8, Figure 2, Figure 3 and Figure 4 |
28 | Indication of statistical uncertainty of findings | 7,8, Figure 5 |
29 | Quantitative assessment of bias (e.g., publication bias) | 7,8, Figure 5 |
30 | Justification for exclusion (e.g., exclusion of non-English language citations) | Figure 1, 11 |
31 | Assessment of quality of included studies | 11 |
Reporting of conclusions should include | ||
32 | Consideration of alternative explanations for observed results | 8,9 |
33 | Generalization of the conclusions (i.e., appropriate for the data presented and within the domain of the literature review) | 12 |
34 | Guidelines for future research | 8,9,11 |
35 | Disclosure of funding source | 12 |
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Share and Cite
Indini, A.; Petrelli, F.; Tomasello, G.; Rijavec, E.; Facciorusso, A.; Grossi, F.; Ghidini, M. Impact of Use of Gastric-Acid Suppressants and Oral Anti-Cancer Agents on Survival Outcomes: A Systematic Review and Meta-Analysis. Cancers 2020, 12, 998. https://doi.org/10.3390/cancers12040998
Indini A, Petrelli F, Tomasello G, Rijavec E, Facciorusso A, Grossi F, Ghidini M. Impact of Use of Gastric-Acid Suppressants and Oral Anti-Cancer Agents on Survival Outcomes: A Systematic Review and Meta-Analysis. Cancers. 2020; 12(4):998. https://doi.org/10.3390/cancers12040998
Chicago/Turabian StyleIndini, Alice, Fausto Petrelli, Gianluca Tomasello, Erika Rijavec, Antonio Facciorusso, Francesco Grossi, and Michele Ghidini. 2020. "Impact of Use of Gastric-Acid Suppressants and Oral Anti-Cancer Agents on Survival Outcomes: A Systematic Review and Meta-Analysis" Cancers 12, no. 4: 998. https://doi.org/10.3390/cancers12040998