Prevalence and influencing factors of pulmonary nodules in hospitalized patients with diabetes
Highlight box
Key findings
• The prevalence of pulmonary nodules is high in hospitalized patients with diabetes.
What is known and what is new?
• Individuals with diabetes constitute a group at high risk of lung cancer. Pulmonary nodules are an early manifestation of many lung cancers. There is an urgent need for data that can inform the management of pulmonary nodules in patients with diabetes.
• Older age, smoking, and dipeptidyl peptidase 4 inhibitor use are independent risk factors for the development of pulmonary nodules in patients with diabetes.
What is the implication, and what should change now?
• In order to improve the quality of life of diabetic patients, it is recommended to popularize the early detection of pulmonary nodules in this group, so as to detect lung cancer early.
Introduction
With the improvement of living standards and health awareness, chest computed tomography (CT) has become a routine physical examination item, and the detection rate of pulmonary nodules has risen considerably. A large retrospective study in Japan showed that the risk of cancer in patients with diabetes was significantly increased in both men and women, and after adjustments for age, obesity, and smoking, the risk of lung cancer in patients with diabetes increased by 53% in men and 61% in women (1). According to the Fleischner Society in the United States [2017], among the 4.8 million people examined via CT, more than 1.5 million people were diagnosed with lung nodules, of whom nearly 63,000 were diagnosed with lung cancer (2). However, there is a lack of epidemiological data on pulmonary nodules in patients with diabetes in China or internationally. From January 2020 to November 2022, during the period of strict epidemic prevention of novel coronavirus infection in China, chest CT became a routine screening item for those patients hospitalized with diabetes. Therefore, we retrospectively investigated the incidence of pulmonary nodules in hospitalized patients with diabetes and analyzed the influencing factors to provide preliminary data for guiding the management of diabetic pulmonary nodules. We present this article in accordance with the STROBE reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1374/rc).
Methods
Study design and participants
This is a retrospective study. From January 2020 to November 2022, clinical data of patients with diabetes hospitalized in the Department of Endocrinology and Metabolism in the North District of Suzhou Municipal Hospital were collected. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). This study was approved by the Ethics Committee of the Suzhou Municipal Hospital (No. K-2022-118-H01), and the requirement for informed consent of the patients was waived due to the retrospective nature of the analysis.
The inclusion criteria were as follows: (I) hospitalized patients over 18 years old who had been diagnosed with diabetes mellitus according to the World Health Organization diagnostic criteria [1999] and (II) complete low-dose spiral CT scan of the chest, with results of the first chest CT examination for those who had undergone multiple chest CT examinations being used for analysis. Meanwhile, the exclusion criteria were as follows: (I) history of acute and chronic pulmonary diseases; (II) acute complications of diabetes; (III) pregnant and lactating women; and (IV) severe liver and kidney insufficiency.
For grouping, according to the CT examination report, patients with no pulmonary nodules were included in the group without pulmonary nodules, while the patients with pulmonary nodules were divided into three subgroups according to the following maximum nodule diameter: <5, ≥5 and <10, and ≥10 and ≤30 mm.
Anthropometric measurements
Data on gender, age, duration of diabetes, height, weight, systolic blood pressure (SBP), diastolic blood pressure (DBP), smoking history, diabetes treatment regimen, and statin drug use history were collected. Body mass index (BMI) was calculated as follows: BMI = weight (kg)/[height (m)]2. According to the Guidelines for the Prevention and Control of Overweight and Obesity in Chinese Adults (3), BMI <18.5 kg/m2 is defined as emaciated, BMI >18.5 and <24 kg/m2 as normal, BMI ≥24 and <28 kg/m2 as overweight, and BMI ≥28 kg/m2 as obese.
Biochemical measurements
Fasting plasma glucose (FPG), glycated hemoglobin A1c (HbA1c), glycated albumin, fasting C-peptide, 2-hour postprandial C-peptide, glutamic pyruvic transaminase (GPT), glutamic oxaloacetic transaminase (GOT), serum creatinine (Scr), uric acid (UA), total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), serum tumor markers [including alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA125), carbohydrate antigen 199 (CA199)], C-reactive protein (CRP), and homocysteine (Hcy) levels were collected.
The diagnosis of diabetic retinopathy (DR) was based on the criteria of the International Clinical Classification of Diabetic Retinopathy [2002] (4). The estimated glomerular filtration rate (eGFR) was calculated according to the Modification of Diet in Renal Disease (MDRD) equation (see http://www.nkdep.nih.gov). Proteinuria was defined as a positive urine protein or urine albumin creatine ratio (UACR) of ≥30 mg/g, which excluded urinary tract infection, nephritis, urinary tract obstruction, or fever (5). The insulin resistance index was determined with Homeostatic Model Assessment for Insulin Resistance 2 (HOMA2IR) (see https://www.dtu.ox.ac.uk/homacalculator/).
Radiological examinations
A Brilliance iCT256 CT scanner (Philips, Amsterdam, the Netherlands) was used to perform chest CT examination on the patients, and two senior doctors from the Radiology Department of Suzhou Municipal Hospital jointly read the images and issued a CT examination report. According to the 2016 Asian Consensus Guidelines: Evaluation of Pulmonary Nodules (6), pulmonary nodules refer to focal, round-like, and dense solid or subsolid lung shadows of ≤3 cm in diameter on CT images.
According to the Chinese Expert Consensus on the Diagnosis and Treatment of Pulmonary Nodules [2018] (7), pulmonary nodules with a diameter of <5 mm are defined as micronodules, and those with a diameter of 5–10 mm are defined as small nodules. A solitary pulmonary nodule is defined as a single nodule, while multiple pulmonary nodules are defined as the presence of two or more nodules. For individuals with multiple pulmonary nodules, the maximum diameter of the largest nodule was used for analysis in this study. For solitary pulmonary nodules, the location of the nodules was further recorded and divided into the right upper lobe, middle lobe, lower lobe, left upper lobe, and lower lobe. Pulmonary nodules were classified according to density and were divided into solid pulmonary nodules and subsolid pulmonary nodules. Subsolid pulmonary nodules included pure ground-glass nodules (pGGNs) and mixed ground-glass nodules (mGGNs) with both ground-glass and solid densities.
Statistical methods
Data analysis was performed using SPSS 25.0 (IBM Corp., Armonk, NY, USA). Normally distributed data are expressed as the mean ± standard deviation. Nonnormally distributed variables were logarithmically transformed before analysis and are expressed as the median and interquartile range. The relationships between pulmonary nodules and variables including age, diabetes duration, BMI, SBP, DBP, FPG, HbA1c, glycated albumin, fasting C-peptide, 2-hour postprandial C-peptide, GPT, GOT, AFP, CEA, CA125, CA199, and Hcy, among others, were analyzed by one-way analysis of variance or the Mann-Whitney test. The Chi-square test was used to compare groups with regard to frequency and percentage. Risk factor analysis was performed using multinomial logistic regression analysis. Statistical significance was indicated by a P value <0.05.
Results
Prevalence and imaging characteristics of pulmonary nodules in patients with diabetes
In this study, a total of 1,864 inpatients with diabetes were included in the analysis. Among these patients, 1,407 were found to have pulmonary nodules, representing a total prevalence rate of 75.48% (1,407/1,864), of which 22.53% were single nodules (317/1,407) and the remainder multiple nodules. Of the single pulmonary nodules, 49.53% were located in the upper lobe of the lung (157/317). According to pulmonary nodules size, the diameter of nodules ≤5 mm accounted for 43.43% (611/1,407) of the nodules, those ≥5 and <10 mm for 51.03% (718/1,407), and those ≥10 and ≤30 mm for 5.54% (78/1,407). According to pulmonary nodules nature, solid nodules accounted for 57.21% (805/1,407) of nodules, pGGNs accounted for 13.08% (184/1,407), and mGGNs accounted for 29.71% (418/1,407).
Comparison of general data between patients with diabetes mellitus in the no pulmonary nodules group and the pulmonary nodules group
According to chest CT, the patients were divided into a pulmonary nodules group (1,407 cases, 75.48%) and no pulmonary nodules (457 cases, 24.52%). The age, smoking rate, and dipeptidyl peptidase 4 (DPP4) inhibitor use rate of the no pulmonary nodule group were lower than those of the nodule group, while the fasting C-peptide, 2-hour postprandial C-peptide, insulin resistance index level, and proteinuria incidence were higher than those of the nodule group (all P values <0.05).
According to the size of the nodule diameter, the patients in the nodule group were further divided into three subgroups according to the following nodule diameters: <5, ≥5 and <10, and ≥10 and ≤30 mm. The no pulmonary nodules group was compared with the three subgroups. (I) Compared with the group with a nodule diameter <5 mm, the no pulmonary nodules group had a lower proportion of males and smoking but a higher incidence of proteinuria (all P values <0.05). (II) Compared with the group with nodule diameter ≥5 and <10 mm, the nodule group had lower age, male ratio, proportion of smokers, and DPP4 inhibitor and insulin use rates but a higher rate of proteinuria (all P values <0.05). (III) Compared to the group with a nodule diameter ≥10 and ≤30 mm, the nodule group had a lower age, male ratio, and smoking and insulin use rates but higher rates of proteinuria (all P values <0.05).
The comparison of subgroups in the nodule group yielded the following results: (I) compared with the group with a nodule diameter of ≥5 and <10 mm and the group with a nodule diameter ≥10 and ≤30 mm, the group with a nodule diameter <5 mm had a lower age, male ratio, and smoking and insulin use rates (all P values <0.05); (II) compared with the group with a nodule diameter ≥10 and ≤30 mm, the group with a diameter ≥5 and <10 mm had lower age, male ratio, and smoking and insulin use rates but higher rates of DPP4 inhibitor use (all P values <0.05). There were no significant differences in disease course, BMI, SBP, DBP, DR, other hypoglycemic drugs, or statin use between the groups (Table 1).
Table 1
| Variables | No pulmonary nodules group (n=457) | Diameter <5 mm group (n=611) | Diameter ≥5 and <10 mm group (n=718) | Diameter ≥10 and ≤30 mm group (n=78) | P value |
|---|---|---|---|---|---|
| Male | 212 (46.39) | 344 (56.30)† | 428 (59.61)†,‡ | 50 (64.10)†,‡,§ | <0.005 |
| Age (years) | 59.25±15.33 | 58.82±13.56 | 62.11±13.33†,‡ | 67.00±12.55†,‡,§ | <0.005 |
| Disease course (years) | 8.00 (1.00, 13.00) | 6.00 (1.00, 13.00) | 8.00 (2.00, 14.25) | 10.00 (4.50, 15.00) | 0.051 |
| BMI (kg/m2) | 0.92 | ||||
| <18.5 | 13 (2.84) | 16 (2.62) | 18 (2.51) | 3 (3.85) | |
| ≥18.5 and <24 | 155 (33.92) | 238 (38.95) | 266 (37.05) | 28 (35.90) | |
| ≥24 and <28 | 164 (35.89) | 221 (36.17) | 274 (38.16) | 28 (35.90) | |
| ≥28 | 97 (21.23) | 121 (19.80) | 132 (18.38) | 14 (17.95) | |
| SBP (mmHg) | 128.30±20.55 | 125.68±18.60 | 127.92±18.93 | 130.92±21.04 | 0.73 |
| DBP (mmHg) | 72.13±11.88 | 71.98±11.34 | 71.61±11.70 | 71.92±10.54 | 0.88 |
| DR | 62 (13.57) | 87 (14.24) | 112 (15.60) | 14 (17.95) | 0.64 |
| Proteinuria | 80 (17.51) | 75 (12.27)† | 88 (12.26)† | 12 (15.38)† | 0.044 |
| Smoke | 132 (28.88) | 205 (33.55)† | 284 (39.55)†,‡ | 33 (42.31)†,‡,§ | 0.001 |
| Drug use | |||||
| Metformin | 177 (38.73) | 227 (37.15) | 273 (38.02) | 31 (39.74) | 0.94 |
| Sulfonylureas | 116 (25.38) | 159 (26.02) | 187 (26.04) | 17 (21.79) | 0.87 |
| Glinide | 16 (3.50) | 18 (2.95) | 31 (4.32) | 5 (6.41) | 0.34 |
| Glucosidase inhibitor | 78 (17.07) | 102 (16.69) | 128 (17.83) | 13 (16.67) | 0.95 |
| Thiazolidinedione | 27 (5.91) | 28 (4.58) | 42 (5.85) | 5 (6.41) | 0.11 |
| DPP4 inhibitor | 30 (6.56) | 60 (9.82) | 82 (11.42)† | 5 (6.41)§ | 0.03 |
| SGLT2 inhibitor | 34 (7.44) | 55 (9.00) | 64 (8.91) | 9 (11.54) | 0.61 |
| Insulin | 138 (30.20) | 173 (28.31) | 232 (32.31)†,‡ | 34 (43.59)†,‡,§ | 0.01 |
| GLP-1RA | 9 (1.97) | 9 (1.47) | 6 (0.84) | 1 (1.28) | 0.42 |
| Statins | 58 (12.69) | 80 (13.09) | 84 (11.70) | 10 (12.82) | 0.89 |
Data are expressed as the n (%), mean ± standard deviation, or median (interquartile range). Parameters among the four groups were compared with analysis of variance, Kruskal-Wallis test, or Chi-square test. †, P<0.05 compared with the no pulmonary nodules group; ‡, P<0.05 compared with the diameter <5 mm group; §, P<0.05 compared with the diameter ≥5 and <10 mm group. 1 mmHg =0.133 kPa. BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; DR, diabetic retinopathy; DPP4, dipeptidyl peptidase 4; SGLT2, sodium-dependent glucose transporter 2; GLP-1RA, glucagon-like peptide-1 receptor agonist.
Comparison of clinical indicators of patients with diabetes mellitus between the no pulmonary nodules group and the pulmonary nodules groups
Compared with the group with a nodule diameter ≥5 and <10 mm and that with a diameter ≥10 and ≤30 mm group, the no pulmonary nodules group and group with a diameter <5 mm group had a higher fasting and 2-hour postprandial C-peptide level, LDL-C, and HOMA2IR score but a lower Hcy level (all P values <0.05). Compared with the group with a nodule diameter ≥10 and ≤30 mm, the group with a diameter ≥5 and <10 mm had a higher LDL-C level and lower Hcy level (all P values <0.05). There were no significant differences in FPG, HbA1c, glycosylated albumin, GPT, GOT, Scr, eGFR, UA, CRP, TC, TG, HDL-C, AFP, CEA, CA125, or CA199 levels between the groups (Table 2).
Table 2
| Variables | No pulmonary nodules group | Diameter <5 mm group | Diameter ≥5 and <10 mm group | Diameter ≥10 and ≤30 mm group | P value | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Median (interquartile range) |
Number of cases | Median (interquartile range) |
Number of cases | Median (interquartile range) |
Number of cases | Median (interquartile range) |
Number of cases | |||||
| FPG (mmol/L) | 7.20 (5.50, 9.37) | 448 | 7.37 (5.72, 9.81) | 604 | 6.96 (5.47, 9.45) | 691 | 6.92 (5.33, 9.00) | 71 | 0.51 | |||
| FCP (nmol/L) | 1.08 (0.48, 2.24) | 448 | 1.00 (0.51, 2.02) | 604 | 0.78 (0.38, 1.61)†,‡ | 691 | 0.81 (0.38, 1.48)†,‡ | 71 | 0.002 | |||
| 2-hour postprandial C-peptide (nmol/L) | 2.23 (1.06, 4.94) | 448 | 2.25 (1.06, 4.37) | 604 | 1.70 (0.83, 3.68)†,‡ | 691 | 1.90 (0.90, 4.14)†,‡ | 71 | 0.007 | |||
| HbA1c (%) | 8.79 (7.91, 10.36) | 435 | 8.83 (7.12, 10.40) | 598 | 8.77 (7.14, 10.62) | 678 | 8.66 (7.08, 10.98) | 65 | 0.77 | |||
| Glycated albumin (%) | 25.30 (19.80, 31.30) | 435 | 24.90 (18.83, 31.20) | 598 | 24.30 (19.10, 30.90) | 678 | 25.20 (20.50, 34.15) | 65 | 0.26 | |||
| HOMA2IR | 2.79 (1.24, 5.66) | 448 | 2.60 (1.30, 5.26) | 604 | 2.08 (0.97, 4.13)†,‡ | 691 | 2.11 (1.06, 3.99)†,‡ | 71 | 0.04 | |||
| GOT (U/L) | 17.90 (12.10, 30.50) | 423 | 19.25 (12.90, 31.85) | 581 | 17.95 (12.80, 27.03) | 664 | 15.15 (12.45, 25.95) | 61 | 0.13 | |||
| GPT (U/L) | 19.70 (15.15, 28.45) | 423 | 19.75 (15.80, 27.00) | 581 | 19.90 (15.88, 26.10) | 664 | 19.35 (15.93, 25.90) | 61 | 0.28 | |||
| Scr (μmol/L) | 67.20 (54.50, 83.80) | 430 | 66.05 (55.25, 80.93) | 585 | 68.00 (55.65, 83.55) | 673 | 72.20 (59.35, 90.08) | 63 | 0.051 | |||
| eGFR (mL·min−1·1.73−1·m−2) | 100.45 (76.40, 125.13) | 430 | 101.72 (44.71, 103.52) | 585 | 80.46 (46.33, 107.74) | 673 | 76.29 (47.97, 110.66) | 63 | 0.48 | |||
| UA (μmol/L) | 342.07±114.66 | 430 | 331.32±109.26 | 585 | 329.92±98.29 | 673 | 349.74±120.64 | 63 | 0.15 | |||
| CRP (mg/L) | 1.83 (0.95, 5.57) | 428 | 1.77 (0.92, 4.61) | 580 | 1.84 (0.90, 4.78) | 657 | 2.66 (1.15, 6.79) | 55 | 0.19 | |||
| TC (mmol/L) | 4.59±1.24 | 420 | 4.69±1.29 | 582 | 4.54±1.29 | 640 | 4.36±1.22 | 59 | 0.06 | |||
| TG (mmol/L) | 1.38 (0.99, 2.12) | 420 | 1.42 (0.99, 2.22) | 582 | 1.37 (0.94, 2.09) | 640 | 1.44 (0.86, 2.03) | 59 | 0.91 | |||
| HDL-C (mmol/L) | 1.08±0.25 | 420 | 1.11±0.28 | 582 | 1.11±0.3 | 640 | 1.06±0.25 | 59 | 0.15 | |||
| LDL-C (mmol/L) | 2.82±0.85 | 420 | 2.89±0.86 | 582 | 2.77±0.88†,‡ | 640 | 2.65±0.91†,‡,§ | 59 | 0.043 | |||
| Hcy (μmol/L) | 10.95 (8.90, 14.40) | 414 | 10.90 (8.40, 13.90) | 571 | 11.10 (9.10, 13.80)†,‡ | 620 | 12.90 (10.48, 15.85)†,‡,§ | 59 | 0.03 | |||
| AFP (ng/mL) | 2.48 (1.72, 3.41) | 404 | 2.51 (1.89, 3.38) | 559 | 2.40 (1.82, 3.07) | 609 | 2.16 (1.85, 3.12) | 61 | 0.53 | |||
| CEA (ng/mL) | 2.08 (1.40, 3.57) | 404 | 1.97 (1.31, 3.19) | 559 | 2.54 (1.60, 4.06) | 609 | 2.45 (2.11, 3.55) | 61 | 0.17 | |||
| CA125 (U/mL) | 9.25 (6.23, 14.40) | 404 | 8.40 (5.88, 12.30) | 559 | 7.90 (5.90, 11.98) | 609 | 8.60 (5.05, 13.05) | 61 | 0.32 | |||
| CA199 (U/mL) | 12.80 (7.50, 23.80) | 404 | 10.30 (6.80, 21.10) | 559 | 11.95 (6.57, 22.30) | 609 | 14.15 (8.65, 26.28) | 61 | 0.33 | |||
Data are expressed as the mean ± standard deviation or median (interquartile range). Parameters among the four groups were compared with analysis of variance or the Kruskal-Wallis test. †, P<0.05 compared with the no pulmonary nodules group; ‡, P<0.05 compared with the diameter <5 mm group; §, P<0.05 compared with the diameter ≥5 and <10 mm group. FPG, fasting plasma glucose; FCP, fasting C-peptide; HbA1c, glycated hemoglobin A1c; HOMA2IR, Homeostatic Model Assessment for Insulin Resistance 2; GOT, glutamic oxaloacetic transaminase; GPT, glutamic pyruvic transaminase; Scr, serum creatinine; eGFR, estimated glomerular filtration rate; UA, uric acid; CRP, C-reactive protein; TC, total cholesterol; TG, triglyceride; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; Hcy, homocysteine; AFP, alpha-fetoprotein; CEA, carcinoembryonic antigen; CA125, carbohydrate antigen 125; CA199, carbohydrate antigen 199.
Multinominal logistic regression
The size of the pulmonary nodule was used as the dependent variable. Gender (assignment: male =0, female =1), smoking (assignment: none =0, yes =1), proteinuria (assignment: none =0, yes =1), insulin use (assignment: none =0, yes =1), DPP4 inhibitor use (assignment: none =0, yes =1), course of disease, age, fasting and 2-hour postprandial C-peptide level, HOMA2IRs score, LDL-C level, and Hcy level were taken as independent variables. According to multinominal logistic regression analysis, with non-pulmonary nodules used as the reference category, older age [nodule diameter ≥5 and <10 mm: odds ratio (OR) =1.019, 95% confidence interval (CI): 1.005–1.032, P=0.007; nodule diameter ≥10 and ≤30 mm: OR =1.036, 95% CI: 1.008–1.065, P=0.01] and smoking (nodule diameter ≥5 and <10 mm: OR =1.647, 95% CI: 1.095–2.475, P=0.02; nodule diameter ≥10 and ≤30 mm: OR =2.217, 95% CI: 1.002–4.926, P=0.049) were risk factors for pulmonary nodules with a diameter >5 mm. DPP4 inhibitor was found to be a risk factor for the development of pulmonary nodules with a diameter of 5–10 mm (OR =1.912, 95% CI: 1.094–3.344, P=0.02). Proteinuria was found to be a protective factor for the occurrence of pulmonary nodules (nodule diameter <5 mm: OR =0.618, 95% CI: 0.389–0.983, P=0.042; ≥5 and <10 mm: OR =0.523, 95% CI: 0.315–0.802, P=0.004) (Table 3).
Table 3
| Variables (reference category: no pulmonary nodules) | β | SE | Wald | P value | OR | 95% CI |
|---|---|---|---|---|---|---|
| Diameter <5 mm | ||||||
| Sex | −0.037 | 0.197 | 0.035 | 0.85 | 1.037 | 0.705–1.527 |
| Disease course | 0.006 | 0.013 | 0.232 | 0.63 | 1.006 | 0.981–1.032 |
| Age | 0.004 | 0.007 | 0.350 | 0.55 | 1.004 | 0.991–1.017 |
| FCP | −0.153 | 0.254 | 0.361 | 0.55 | 0.858 | 0.521–1.413 |
| 2-hour postprandial C-peptide | −0.014 | 0.028 | 0.237 | 0.63 | 0.987 | 0.934–1.042 |
| HOMA2IR | 0.048 | 0.095 | 0.259 | 0.61 | 1.05 | 0.871–1.264 |
| LDL-C | −0.039 | 0.092 | 0.182 | 0.67 | 0.962 | 0.803–1.151 |
| Hcy | −0.014 | 0.014 | 0.968 | 0.32 | 0.986 | 0.958–1.014 |
| Smoke | −0.86 | 0.209 | 0.172 | 0.68 | 1.091 | 0.725–1.642 |
| Proteinuria | 0.481 | 0.237 | 4.123 | 0.042 | 0.618 | 0.389–0.983 |
| DPP4 inhibitor | −0.494 | 0.290 | 2.906 | 0.09 | 1.639 | 0.929–2.890 |
| Insulin | 0.35 | 0.194 | 3.266 | 0.07 | 0.705 | 0.482–1.030 |
| Diameter ≥5 and <10 mm | ||||||
| Sex | −0.045 | 0.201 | 0.051 | 0.82 | 1.046 | 0.706–1.529 |
| Disease course | 0.015 | 0.013 | 1.369 | 0.24 | 1.015 | 0.99–1.04 |
| Age | 0.018 | 0.007 | 7.213 | 0.007 | 1.019 | 1.005–1.032 |
| FCP | 0.116 | 0.284 | 0.168 | 0.68 | 1.123 | 0.644–1.961 |
| 2-hour postprandial C-peptide | −0.049 | 0.031 | 2.493 | 0.11 | 0.953 | 0.897–1.012 |
| HOMA2IR | −0.077 | 0.107 | 0.526 | 0.47 | 0.925 | 0.757–1.141 |
| LDL-C | −0.114 | 0.093 | 1.509 | 0.22 | 0.892 | 0.743–1.07 |
| Hcy | 0.004 | 0.013 | 0.103 | 0.75 | 1.004 | 0.98–1.029 |
| Smoking | −0.499 | 0.208 | 5.762 | 0.02 | 1.647 | 1.095–2.475 |
| Proteinuria | 0.688 | 0.239 | 8.329 | 0.004 | 0.523 | 0.315–0.802 |
| DPP4 inhibitor | −0.648 | 0.285 | 5.182 | 0.02 | 1.912 | 1.094–3.344 |
| Insulin | 0.249 | 0.190 | 1.704 | 0.19 | 0.780 | 0.537–1.133 |
| Diameter ≥10 and ≤30 mm | ||||||
| Sex | −0.144 | 0.425 | 0.115 | 0.73 | 1.129 | 0.502–2.653 |
| Disease course | −0.004 | 0.024 | 0.021 | 0.88 | 0.996 | 0.951–1.044 |
| Age | 0.035 | 0.014 | 6.186 | 0.01 | 1.036 | 1.008–1.065 |
| FCP | 0.304 | 0.662 | 0.211 | 0.65 | 1.356 | 0.37–4.967 |
| 2-hour postprandial C-peptide | −0.035 | 0.066 | 0.279 | 0.60 | 0.996 | 0.848–1.099 |
| HOMA2IR | −0.163 | 0.253 | 0.418 | 0.52 | 0.849 | 0.518–1.394 |
| LDL-C | −0.075 | 0.188 | 0.159 | 0.69 | 0.928 | 0.642–1.341 |
| Hcy | 0.016 | 0.020 | 0.641 | 0.42 | 1.016 | 0.977–1.057 |
| Smoking | −0.796 | 0.409 | 3.788 | 0.049 | 2.217 | 1.002–4.926 |
| Proteinuria | 0.745 | 0.477 | 2.441 | 0.12 | 0.475 | 0.186–1.209 |
| DPP4 inhibitor | 0.187 | 0.650 | 0.082 | 0.77 | 0.830 | 0.232–2.967 |
| Insulin | 0.138 | 0.367 | 0.141 | 0.71 | 0.871 | 0.424–1.789 |
SE, standard error; OR, odds ratio; CI, confidence interval; FCP, fasting C-peptide; HOMA2IR, Homeostatic Model Assessment for Insulin Resistance 2; LDL-C, low-density lipoprotein cholesterol; Hcy, homocysteine; DPP4, dipeptidyl peptidase 4.
Discussion
In this study, the detection rate of pulmonary nodules in hospitalized patients with diabetes was 75.48%, which was significantly higher than the 32.70% reported in a southern California study, which examined patients from 2006 to 2012 (8). An early lung cancer initiative at Cornell Medical Center in the United States found that subsolid nodules were more likely to develop malignancy than were solid nodules (34% vs. 7%) (9). Meanwhile, mGGNs were malignant in 63% of the subsolid nodules, representing a significantly higher rate of malignancy than pGGNs (18%) in the study (9). In a lung cancer early detection study conducted at Vancouver General Hospital, Canada, which followed up on 7,008 pulmonary nodules, more than half of the malignant nodules were located in the upper lobe of the lung (64.70%) (10). In our study, nearly half (49.53%) of the nodules in patients with diabetes were located in the upper lobe of the lungs and about one-third (29.71%) were mGGNs. Therefore, its critical that the lung nodules in patients with diabetes are closely monitored in follow-up.
In addition, we found that patients with diabetes and a nodule diameter ≥5 mm had a higher rate of insulin use than did those without nodules and those with nodules diameter <5 mm in diameter. Larici et al. found that the probability of malignancy of pulmonary nodules was positively correlated with the size of the nodule diameter (11). Therefore, we hypothesize that the use of insulin in patients with diabetes may increase the risk of malignant pulmonary nodules. Zhong et al. reported that insulin dose was positively associated with the incidence of cancer in those with type 1 diabetes (12). However, due to the retrospective nature of our study, it was not possible to accurately trace the specific insulin dose used in patients, so the relationship between insulin dose and pulmonary nodules could not be further examined, but this should be undertaken in subsequent research.
Xia et al. found age to be an independent risk factor for nodule growth and that detection rate of pulmonary nodules increases with age (13). Raghu et al. reported that smoking prevalence was positively correlated with the detection rate of pulmonary nodules (14). In our study, advanced age and smoking were associated with an increased risk of pulmonary nodules ≥5 mm. Therefore, it is necessary to pay attention to the status of pulmonary nodules in older adult patients with diabetes who smoke and strengthen education to raise patients’ awareness of the dangers of smoking.
We also found that the use of DPP4 inhibitors was a risk factor for the development of pulmonary nodules. Studies demonstrated that DPP4 inhibitors induce the re-epithelialization of epithelial cells, increasing the risk of tumor development (15,16). A case report in Japan was the first to find multiple pulmonary GGNs present in patients taking vildagliptin for 7 months, and the multiple GGNS almost disappeared 10 days after discontinuation of the drug and completely disappeared after 4 months of discontinuation. The mechanism underlying this relationship may be a link between DPP4 inhibitors and the pulmonary immune system under the influence of the gut microbiota (17). Therefore, more experimental and clinical studies are needed to clarify the connection between DPP4 inhibitors and pulmonary nodules.
In addition, we found that the incidence of proteinuria in patients with diabetes without pulmonary nodules was higher than that in those with nodules, which may be due to the higher levels of advanced glycation end-products (AGEs) in patients with diabetic nephropathy (18). The carboxymethyllysine (CML) in AGEs can induce epithelial-to-mesenchymal transition (EMT) in podocytes by activating the NF-κB signaling cascade to induce the transcription factor Zeb2 and promote proteinuria (19). Bartling et al. found that AGEs can inhibit tumor cells from destroying the extracellular matrix barrier, thereby hindering the spread and aggressive growth of tumor cells and delaying the progression of non-small cell lung cancer (20). In this study, patients with diabetes and proteinuria might have had higher levels of AGEs, which inhibits the occurrence and progression of pulmonary nodules to a certain extent.
The limitations of this study include its retrospective nature, which did not account for environmental factors such as specific occupations, dust, second-hand smoke, and other exposures. Moreover, few tumor indicators were employed, and due the single-center, cross-sectional design, only hospitalized patients with diabetes were included, which inevitably introduced selection bias.
Conclusions
The prevalence of pulmonary nodules in hospitalized patients with diabetes is high. Patients who are older, smokers, and using DPP4 inhibitors should be closely followed up in regard to their pulmonary nodules. Meanwhile, screening for pulmonary nodules in diabetic populations should be widely carried out to detect early lung cancer and improve the quality of life of patients.
Acknowledgments
We would like to thank the participants and study nurses.
Funding: None.
Footnote
Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1374/rc
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Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1374/coif). The authors have no conflicts of interest to declare.
Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). This study was approved by the Ethics Committee of the Suzhou Municipal Hospital (No. K-2022-118-H01), and the requirement for informed consent of the patients was waived due to the retrospective nature of the analysis.
Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
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(English Language Editor: J. Gray)
