| Literature DB >> 30881522 |
Long Yao1, Mengke Liu2, Yunlong Huang1, Kaiming Wu1, Xin Huang1, Yuan Zhao1, Wei He3, Renquan Zhang1.
Abstract
BACKGROUND: Antidiabetic medications (ADMs) can alter the risk of different types of cancer, but the relationship between lung cancer incidence and metformin remains controversial. Our aim was to quantitatively estimate the relationship between incidences of lung cancer and metformin in patients with diabetes in this meta-analysis.Entities:
Mesh:
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Year: 2019 PMID: 30881522 PMCID: PMC6387718 DOI: 10.1155/2019/6230162
Source DB: PubMed Journal: Dis Markers ISSN: 0278-0240 Impact factor: 3.434
Figure 1Flow chart of study selection.
Characteristics of the included studies.
| First author | Year | Country | Study design | Time period | Case source | Comparison | Estimates and 95% CI | Study quality | |
|---|---|---|---|---|---|---|---|---|---|
| Unadjusted | Adjusted | ||||||||
| Libby | 2009 | UK | Cohort (PB) | 1994-2003 | The resident population of Tayside Health Board | Metformin vs. nonmetformin | 0.49 (0.32-0.74) | 0.70 (0.43-1.15) | 8 |
| Lai | 2012 | Taiwan, China | Cohort (PB) | 2000-2008 | National Health Research Institutes in Taiwan | Metformin vs. nonmetformin | 0.43 (0.29-0.63) | 0.55 (0.37-0.82) | 7 |
| Ruiter | 2012 | Netherlands | Cohort (HB) | 1998-2008 | PHARMO Record Linkage System | Metformin vs. Sul | NA | 0.87 (0.84-0.91) | 7 |
| Neumann | 2012 | France | Cohort (PB) | 2006-2009 | French national health insurance information | Metformin vs. nonmetformin | NA | 0.88 (0.84-0.92) | 7 |
| Mazzone | 2012 | USA | Case-control (HB) | 2001-2011 | Cleveland Clinic Health System | Metformin vs. nonmetformin | NA | 0.48 (0.28-0.81) | 6 |
| Hsieh | 2012 | Taiwan, China | Case-control (PB) | 2000-2008 | Taiwan's National Health Insurance Medical Claims Database | Metformin vs. Sul | NA | 0.64 (0.45-0.9) | 7 |
| NA | |||||||||
| Luo | 2012 | USA | Cohort (HB) | 1993-2010 | Women's Health Initiative (WHI) study | Metformin vs. nonmetformin | NA | 1.32 (0.76-2.28) | 8 |
| Smiechowski | 2013 | Canada | Case-control (PB) | 1988-2009 | U.K. General Practice Research database | Metformin vs. nonmetformin | 0.97 (NA) | 0.94 (0.76-1.17) | 8 |
| Wang | 2013 | Taiwan, China | Cohort (PB) | 1998-2009 | National Health Insurance datasets | Metformin vs. nonmetformin | NA | 1.11 (0.94-1.47) | 7 |
| Tsilidis | 2014 | UK | Cohort (HB) | 1987-2010 | U.K. Clinical Practice Research Datalink | Metformin vs. Sul | NA | 0.96 (0.89-1.04) | 8 |
| Sakoda | 2015 | USA | Cohort (PB) | 1997-2012 | KPNC Diabetes Registry | Metformin vs. nonmetformin | NA | 1.02 (0.85-1.22) | 8 |
| Kowall | 2015 | Germany and the UK | Cohort (HB) | 1995-2013 | Disease Analyzer database | Metformin vs. Sul | 0.81 (0.65-1.01) | 1.04 (0.82-1.31) | 7 |
| 1.28 (0.81-2.04) | 1.03 (0.64-1.64) | ||||||||
| Chen | 2015 | Taiwan, China | Cohort (HB) | 1998-2008 | Longitudinal Health Insurance Dataset | Metformin vs. Sul | 0.72 (0.58-0.88) | 0.74 (0.60-0.90) | 8 |
| 0.85 (0.61-1.18) | 0.95 (0.68-1.35) | ||||||||
Abbreviations: PB: population-based; HB: hospital-based; NA: not available; KPNC: the Kaiser Permanente Northern California Diabetes Registry; Sul: sulfonylurea; Ins: insulin.
Adjustment variables of the included studies.
| Study | Adjustment |
|---|---|
| Libby et al. | Age, sex, smoking, deprivation, BMI, HbA1C, insulin use, and sulfonylurea use |
| Lai et al. | Sex, age, pulmonary tuberculosis, chronic obstructive pulmonary disease, and propensity score |
| Ruiter et al. | Age at first OGLD prescription, sex, year in which the first OGLD prescription was dispensed, number of unique drugs used in the year, and number of hospitalizations in the year before the start of the OGLD |
| Neumann et al. | Age, sex (when applicable), and exposure to glucose-lowering drugs |
| Mazzone et al. | Medication use, BMI, HbA1C, and pack-years of smoking |
| Hsieh et al. | Sex and age |
| Luo et al. | Age, ethnicity, education, BMI, waist-to-hip ratio, recreational physical activity, alcohol intake, total energy intake, percent calories from fat, total fruit intake, total vegetable intake, history of hormone therapy use, and different treatment assignments for clinical trials |
| Smiechowski et al. | Diabetes duration, HbA1c, obesity, smoking, excessive alcohol use, previous cancer, chronic obstructive pulmonary disease, asthma, nonsteroidal anti-inflammatory drugs, aspirin, statins, and other antidiabetic drugs |
| Wang et al. | Age, sex, and occupation |
| Tsilidis et al. | Smoking status, BMI, alcohol consumption, use of aspirin or NSAIDs and statins, diabetes duration, and year of first antidiabetes prescription |
| Sakoda et al. | Gender, race/ethnicity, birth year, diabetes duration, BMI, alcohol use, Charlson comorbidity index, and other diabetes medications |
| Kowall et al. | Age at first diabetes medication, sex, country (the UK or Germany), time between first diagnosis of diabetes and prescription of first diabetes drug, obesity, hypertension, hyperlipidemia, prevalence of microcomplications (retinopathy, neuropathy, or nephropathy), Charlson index, use of antihypertensives, use of antithrombotic agents, use of aspirin, use of statins, use of nonsteroidal anti-inflammatory drugs, and use of contraceptives |
| Chen et al. | Age, sex, Charlson comorbidity index, smoking-related comorbidities, alcohol use disorders, morbid smoking history (status and pack-years), education, income level, creatinine level, HbA1c level, obesity, pancreatitis, hypertension, monthly income, and urbanization level |
Abbreviations: BMI: body mass index; HbA1C: glycosylated hemoglobin; OGLD: oral glucose-lowering drugs; NSAID: nonsteroidal anti-inflammatory drugs.
Figure 2Random-effect meta-analysis of the association between metformin and lung cancer.
A subgroup analysis of metformin use and lung cancer risk in patients with diabetes.
| Subgroups | Pooled RR | Heterogeneity | ||||
|---|---|---|---|---|---|---|
|
| RR (95% CI) |
|
|
|
| |
| Study design | ||||||
| Case-control | 3 | 0.70 (0.47-1.03) | 0.07 | 7.51 | 0.02 | 73 |
| Cohort | 10 | 0.91 (0.85-0.98) | 0.008 | 26.33 | 0.002 | 66 |
| Study location | ||||||
| Asia | 4 | 0.76 (0.55-1.06) | 0.1 | 16.89 | 0.0007 | 82 |
| North America | 4 | 0.92 (0.71-1.19) | 0.51 | 8.43 | 0.04 | 64 |
| Europe | 5 | 0.90 (0.86-0.94) | <0.0001 | 7.33 | 0.12 | 45 |
| Source of case | ||||||
| Population-based | 7 | 0.88 (0.76-1.01) | 0.07 | 18.59 | 0.005 | 68 |
| Hospital-based | 6 | 0.89 (0.80-0.99) | 0.04 | 16.88 | 0.005 | 70 |
| Control drugs | ||||||
| None | 8 | 0.89 (0.77-1.03) | 0.13 | 22.37 | 0.002 | 69 |
| Sulfonylurea | 5 | 0.91 (0.86-0.96) | 0.001 | 5.09 | 0.28 | 21 |
| Insulin | 3 | 0.97 (0.75-1.26) | 0.84 | 0.06 | 0.97 | 0 |
| Adjustment | ||||||
| BMI | 8 | 0.91 (0.80-1.03) | 0.12 | 16.41 | 0.02 | 57 |
| Smoking | 6 | 0.86 (0.75-1.00) | 0.05 | 14.11 | 0.01 | 65 |
| HbA1C | 4 | 0.83 (0.65-1.07) | 0.16 | 8.31 | 0.04 | 64 |
| Alcohol | 5 | 0.93 (0.83-1.05) | 0.27 | 8.07 | 0.09 | 50 |
| Glucose-lowering drugs | 4 | 0.90 (0.84-0.97) | 0.004 | 3.51 | 0.32 | 15 |
Figure 3Publication bias detected by funnel plot.