Association between DPP-4 inhibitors and events of colorectal and liver cancers in patients with diabetes receiving second-line agents: a nested case-control study

doi:10.21203/rs.3.rs-30941/v1

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Association between DPP-4 inhibitors and events of colorectal and liver cancers in patients with diabetes receiving second-line agents: a nested case-control study

https://doi.org/10.21203/rs.3.rs-30941/v1

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Background and aim:

Several studies showed plasma dipeptidyl peptidase-4 (DPP4) levels were significantly lower in patients with colorectal and liver cancers, and animal studies also showed DPP4 inhibitors (DPP4is) have procarcinogenic effects in colorectal cancer. The aims of this study were to investigate the association between cumulative defined daily dose (cDDD) of DPP4is exposure and risks of liver and colorectal cancers in patients with type 2 diabetes mellitus.

Methods

In this nested case-control study, we identified 268,520 patients with diabetes receiving DPP4is as second-line agents between March 1, 2009, and December 31, 2013, from Taiwan’s National Health Insurance Research Database, Taiwan Cancer Registry, and National Death Registry of Taiwan. Of these, 948 and 990 patients newly were diagnosed with liver and colorectal cancer, respectively. The amount of DPP4is were divided into three groups (low, medium, and high) based on the interquartile range of the cDDD of the DPP4is. Results: The data showed that the low cDDD of DPP-4is was associated with a reducing risk of colorectal cancer [adjusted odds ratio (OR), 0.49; 95% CI, 0.32–0.75; P = 0.001]. However, the high cDDD of DPP-4is was associated with an increasing risk of colorectal cancer (adjusted OR, 1.86; 95% CI, 1.32–2.61; P < 0.001). No association between DPP4is use and liver cancer risk was observed.

Conclusions

The novel finding of this nested case study revealed a J-shaped association between the cDDD of DPP-4is and colorectal cancer risk, but not liver cancer risk. A large-based longitudinal investigation is necessary to determine whether long-term DPP4is exposure increase colorectal cancer risk.

Cardiac & Cardiovascular Systems

Endocrinology & Metabolism

DPP-4 inhibitors

Liver cancer

Colorectal cancer

Second-line agents

Type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM), which is associated with a high risk of organ dysfunction and high mortality, poses a high economic burden worldwide [1]. In patients with T2DM managed through lifestyle modification, metformin monotherapy is recommended as the initial therapy [2]. After metformin monotherapy fails to achieve target glucose control, a second-line agent may be administered, and the agent prescribed depends on the risk-benefit profile of individual agents.

Among oral antidiabetic drugs, dipeptidyl peptidase-4 inhibitors (DPP4is) are a new and promising class of second-line therapy [3]. Recent research showed that the incretin-based insulinotropic therapeutic agent of the DPP4is provides favorable glucose control with negligible adverse effects, although hypoglycemia and pancreatitis were reported [4]. Moreover, DPP4is are gaining popularity because of their glucose-lowering potential and possible pleiotropic benefits in patients with T2DM, such as lowering serum low-density lipoprotein [5], improving blood pressure [6, 7], and attenuating vascular remodeling processes [8].

Although DPP4is have pleiotropic benefits in addition to glucose-lowering effects, controversial results have been obtained regarding its tissue growth stimulation potential in animal studies [9, 10]. Additionally, Javidroozi et al. [11] reported that plasma dipeptidyl peptidase-4 (DPP4) levels were significantly lower in patients with cancers such as colorectal or liver cancer than in healthy subjects. Higher DPP4 levels were associated with higher survival in all cancers combined [11]. Therefore, long-term DPP4is use has raised concerns regarding the risks of liver and colorectal cancer in patients with T2DM. Additionally, T2DM is an independent risk factor for liver cancer [12] and colorectal cancer [13]. Furthermore, a recent meta-analysis of randomized clinical trials suggested it is mandatory to further investigate the associations between (1) DPP4is and colorectal cancer, and (2) DPP4is and liver cancer risk [14]. Until now, whether DPP4is therapy affects the progression of liver cancer and colorectal cancer in patients with T2DM is inconclusive, possibly because of the low incidence of liver and colorectal cancer. Thus, in this nested case-control study, we investigated the association between DPP4is exposure and risks of liver cancer and colorectal cancer in patients with T2DM receiving second-line agents using data between March 1, 2009 and December 31, 2013 from the National Health Insurance Research Database (NHIRD), Taiwan Cancer Registry (TCR), and National Death Registry (NDR) of Taiwan.

Data sources

This nested case-control study was conducted using data from the NHIRD, TCR, and NDR between March 1, 2009, and December 31, 2013. The NHIRD is a population-based claims database provided by the National Health Insurance Administration and managed by the Health and Welfare Data Science Center, Ministry of Health and Welfare, Executive Yuan, Taiwan. The NHI program covers more than 99% of residents of Taiwan. The NHIRD contains reliable clinical data that are utilized for population-based cohort studies in Taiwan [15, 16]. It is one of the highest-quality databases worldwide [16] and is widely used for longitudinal cohort studies [17–27]. The NHIRD contains data on drug prescriptions, diagnoses, and basic medical and demographic characteristics. In this study, diseases diagnoses were coded according to the International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM). Each patient has a unique encrypted identifier that can be linked to the TCR and NDR. Both the TCR and NDR are population-based registries, and detailed information on the completeness and accuracy of data from the NHIRD, TCR, and NDR has been provided and widely used for longitudinal cohort studies in previous studies [28, 29].

Ethics statement

This study was approved by the Joint Institutional Review Board of Taipei Medical University (TMU-JIRB No. N201712032), and the informed consent requirement was waived for this study.

Study cohort

This study included patients with T2DM who were receiving metformin monotherapy as first-line treatment and initiating second-line therapy (add-on or switching) between March 1, 2009, and December 31, 2013. In Taiwan, the first DPP4is was launched on March 1, 2009, and was as second-line therapy for diabetes when metformin monotherapy fails to achieve glucose control or when metformin is contraindicated for specific patients, such as patients with chronic kidney disease. The exclusion criteria were as follows: 1) not a citizen of Taiwan or missing sex information, 2) diagnosed with cancer and human immunodeficiency virus before receiving a second-line agent, 3) diagnosed with cancer other than liver and colorectal cancer, and 4) without a minimum of 2 years of data available following initiation of second-line therapy.

Patient and control selection

Patients diagnosed with liver cancer (International Classification of Diseases for Oncology, Third Edition [ICD-O-3] code C22) or colorectal cancer (ICD-O-3 codes C18, C19, C20, and C21) were identified from the TCR, and the date of cancer diagnosis was defined as the index date. Only patients with liver and colorectal cancers were included because T2DM is an independent risk factor for liver cancer [12] and colorectal cancer [13]. Each patient was matched to four controls by sex, age (+/− 1 year), and follow-up period using an incidence density sampling approach, which involves matching a patient to control at risk of the disease at the time the patient is diagnosed with the disease. Because controls did not have cancer, they were assigned a date for a pseudo-cancer event, which corresponded to the index date of their matched patients (referred to as the index date hereafter). This approach enabled both patients and controls to be observed for similar periods, eliminating the bias caused by differences in the time frame.

DPP4is exposure

DPP4is use was determined using prescription claims data. DPP4is exposure was measured based on the cumulative defined daily dose (cDDD) within 2 years before the index date of patients and controls. Of these, patients who had no claims data on DPP4is use within the 2-year observational period were considered nonusers. Among the users, we used the interquartile range (IQR) to divide patients into three DPP4is exposure groups, low cDDD group (cDDD < Q₁), medium cDDD group (Q₁ ≤ cDDD < Q₃), and high cDDD group (cDDD ≥ Q₃). The reason for such patient classification was the U-shaped distribution of patients with DPP4is use, and this nonlinear distribution was likely more effectively presented using multiple groups.

Covariates

Baseline demographic and clinical characteristics recorded before the index date were obtained. Socioeconomic status (SES) was measured based on monthly income calculated from the insurance premium provided in patients’ enrollment profile, and SES was divided into six categories. ICD-9-CM disease diagnostic codes for previous or coexisting diseases and Anatomical Therapeutic Chemical (ATC) codes for medication are listed in Table S1. The comorbidities for liver and colorectal cancer were cholangitis, cholelithiasis, cholecystitis, cirrhosis of liver, alcoholic liver disease, chronic nonalcoholic liver disease, hepatitis B, hepatitis C, inflammatory bowel disease, adenomatous polyposis, peptic ulcer, gastroesophageal reflux disease (GERD), cardiovascular disease, and hyperlipidemia. To quantify the severity of comorbidities, we used a modified Charlson–Deyo comorbidity index (CCI) without considering uncomplicated diabetes as a proxy measure. The prescribed medications included diabetic and nondiabetic medications. The major classes of diabetic medications were metformin, thiazolidinedione, sulfonylureas, alpha-glucosidase inhibitors, and insulin. The nondiabetic medications included angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (ACEIs/ARBs), beta-selective blockers, diuretics, calcium channel blockers (CCBs), antiplatelet drugs, statins, nonsteroidal anti-inflammatory drugs (NSAIDs), and steroids.

Statistical analysis

We used standardized mean difference (SMD) to evaluate the balance of baseline characteristics between patients and controls. An imbalance was defined as an absolute value of > 0.1. Stepwise conditional logistic regression was used to estimate the crude odds ratios (ORs), adjusted ORs, and 95% confidence intervals (CIs) for the association between DPP4is use and the risk of liver or colorectal cancer. We also performed subgroup analysis to examine further the association between DPP4is use and cancer in different age groups, male and female patients, and those receiving different diabetic agents. Statistical analyses were performed using SAS/STAT (version 9.3; SAS Institute, Cary, NC, USA) and STATA 12 (Stata Corp, College Station, TX, USA). A P value of < 0.05 was considered statistically significant.

Sample size

Initially, 224,974 patients with T2DM receiving second-line therapy were eligible for the study, and this nested case-control study comprised 948 and 990 patients with liver and colorectal cancer who were matched to 3,792 and 3,956 matched controls, respectively (Fig. 1).

Baseline characteristics

Table 1 presents the baseline characteristics of patients with liver (cohort 1) and colorectal cancer (cohort 2) and their matched controls. The mean age of the two cohorts was 63.4 years (standard deviation [SD]: 10.7 years). Patients with liver cancer were more likely to have higher CCI than matched controls, but this trend was not observed in patients with colorectal cancer. Patients with liver cancer were more likely than controls to have comorbidities related to bile and the liver, such as cholangitis, cholelithiasis, cirrhosis of liver, alcoholic liver disease, hepatitis B, and hepatitis C. Moreover, patients with liver cancer were more likely than controls to have adenomatous polyposis, peptic ulcer, GERD, and cardiovascular disease. Patients with colorectal cancer were more likely than controls to have peptic ulcer, GERD, hyperlipidemia, hypertension, and cardiovascular disease. Regarding previous or coexisting medication use, both groups of patients with cancer were more likely than controls to be prescribed with diuretics, NSAIDs, metformin, sulfonylureas, and insulin.

Table 1

Characteristics of patients with liver and colorectal cancer and age- and sex-matched controls among patients with T2DM receiving second-line therapy
	Cohort 1					Cohort 2
	Patients with liver cancer		Matched controls			Patients with colorectal cancer		Matched controls
	n	(%)	n	(%)	SMD	n	(%)	n	(%)	SMD
Sample size, N	948	(100.0)	3,792	(100.0)		990	(100.0)	3,960	100.0
Age (years), mean (SD)	63.4	(10.7)	63.4	(10.7)		63.4	(10.7)	63.4	(10.7)
< 45	38	(4.0)	145	(3.8)	0.010	20	(2.0)	86	(2.2)	0.011
≧ 45 and < 65	467	(49.3)	1,890	(49.9)	0.012	409	(41.3)	1,631	(41.2)	0.003
≧ 65	443	(46.7)	1,757	(46.3)	0.008	561	(56.7)	2,243	(56.6)	0.001
Male, yes	675	(71.2)	2,700	(71.2)	0.008	637	(64.3)	2,545	(64.3)	0.001
Socioeconomic status
1 (highest)	59	(6.2)	152	(4.0)	0.101	58	(5.9)	168	(4.2)	0.073
2	89	(9.4)	252	(6.7)	0.101	86	(8.7)	268	(6.8)	0.072
3	342	(36.1)	1,659	(43.8)	0.157	414	(41.8)	1,664	(42.1)	0.005
4	407	(42.9)	1,413	(37.3)	0.116	382	(38.6)	1,511	(38.2)	0.008
5	37	(3.9)	183	(4.8)	0.045	41	(4.1)	206	(5.2)	0.050
6 (lowest)	14	(1.5)	133	(3.5)	0.131	9	(0.9)	139	(3.5)	0.178
Modified CCI
0	64	(6.8)	1,030	(27.2)	0.565	327	(33.0)	1,003	(25.3)	0.170
1–2	508	(53.6)	1,531	(40.4)	0.267	454	(45.9)	1,632	(41.3)	0.094
≧ 3	376	(39.7)	1,231	(32.4)	0.150	209	(21.1)	1,325	(33.4)	0.280
Previous or coexisting diseases, yes
Cholangitis	18	(1.9)	22	(0.6)	0.119	6	(0.6)	45	(1.1)	0.057
Cholelithiasis	84	(8.9)	109	(2.9)	0.257	40	(4.0)	113	(2.9)	0.065
Cholecystitis	14	(1.5)	37	(1.0)	0.046	7	(0.7)	28	(0.7)	0.000
Cirrhosis of liver	511	(53.9)	450	(11.9)	1.000	33	(3.3)	298	(7.5)	0.186
Alcoholic liver disease	129	(13.6)	283	(7.5)	0.201	16	(1.6)	170	(4.3)	0.159
Chronic nonalcoholic liver disease	17	(1.8)	31	(0.8)	0.086	10	(1.0)	22	(0.6)	0.052
Hepatitis B	290	(30.6)	166	(4.4)	0.735	32	(3.2)	105	(2.6)	0.034
Hepatitis C	309	(32.6)	192	(5.0)	0.752	14	(1.4)	111	(2.8)	0.097
Inflammatory bowel disease	3	(0.3)	16	(0.4)	0.017	11	(1.1)	15	(0.4)	0.085
Adenomatous polyposis	38	(4.0)	14	(0.4)	0.251	6	(0.6)	7	(0.2)	0.069
Peptic ulcer	283	(29.9)	715	(18.9)	0.258	240	(24.2)	726	(18.3)	0.145
GERD	114	(12.0)	304	(8.0)	0.134	121	(12.2)	280	(7.1)	0.175
Cardiovascular disease	209	(22.0)	1,186	(31.3)	0.210	283	(28.6)	1,380	(34.9)	0.135
Hyperlipidemia	226	(23.8)	847	(22.3)	0.036	378	(38.2)	825	(20.8)	0.387
Hypertension	366	(38.6)	1,535	(40.5)	0.038	300	(30.3)	1,534	(38.7)	0.178
Previous or coexisting medications, yes
ACEI/ARB	453	(47.8)	1,796	(47.3)	0.008	541	(54.6)	1,903	(48.1)	0.132
Beta-2 blocker	417	(44.0)	1,443	(38.1)	0.121	386	(39.0)	1,456	(36.8)	0.046
Diuretic	539	(56.9)	1,692	(44.6)	0.247	399	(40.3)	1,829	(46.2)	0.119
CCB	476	(50.2)	1,879	(49.6)	0.013	564	(57.0)	1,978	(50.0)	0.141
Antiplatelet drug	315	(33.2)	1,557	(41.0)	0.163	389	(39.3)	1,691	(42.7)	0.069
Statin	186	(19.6)	862	(22.8)	0.076	324	(32.7)	910	(23.0)	0.219
NSAID	729	(76.9)	2,370	(62.5)	0.317	721	(72.8)	2,340	(59.1)	0.293
Steroid	384	(40.5)	1,572	(41.5)	0.019	437	(44.1)	1,646	(41.6)	0.052
Other OADs
Metformin	470	(49.6)	1,286	(33.9)	0.322	480	(48.5)	1,271	(32.1)	0.339
Thiazolidinedione	57	(6.0)	191	(5.0)	0.043	51	(5.2)	172	(4.3)	0.038
Sulfonylureas	443	(46.7)	1,279	(33.7)	0.267	427	(43.1)	1,248	(31.5)	0.242
Alpha-glucosidase inhibitor	118	(12.4)	384	(10.1)	0.073	106	(10.7)	353	(8.9)	0.060
Insulin	377	(39.8)	1,019	(26.9)	0.276	448	(45.3)	1,020	(25.8)	0.416
*SMD: standardized mean difference = difference in means or proportions divided by standard error; imbalance defined as absolute value greater than 0.1.
ACEI angiotensin-converting enzyme inhibitor, ARBs angiotensin receptor blockers, CCB calcium channel blockers, CCI Charlson–Deyo comorbidity index, GERD gastroesophageal reflux disease, OADs oral antidiabetic drugs, NSAID nonsteroidal anti-inflammatory drug, SD standard deviation, T2DM type 2 diabetes mellitus.

Association of DPP4is use and risks of liver and colorectal cancer

Table 2 presents the association between DPP4is use and the risk of liver cancer in patients with T2DM receiving second-line therapy. Patients were divided into DPP4is exposure groups according to the IQR of the cDDD. During the 2-year observation period, 17.9% of patients with liver cancer was DPP4is users and 16.0% of control patients were DPP4is users, respectively. When we compared patients with liver cancer with their matched controls, there was no association between DPP4is use and liver cancer risk.

Table 2

Association between DPP4is exposure and liver cancer risk among patients with T2DM receiving second-line therapy
	Patients with liver cancer		Matched controls		Crude OR (95% CI)	P	Adjusted* OR (95% CI)	P
	N	(%)	N	(%)
Sample size	948	(100.0)	3,792	(100.0)
DPP4is exposure group (cDDD within 2 years)
Nonuser (cDDD = 0)	778	(82.1)	3,184	(84.0)	1.00 (Ref.)		1.00 (Ref.)
Low cDDD group (cDDD < 52)	35	(3.7)	160	(4.2)	0.90 (0.62–1.32)	0.593	0.79 (0.48–1.29)	0.337
Medium cDDD group (52 ≤ cDDD < 414)	88	(9.3)	301	(8.0)	1.20 (0.93–1.54)	0.159	0.91 (0.64–1.28)	0.580
High cDDD group (cDDD ≥ 414)	47	(5.0)	147	(3.9)	1.32 (0.94–1.86)	0.113	1.13 (0.71–1.79)	0.602
*Adjustment for the covariates listed in Table 1
DPP4is dipeptidyl peptidase-4 inhibitors, CI confidence interval, cDDD cumulative defined daily dose, OR odds ratio, Ref. reference group, T2DM type 2 diabetes mellitus

As shown in Table 3, the dose-response effect of DPP4is for colorectal cancer was J-shaped, indicating the dual effects of DPP4is. The low cDDD group of DPP4is exposure was associated with a reducing risk of colorectal cancer in patients with colorectal cancer than in their matched controls (adjusted OR = 0.49, 95% CI = 0.32–0.75, P = 0.001). By contrast, the high cDDD group of DPP4is exposure was associated with an increasing risk of colorectal cancer in patients with colorectal cancer than in their matched controls (adjusted OR = 1.86, 95% CI = 1.32–2.61, P < 0.001). No association between PP4is use and colorectal cancer risk was observed in the medium cDDD group.

Table 3

Association between DPP4is exposure and colorectal cancer risk among patients with T2DM receiving second-line therapy
	Patients with colorectal cancer		Matched controls		Crude OR (95% CI)	P	Adjusted* OR (95% CI)	P
	N	(%)	N	(%)
Sample size	990	(100.0)	3,960	(100.0)
DPP4is exposure group (cDDD within 2 years)
Nonuser (cDDD = 0)	790	(79.8)	3,321	(83.9)	1.00 (Ref.)		1.00 (Ref.)
Low cDDD group (cDDD < 56)	30	(3.0)	189	(4.8)	0.68 (0.46–1.01)	0.057	0.49 (0.32–0.75)	0.001
Medium cDDD group (56 ≤ cDDD < 420)	96	(9.7)	316	(8.0)	1.30 (1.02–1.66)	0.037	0.91 (0.69–1.20)	0.515
High cDDD group (cDDD ≥ 420)	74	(7.5)	134	(3.4)	2.34 (1.74–3.15)	< 0.001	1.86 (1.32–2.61)	< 0.001
*Adjustment for the covariates listed in Table 1
The abbreviations as in Table 2

Subgroup analysis of high cDDD group for the association between DPP4is use and risk of colorectal cancer in patients with T2DM initiating second-line therapy

During the 2-year observational period, patients with colorectal cancer aged less than 65 years (Fig. 2) were more likely to be exposed to the high cDDD group than their matched controls (adjusted OR = 2.52, 95% CI = 1.59–3.99). Similar results were found for patients who were male, without hyperlipidemia, and did not take metformin, sulfonylureas, or insulin. For example, among insulin nonusers, the adjusted OR of patients with colorectal cancer to their matched controls was 1.92 (95% CI = 1.16–3.18).

This study was the first to examine the association between the cDDD of DPP4is exposure and risks of liver and colorectal cancers in patients with type 2 diabetes mellitus receiving second-line agents. After multivariate adjustment and subgroup analysis, the major findings of our study are as follows. (1) Based on the prospective data from the Taiwan NHIRD, DPP4is exposure was associated with colorectal cancer risk, in patients with T2DM, and the dose-response effect of DPP4is for colorectal cancer was J-shaped, indicating the dual effects of DPP4is. (2) No association between DPP4is use and liver cancer risk was observed. (3) Subgroup analyses showed that among the high cDDD group, DPP4is use remained a risk factor for colorectal cancer in patients who were less than 65 years old, male, without hyperlipidemia, and did not take metformin, sulfonylureas, and insulin.

Controversial results have been obtained regarding the association of DPP4is use with the risk of colorectal cancer. In this nested case-control study, our findings showed the association between DPP4is use and the risk of colorectal cancer in patients with T2DM. Furthermore, our study provided a novel finding that the dose-response curve of DPP4is exposure for colorectal cancer is J-shaped, indicating the dual effects of DPP4is. The low cDDD group was associated with a reducing risk of colorectal cancer (adjusted OR = 0.49, 95% CI = 0.32–0.75, P = 0.001). By contrast, the high cDDD group was associated with an increasing risk of colorectal cancer (adjusted OR = 1.86, 95% CI = 1.32–2.61, P < 0.001). Emerging studies show that antiangiogenic agents exhibit J-shaped or U-shaped dose-response curves [30], indicating inhibitory effects at a low dosage and stimulatory effects at a higher dosage. DPP4is have potent antiangiogenic activities, which are mediated through the suppression of DPP4 and plasminogen activator inhibitor-1 [31].

Few in vitro and in vivo studies have evaluated the effects of DPP4is on colorectal cancer, and the association between DPP4is use and colorectal cancer remains unclear [32–34]. Amritha et al. [32] reported that sitagliptin exerted more potent inhibitory effects on HT-29 colon cancer cell growth than vildagliptin. However, Wang et al. [33] found that saxagliptin and sitagliptin could increase cell migration and invasion in SW480 and HCT116 colon cancer cell lines through the activation of nuclear factor E2-related factor 2. Femia et al. [34] investigated the effect of 15-week sitagliptin treatment on colon carcinogenesis in 1,2-dimethylhydrazine-induced colon cancer rats and found fewer precancerous lesions (manifesting as mucin-depleted foci) in the colorectum in rats treated with sitagliptin than in controls. Therefore, additional in vitro and in vivo experiments will be necessary to evaluate the effect of DPP4is dose and duration on cancer cells.

The Saxagliptin Assessment of Vascular Outcomes Recorded in Patients with Diabetes Mellitus-Thrombolysis in Myocardial Infarction (SAVOR-TIMI) 53 trial in 2016 reported that saxagliptin exerted a protective effect against colon cancer (hazard ratio = 0.51, 95% CI = 0.27–0.92, P = 0.026) [35]. However, the sample size of patients with colon cancer in this trial was small (number of patients = 47). A meta-analysis of randomized clinical trials in 2017 showed the insignificant effect of DPP4is on the risk of colon cancer (MH-RR = 0.96, 95% CI = 0.71–1.31, P = 0.808) [14]. Furthermore, in 2018, in a large population from the UK Clinical Practice Research Datalink, the results of 388,619 person-years of follow-up between 1 January 2007 and 31 March 2015 indicated the use of DPP4is inhibitors had a tendency to raise colorectal cancer incidence, however, which was not much significantly in statistics (hazard ratio = 1.2, 95% CI = 1.0–1.5) [36]. These findings indicate the ambiguous effect of DPP4is on the inhibition of and stimulation of cancers, and the conflicting results may be because of variable dosage and follow-up duration among these studies. Thus, additional cohort studies should be conducted to examine the J-shaped association (related to antiangiogenesis) between the cDD of DPP4is use and the risk of colon cancer.

In the present study, no association of DPP4is use and liver cancer risk was observed between patients with liver cancer and their matched controls (adjusted OR = 1.13, 95% CI = 0.71–1.79, P = 0.602). In a meta-analysis, Zhao et al. showed no significant association between DPP4is use and the risk of liver cancer in patients with T2DM (MH-RR = 1.02, 95% CI = 0.54–1.91, P = 0.96) [14].

The strengths of our study are the large sample size, the use of a national database, the consideration of the cumulative dose effect of drug use, and the subgroup analysis. Moreover, in this population-based observational study, multiple potential risk factors from the Taiwan NHIRD were adjusted for. Despite its strengths and novelty, this study has some limitations that require clarification. First, drug exposure was measured based on prescription records, which might not reflect the actual use of drugs. Second, the NHIRD lacks information on patients’ risk behavior and clinical characteristics, which might affect the findings. Third, although all potential risk factors were adjusted for in this population-based observational study, unmeasured factors might have still biased our observations; therefore, the results should be interpreted with caution. Finally, this study included Taiwanese patients; therefore, our results might not apply to other populations.

The novel finding of this nested case-control study showed a J-shaped association between the cDDD of DPP4is and the risk of colorectal cancer. This study provided the possible effects of long-term DPP4is use on colorectal cancer in patients with T2DM. Therefore, the effects of long-term DPP4is use on colorectal cancer risk warrant further study.

ATC: Anatomical Therapeutic Chemical; ACEIs/ARBs: angiotensin-converting enzyme inhibitors/angiotensin receptor blockers; cDDD: cumulative defined daily dose; CI: confidence interval; CCBs: calcium channel blockers; CCI: Charlson; Deyo comorbidity index; DPP4is: dipeptidyl peptidase-4 inhibitors; DPP4: dipeptidyl peptidase-4; OR: odds ratio; GERD: gastroesophageal reflux disease; IQR: interquartile range; ICD-O-3: International Classification of Diseases for Oncology, Third Edition; ICD-9-CM: International Classification of Disease, Ninth Revision, Clinical Modification; NDR: National Death Registry; NHIRD: National Health Insurance Research Database; NSAIDs: nonsteroidal anti-inflamm atory drugs; SMD: standardized mean difference; SD: standard deviation; SES: Socioeconomic status; TCR: Taiwan Cancer Registry; T2DM: Type 2 diabetes mellitus.

Acknowledgments

We thank the Bureau of Health Promotion, Department of Health, and National Health Research Institutes of Taiwan for providing access to the NHIRD, TCR, and NDR. The interpretations and conclusions contained herein do not represent those of the Bureau of National Health Insurance, Department of Health, or National Health Research Institutes. This study was presented at the 2018 Annual Meeting of the Taiwan Society of Nephrology (Taoyuan, Taiwan, December 8–9, 2018). We thank Wallace Academic Editing for English editing of this manuscript.

Authors’ Contributions

CLC, LNC and TCF designed the research. CLC, SHJ, HHC, LNC and TCF conducted the research. LNC and TCF analyzed data and performed the statistical analysis. CLC, LNC and TCF wrote and edited the manuscript. TCF had the primary responsibility for the final content. All authors read and approved the final manuscript.

Funding

We appreciate the support from the Health and Clinical Data Research Center, College of Public Health, Taipei Medical University. The study was financially sponsored by Taipei Medical University Hospital, Taipei Medical University, Taiwan, Taiwan (106TMU-TMUH-11). The funder had no role in study design, data collection and analysis, publication decision, and manuscript preparation.

Availability of data and materials

The datasets used in this study were available from the Bureau of Health Promotion, Department of Health, and National Health Research Institutes of Taiwan. The SAS programs (codes) involved for this study are available from the corresponding author on reasonable request.

Ethics approval and consent to participate

This study was approved by the Joint Institutional Review Board of Taipei Medical University (TMU-JIRB No. N201712032).

Consent for publications

Authors give full consents for publication of the present article.

Competing interests

The authors declare that they have no competing interests.

Author details

¹Division of Nephrology, Department of Internal Medicine, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan.

²Division of Nephrology, Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan

³TMU Research Center of Urology and Kidney, Taipei Medical University, Taipei, Taiwan

⁴Department of Physiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan Taipei Medical University, Taipei, Taiwan

⁵Division of Nephrology, Department of Internal Medicine, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan

⁶Health and Clinical Data Research Center, College of Public Health, Taipei Medical University

⁷Department of Medical Education and Research, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan

⁸School of Health Care Administration, College of Management, Taipei Medical University, Taipei, Taiwan

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Additional file 1: Table S1. Disease Diagnosis Codes According to The International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) and Prescribed Medications Classified Based on Anatomical Therapeutic Chemical (ATC) Classification.

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Association between DPP-4 inhibitors and events of colorectal and liver cancers in patients with diabetes receiving second-line agents: a nested case-control study

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Abstract

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Background

Methods

Data sources

Ethics statement

Study cohort

Patient and control selection

DPP4is exposure

Covariates

Statistical analysis

Results

Sample size

Baseline characteristics

Association of DPP4is use and risks of liver and colorectal cancer

Subgroup analysis of high cDDD group for the association between DPP4is use and risk of colorectal cancer in patients with T2DM initiating second-line therapy

Discussion

Conclusions

Abbreviations

Declarations

References

Supplementary information

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