Abstract
Objective
This study aimed to determine the impact of type 2 diabetes mellitus (T2DM) on clinical outcomes of gastric cancer (GC) patients and explore whether metformin use and good glycemic control could reverse it.
Methods
Clinicopathologic data of consecutive GC patients who underwent gastrectomy at Nanfang Hospital between October 2004 and December 2015 were included. Propensity score matching (PSM) was performed to balance the important factors of the disease status between non-T2DM and T2DM group. The last follow-up time was January 2019.
Results
A total of 1,692 eligible patients (1,621 non-T2DM vs. 71 T2DM) were included. After PSM, non-T2DM group (n=139) and T2DM group (n=71) were more balanced in baseline variables. The 5-year cancer-specific survival (CSS) rate in T2DM group (47.0%) was inferior to that in non-T2DM group (58.0%), but did not reach statistical significance [hazard ratio (HR)=1.319, 95% confidence interval (95% CI): 0.868−2.005, P=0.192]. While the 5-year progress-free survival (PFS) rate of T2DM group (40.6%) is significantly worse than that in non-T2DM group (56.3%) (HR=1.516, 95% CI: 1.004−2.290, P=0.045). Univariate and multivariate analyses showed that T2DM was an independent risk factor for PFS but not for CSS. In T2DM group, metformin use subgroup was associated with superior 5-year CSS and PFS in compared with non-metformin use subgroup, although the difference was not statistically significant (5-year CSS: 48.0%vs. 45.4%, HR=0.680, 95% CI: 0.352−1.313, P=0.246; 5-year PFS: 43.5%vs. 35.7%, HR=0.763, 95% CI: 0.400−1.454, P=0.406). The 5-year CSS rate was 47.5% in good glycemic control subgroup and 44.1% in poor glycemic control subgroup (HR=0.826, 95% CI: 0.398−1.713, P=0.605). And both two subgroups yielded a similar 5-year PFS rate (42.2%vs. 36.3%, HR=0.908, 95% CI: 0.441−1.871, P=0.792).
Conclusions
DM promoted disease progress of GC after gastrectomy but had not yet led to the significant discrepancy of CSS. For GC patients with T2DM, metformin use was associated with superior survival but without statistical significance, while better glycemic control could not improve the prognosis.
Keywords: Gastric cancer, diabetes mellitus, prognosis, metformin, glycemic, gastrectomy
Introduction
Gastric cancer (GC) is one of the leading causes of cancer-related deaths worldwide and a substantial global health burden (1-3). Although the cornerstone treatment, gastrectomy and lymphadenectomy, has reached the maturity level (4-6), locally advanced GC still has a high risk of recurrence (7,8). While diabetes mellitus (DM) also is a major cause of morbidity and death worldwide (9,10). It is worth noting that DM has been closely linked to cancer epidemiologically and biologically (11,12). The underlying mechanisms for higher risk of cancer in patients with DM including insulin resistance, inadequate glycemic control, oxidative stress etc. have been revealed (11,13). It has been demonstrated that breast cancer patients with DM are at increased risk of all-cause mortality compared with non-DM subgroup (14). Also, the systematic review and meta-analysis confirmed that compared with the non-DM counterparts, breast cancer patients with pre-existing diabetes have a greater risk of death (15). It also has been suggested stage II/III colon cancer (CRC) patients with DM experience a significantly higher rate of overall mortality and cancer recurrence (16). Similar phenomenon has also been observed in pancreatic cancer (17) and prostate cancer (18). However, there are discrepant reports about the relationship between DM and the risk or prognosis of GC (19-24), which still await to be further investigated.
More interestingly, some population studies have indicated that metformin, the most widely used oral hypoglycemic agent in the biguanide class for the treatment of type 2 DM (T2DM), could reduce the risk of cancer and cancer mortality in patients with T2DM (25-30). It’s remarkable that Lee et al. (31) retrospectively analyzed data from 1,974 GC patients performed with gastrectomy (326 DM and 1,648 non-DM patients), and found those treated with metformin (n=132) had a significantly superior prognosis than those who were not (n=194) after a median follow-up of 6.2 years. And multivariable analysis further showed that each cumulative 6 months of metformin use was significantly related to a decreased risk of recurrence, cancer-specific mortality, and all-cause mortality.
Therefore, we aimed to investigate the long-term oncologic outcomes of GC patients with T2DM vs. without T2DM, and assess the impact of metformin use and glycemic control on the survival of T2DM subgroup based on Chinese population which account for 41% of the newly diagnosed GC worldwide (32).
Materials and methods
Patients
A total of 1,909 consecutive patients were diagnosed with GC and underwent surgery at Nanfang Hospital, Southern Medical University between October 2004 and December 2015. The analyses were based on the prospective database which was specifically designed for GC and has been serviced in Nanfang Hospital since 2004 (33). Data monitoring was always conducted by experienced medical recorders. The patient selection standard contains: 1) confirmed by pathological examination; 2) performed with laparoscopy; 3) with active follow-up; and 4) with exact survival months and definite endpoint. Two independent surgical oncologists retrospectively reviewed the pathological reports and medical records of patients, and patients who met the following criteria were excluded: 1) did not receive gastrectomy; 2) aged <18 years; or 3) combined with type 1 DM. After the above inclusion and exclusion criteria were applied, 1,692 patients were enrolled. According to the concomitant T2DM, patients were classified into two groups: GC with T2DM (n=71) and GC without T2DM (n=1,621). After generating propensity score matching (PSM) with five covariates (age, sex, pT status, pN status, pM status) by parameters of “method=‘nearest’, ratio=2, caliper=0.01”, 139 GC patients without T2DM (non-T2DM group) were matched to 71 GC patients with T2DM (T2DM group) ( Figure 1 ).
1.
Study flow diagram. GC gastric cancer; T2DM, type 2 diabetes mellitus.
The cancer stage was determined or recorded based on the 7th edition of the AJCC TNM staging system (34). The gastrectomy reconstruction and methods of lymph node examination followed standard guidelines and the experiences we reported (6,35-37). The good glycemic control subgroup was defined as patients maintained blood glucose not higher than 11.1 mmol/L most time in T2DM group. The poor glycemic control subgroup was defined as patients often presenting with random plasma glucose higher than 11.1 mmol/L. The status of glycemic control was depended on the status of blood glucose monitored by patients or their families. The metformin use subgroup was defined as patients use metformin as the main approach to control T2DM. The non-metformin use subgroup was defined as patients did not use metformin as the approach to control T2DM.
The study complied with the principles set forth in the Declaration of Helsinki. The data collection protocol was approved by the Ethics Committee of Nanfang Hospital, Southern Medical University. Written informed consent was obtained from all the patients in the study.
Diagnosis of DM
Diagnosis of DM was based on the record of the prospective GC database (33), which defined DM according to the following criteria: 1) HbA1c ≥6.5%; or 2) fasting plasma glucose (FGP) ≥126 mg/dL (7.0 mmol/L). Fasting is defined as no caloric intake for at least 8 h; or 3) 2 h plasma glucose 200 mg/dL (11.1 mmol/L) during an oral glucose tolerance test (OGTT); 4) patients with classic symptoms of hyperglycemia or hyperglycemic crisis, a random plasma glucose 200 mg/dL (11.1 mm/L); or 5) patients do not meet above conditions, but have a specific history of DM with well-controlled medication. The exact time of receiving the test of DM was during preparation process of undergoing surgery in Nanfang Hospital.
Follow-up
All patients were followed up until death or last follow-up in January 2019. The follow-up scheme was 3-month interval during the first 2 years after surgery, and 6-month interval in the next 3 years, and annually afterwards. The follow-up duration was measured from the time of surgery to the last follow-up date. Cancer-specific survival (CSS) was measured from the date of surgery to the date of cancer-specific death. Progress-free survival (PFS) after surgery was defined as the time from surgery to recurrence or disease progression.
Statistical analysis
Data are presented as number (%) for categorical variables for which χ2 test and Fisher’s exact test were used to compare as appropriate. PSM with five covariates (age, sex, pT status, pN status, pM status) by the parameter of “method=‘nearest’, ratio=2, caliper=0.01” was performed using R software (Version 3.6.1, https://www.r-project.org/) with the matchit package. Survival probability was estimated with Kaplan-Meier method and compared by log-rank test with the ggplot2, survminer and survival packages. Risk factors for survival were evaluated by univariate and multivariate analyses using Cox regression models. Hazard ratio (HR) is presented with 95% confidence interval (95% CI). Variables with statistical P<0.10 in univariate analysis as well as the critical factor in present analysis, DM (i.e., T2DM or non-T2DM) were entered into the multivariable model and were analyzed by using an “Enter” method. P<0.05 (two-tailed) was considered statistically significant. The statistical software SPSS for Windows (Version 25.0; IBM Corp., New York, USA) was used for all statistical analyses.
Results
Patient characteristics
Clinical and pathological characteristics of 1,692 eligible patients are shown in Table 1 . By PSM, non-T2DM group (n=139) and T2DM group (n=71) were more balanced in baseline variables. Notably, the unbalance of age was redressed and the most important variables that were considered as the most important factors to assess the disease status and affect prognosis (i.e. pT, pN, pM) were more comparable between two groups.
1. Patient characteristics.
| Variable | Before PSM | After PSM | ||||||||
| Non-T2DM
group (n=1,621) |
T2DM
group (n=71) |
Statistic | P | Non-T2DM
group (n=139) |
T2DM
group (n=71) |
Statistic | P | |||
| HBsAg, hepatitis B surface antigen; PSM, propensity score matching; T2DM, type 2 diabetes mellitus. | ||||||||||
| Sex | 0.407 | 0.899 | ||||||||
| Male | 1,088 (67.1) | 51 (71.8) | 0.686 | 101 (72.7) | 51 (71.8) | 0.016 | ||||
| Female | 533 (32.9) | 20 (28.2) | 38 (27.3) | 20 (28.2) | ||||||
| Age (year) | 0.001 | 0.767 | ||||||||
| <40 | 187 (11.5) | 1 (1.4) | −0.318 | 2 (1.4) | 1 (1.4) | −0.296 | ||||
| 40−69 | 1,249 (77.1) | 56 (78.9) | 112 (80.6) | 56 (78.9) | ||||||
| ≥70 | 185 (11.4) | 14 (19.7) | 25 (18.0) | 14 (19.7) | ||||||
| Hepatitis | 0.904 | 0.672 | ||||||||
| No | 1,535 (94.7) | 67 (94.4) | 0.015 | 133 (95.7) | 67 (94.4) | 0.180 | ||||
| Yes | 86 (5.3) | 4 (5.6) | 6 (4.3) | 4 (5.6) | ||||||
| HBsAg (+) | 0.792 | 0.491 | ||||||||
| No | 1,517 (93.6) | 67 (94.4) | 0.070 | 134 (96.4) | 67 (94.4) | 0.475 | ||||
| Yes | 104 (6.4) | 4 (5.6) | 5 (3.6) | 4 (5.6) | ||||||
| Tumor location | 0.187 | 0.487 | ||||||||
| Upper | 275 (17.0) | 18 (25.4) | 3.357 | 30 (21.6) | 18 (25.4) | 1.437 | ||||
| Middle | 345 (21.3) | 14 (19.7) | 21 (15.1) | 14 (19.7) | ||||||
| Lower | 1,001 (61.8) | 39 (54.9) | 88 (63.3) | 39 (54.9) | ||||||
| Ascites | 0.977 | 0.324 | ||||||||
| No | 1,531 (94.4) | 67 (94.4) | 0.001 | 135 (97.1) | 67 (94.4) | 0.974 | ||||
| Yes | 90 (5.6) | 4 (5.6) | 4 (2.9) | 4 (5.6) | ||||||
| Gastrectomy | 0.861 | 0.905 | ||||||||
| Total | 500 (30.8) | 24 (33.8) | 0.298 | 43 (30.9) | 24 (33.8) | 0.199 | ||||
| Proximal | 112 (6.9) | 5 (7.0) | 11 (7.9) | 5 (7.0) | ||||||
| Distal | 1,009 (62.2) | 42 (59.2) | 85 (61.2) | 42 (59.2) | ||||||
| Reconstruction | 0.391 | 0.470 | ||||||||
| Roux-en-Y | 515 (31.8) | 26 (36.6) | 0.735 | 44 (31.7) | 26 (36.6) | 0.521 | ||||
| Others | 1,106 (68.2) | 45 (63.4) | 95 (68.3) | 45 (63.4) | ||||||
| Lymphadenectomy | 0.689 | 0.917 | ||||||||
| Non-D2/D2+ | 233 (14.4) | 9 (12.7) | 0.160 | 15 (10.8) | 8 (11.3) | 0.011 | ||||
| D2/D2+ | 1,388 (85.6) | 62 (87.3) | 124 (89.2) | 63 (88.7) | ||||||
| Radical resection | 0.516 | 0.842 | ||||||||
| Yes | 1,296 (80.0) | 59 (83.1) | 0.423 | 117 (84.2) | 59 (83.1) | 0.040 | ||||
| No | 325 (20.0) | 12 (16.9) | 22 (15.8) | 12 (16.9) | ||||||
| Approach | 0.300 | 0.922 | ||||||||
| Open/Conversion | 671 (41.4) | 25 (35.2) | 1.074 | 48 (34.5) | 25 (35.2) | 0.010 | ||||
| Laparoscopy | 950 (58.6) | 46 (64.8) | 91 (65.5) | 46 (64.8) | ||||||
| Receiv adjuvant chemotherapy | 0.720 | 0.824 | ||||||||
| No | 924 (57.0) | 42 (59.2) | 0.129 | 80 (57.6) | 42 (59.2) | 0.049 | ||||
| Yes | 697 (43.0) | 29 (40.8) | 59 (42.4) | 29 (40.8) | ||||||
| Histology | 0.058 | 0.010 | ||||||||
| Signet-ring cell | 332 (20.5) | 8 (11.3) | 3.596 | 37 (26.6) | 8 (11.3) | 6.578 | ||||
| Others | 1,289 (79.5) | 63 (88.7) | 102 (73.4) | 63 (88.7) | ||||||
| Grade | 0.938 | 0.639 | ||||||||
| G1−G2 | 340 (21.0) | 15 (21.1) | 0.127 | 29 (20.9) | 15 (21.1) | 0.896 | ||||
| G3−G4 | 1,097 (67.7) | 47 (66.2) | 98 (70.5) | 47 (66.2) | ||||||
| Unknown | 184 (11.4) | 9 (12.7) | 12 (8.6) | 9 (12.7) | ||||||
| Vascular invasion | 0.454 | 0.321 | ||||||||
| No | 1,356 (83.7) | 57 (80.3) | 0.561 | 119 (85.6) | 57 (80.3) | 0.984 | ||||
| Yes | 265 (16.3) | 14 (19.7) | 20 (14.4) | 14 (19.7) | ||||||
| Neural invasion | 0.217 | 0.422 | ||||||||
| No | 1,245 (76.8) | 59 (83.1) | 1.525 | 109 (78.4) | 59 (83.1) | 0.644 | ||||
| Yes | 376 (23.2) | 12 (16.9) | 30 (21.6) | 12 (16.9) | ||||||
| Lymphatic vessel invasion | 0.503 | 0.721 | ||||||||
| No | 1,414 (87.2) | 60 (84.5) | 0.449 | 120 (86.3) | 60 (84.5) | 0.128 | ||||
| Yes | 207 (12.8) | 11 (15.5) | 19 (13.7) | 11 (15.5) | ||||||
| Primary tumor invasion | 0.860 | 0.814 | ||||||||
| T1 | 287 (17.7) | 16 (22.5) | −0.176 | 32 (23.0) | 16 (22.5) | −0.236 | ||||
| T2 | 138 (8.5) | 4 (5.6) | 7 (5.0) | 4 (5.6) | ||||||
| T3 | 112 (6.9) | 3 (4.2) | 9 (6.5) | 3 (4.2) | ||||||
| T4 | 1,084 (66.9) | 48 (67.6) | 91 (65.5) | 48 (67.6) | ||||||
| Lymph node status | 0.571 | 0.667 | ||||||||
| N0 | 609 (37.6) | 24 (33.8) | −0.566 | 50 (36.0) | 24 (33.8) | −0.430 | ||||
| N1 | 260 (16.0) | 13 (18.3) | 26 (18.7) | 13 (18.3) | ||||||
| N2 | 316 (19.5) | 13 (18.3) | 26 (18.7) | 13 (18.3) | ||||||
| N3 | 436 (26.9) | 21 (29.6) | 37 (26.6) | 21 (29.6) | ||||||
| Metastasis | 0.550 | 0.662 | ||||||||
| No | 1,398 (86.2) | 63 (88.7) | 0.358 | 126 (90.6) | 63 (88.7) | 0.192 | ||||
| Yes | 223 (13.8) | 8 (11.3) | 13 (9.4) | 8 (11.3) | ||||||
| Tumor size (cm) | 0.481 | 0.568 | ||||||||
| <5 | 981 (60.5) | 40 (56.3) | 0.497 | 84 (60.4) | 40 (56.3) | 0.326 | ||||
| ≥5 | 640 (39.5) | 31 (43.7) | 55 (39.6) | 31 (43.7) | ||||||
Long-term oncologic outcomes of T2DM group and non-T2DM group
Patients were followed up for a median of 70 (range, 1−168) months and a mean of 72.9 months. The 5-year CSS rate was 47.0% (95% CI: 34.26%−59.74%) in T2DM group and 58.0% (95% CI: 49.18%−66.82%) in non-T2DM group, with no significant difference between two groups (HR=1.319, 95% CI: 0.868−2.005, P=0.192) (Figure 2A ). However, the 5-year PFS in T2DM group [40.6% (95% CI: 27.86%−53.34%)] is significantly worse than that in non-T2DM group [56.3% (95% CI: 47.28%−65.31%)] (HR=1.516, 95% CI: 1.004−2.290, P=0.045) (Figure 2B ).
2.
Long-term oncologic outcomes of T2DM group and non-T2DM group of GC patients after gastrectomy. (A) 5-year CSS rate between T2DM group and non-T2DM group [47.0% vs. 58.0%, HR=1.319 (95% CI: 0.868−2.005), P=0.192]; (B) 5-year PFS rate between T2DM group and non-T2DM group [40.6%vs. 56.3%, HR=1.516 (95% CI: 1.004−2.290), P=0.045]. T2DM, type 2 diabetes mellitus; GC, gastric cancer; CSS, cancer-specific survival; HR, hazard ratio; 95% CI, 95% confidence interval; PFS, progress-free survival.
Risk factors for survival
Univariate and multivariate analyses of risk factors for CSS and PFS are presented in Table 2 ,3 , respectively. Univariate analyses revealed that the extent of lymphadenectomy less than D2, unradical resection, the open/conversion surgical approaches, without receiving adjuvant chemotherapy, advanced primary tumor invasion, lymph node metastasis, distant organ(s) metastasis and larger (≥5 cm) tumor size were risk factors for CSS. Multivariate analyses further indicated that without receiving adjuvant chemotherapy, advanced primary tumor invasion, lymph node metastasis were independent risk factors for CSS. Notably, T2DM was not identified as a risk factor for CSS. Univariate analyses revealed that T2DM, ascites, proximal or total gastrectomy, the extent of lymphadenectomy less than D2, unradical resection, the open/conversion surgical approaches, without receiving adjuvant chemotherapy, advanced primary tumor invasion, lymph node metastasis, distant organ(s) metastasis were risk factors for PFS. Multivariate analyses further indicated that T2DM, without receiving adjuvant chemotherapy, advanced primary tumor invasion, lymph node metastasis were independent risk factors for PFS. The sensitive analysis by multivariable analysis without PSM was supplied in Supplementary Table S1 ,S2 and showed satisfied results.
2. Univariate and multivariate Cox regression analyses of risk factors for CSS.
| Variables | Univariate analysis | Multivariate | |||
| HR (95% CI) | P | HR (95% CI) | P | ||
| CSS, cancer-specific survival; T2DM, type 2 diabetes mellitus; HBsAg, hepatitis B surface antigen; HR, hazard ratio; 95% CI, 95% confidence interval. | |||||
| T2DM (Yes vs. No) | 1.319 (0.868−2.005) | 0.192 | 1.153 (0.745−1.786) | 0.523 | |
| Sex (Female vs. Male) | 1.422 (0.919−2.199) | 0.110 | |||
| Age (year) | 0.451 | ||||
| 40−69vs. <40 | 0.909 (0.126−6.572) | 0.925 | |||
| ≥70 vs. <40 | 1.248 (0.167−9.334) | 0.829 | |||
| Hepatitis (Yes vs. No) | 1.003 (0.407−2.471) | 0.995 | |||
| HBsAg (+) (Yes vs. No) | 1.379 (0.559−3.401) | 0.481 | |||
| Tumor location | 0.547 | ||||
| Middle vs. Upper | 0.871 (0.450−1.683) | 0.680 | |||
| Lower vs. Upper | 0.767 (0.477−1.241) | 0.281 | |||
| Ascites (Yes vs. No) | 2.428 (0.984−5.988) | 0.054 | 1.491 (0.473−4.702) | 0.495 | |
| Gastrectomy | 0.051 | 0.346 | |||
| Proximal vs. Total | 1.003 (0.480−2.098) | 0.993 | 0.756 (0.327−1.746) | 0.512 | |
| Distal vs. Total | 0.605 (0.390−0.938) | 0.025 | 0.668 (0.387−1.151) | 0.146 | |
| Reconstruction (Roux-en-Y vs. Others) | 1.238 (0.804−1.906) | 0.329 | |||
| Lymphadenectomy (D2/D2+ vs. Others) | 0.367 (0.216−0.622) | <0.001 | 0.338 (0.067−1.699) | 0.188 | |
| Radical resection (Yes vs. No) | 0.300 (0.190−0.474) | <0.001 | 0.998 (0.435−2.289) | 0.995 | |
| Approach (Laparoscopy vs. Open/conversion) | 0.596 (0.394−0.902) | 0.013 | 0.674 (0.397−1.146) | 0.145 | |
| Received adjuvant chemotherapy (Yes vs. No) | 0.587 (0.382−0.903) | 0.014 | 0.341 (0.203−0.571) | <0.001 | |
| Histology (signet-ring vs. Others) | 1.311 (0.812−2.117) | 0.265 | |||
| Grade | 0.160 | 0.442 | |||
| G3−4vs. G1−2 | 1.697 (0.954−3.020) | 0.072 | 1.425 (0.741−2.741) | 0.288 | |
| Unknown vs. G1−2 | 1.850 (0.839−4.079) | 0.127 | 1.014 (0.395−2.607) | 0.977 | |
| Vascular invasion (Yes vs. No) | 1.563 (0.931−2.623) | 0.087 | 1.210 (0.651−2.250) | 0.546 | |
| Neural invasion (Yes vs. No) | 1.356 (0.822−2.237) | 0.230 | |||
| Lymphatic vessel invasion (Yes vs. No) | 1.268 (0.716−2.243) | 0.412 | |||
| Primary tumor invasion | <0.001 | 0.001 | |||
| T2 vs. T1 | 2.971 (0.709−12.450) | 0.136 | 6.086 (1.288−28.749) | 0.023 | |
| T3 vs. T1 | 6.637 (2.023−21.775) | 0.002 | 14.013 (3.457−56.806) | <0.001 | |
| T4 vs. T1 | 7.962 (3.220−19.686) | <0.001 | 9.108 (2.863−28.971) | <0.001 | |
| Lymph node status | <0.001 | 0.028 | |||
| N1 vs. N0 | 1.811 (0.895−3.665) | 0.099 | 0.750 (0.329−1.705) | 0.492 | |
| N2 vs. N0 | 2.730 (1.392−5.355) | 0.003 | 0.990 (0.444−2.206) | 0.980 | |
| N3 vs. N0 | 6.340 (3.551−11.318) | <0.001 | 1.886 (0.908−3.917) | 0.089 | |
| Metastasis (M1 vs. M0) | 3.482 (2.052−5.908) | <0.001 | 0.359 (0.060−2.157) | 0.263 | |
| Tumor size (cm) (≥5 vs. <5) | 2.524 (1.679−3.814) | <0.001 | 1.131 (0.684−1.869) | 0.631 | |
3. Univariate and multivariate Cox regression analyses of risk factors for PFS.
| Variables | Univariate analysis | Multivariate | |||
| HR (95% CI) | P | HR (95% CI) | P | ||
| PFS, progress-free survival; T2DM, type 2 diabetes mellitus; HBsAg, hepatitis B surface antigen; HR, hazard ratio; 95% CI, 95% confidence interval. | |||||
| T2DM (Yes vs. No) | 1.516 (1.004−2.290) | 0.045 | 1.567 (1.021−2.404) | 0.040 | |
| Sex (Female vs. Male) | 1.385 (0.897−2.137) | 0.137 | |||
| Age (year) | 0.297 | ||||
| 40−69vs. <40 | 1.044 (0.145−7.537) | 0.966 | |||
| ≥70 vs. <40 | 1.528 (0.205−11.384) | 0.679 | |||
| Hepatitis (Yes vs. No) | 0.983 (0.399−2.420) | 0.970 | |||
| HBsAg (+) (Yes vs. No) | 1.396 (0.567−3.441) | 0.463 | |||
| Tumor location | 0.505 | ||||
| Middle vs. Upper | 0.913 (0.479−1.741) | 0.783 | |||
| Lower vs. Upper | 0.763 (0.472−1.232) | 0.269 | |||
| Ascites (Yes vs. No) | 2.516 (1.021−6.204) | 0.037 | 1.595 (0.510−4.991) | 0.422 | |
| Gastrectomy | 0.040 | 0.265 | |||
| Proximal vs. Total | 1.013 (0.486−2.112) | 0.972 | 0.803 (0.347−1.857) | 0.609 | |
| Distal vs. Total | 0.598 (0.388−0.923) | 0.020 | 0.638 (0.371−1.097) | 0.104 | |
| Reconstruction (Roux-en-Y vs. others) | 1.250 (0.817−1.912) | 0.300 | |||
| Lymphadenectomy (D2/D2+ vs. others) | 0.339 (0.203−0.568) | <0.001 | 0.337 (0.072−1.580) | 0.168 | |
| Radical resection (Yes vs. No) | 0.284 (0.181−0.445) | <0.001 | 1.009 (0.439−2.320) | 0.983 | |
| Approach (Laparoscopy vs. Open/conversion) | 0.638 (0.423−0.961) | 0.029 | 0.787 (0.464−1.334) | 0.374 | |
| Received adjuvant chemotherapy (Yes vs. No) | 0.558 (0.364−0.856) | 0.006 | 0.309 (0.184−0.520) | <0.001 | |
| Histology (Signet-ring vs. Others) | 1.256 (0.779−2.025) | 0.346 | |||
| Grade | 0.130 | 0.309 | |||
| G3−4vs. G1−2 | 1.742 (0.980−3.094) | 0.059 | 1.601 (0.833−3.080) | 0.158 | |
| Unknown vs. G1−2 | 1.917 (0.870−4.226) | 0.106 | 1.178 (0.458−3.029) | 0.734 | |
| Vascular invasion (Yes vs. No) | 1.632 (0.984−2.708) | 0.054 | 1.178 (0.644−2.157) | 0.594 | |
| Neural invasion (Yes vs. No) | 1.273 (0.773−2.095) | 0.338 | |||
| Lymphatic vessel invasion (Yes vs. No) | 1.349 (0.775−2.347) | 0.285 | |||
| Primary tumor invasion | <0.001 | <0.001 | |||
| T2 vs. T1 | 2.566 (0.641−10.275) | 0.183 | 5.545 (1.212−25.364) | 0.027 | |
| T3 vs. T1 | 5.469 (1.761−16.980) | 0.003 | 12.519 (3.242−48.342) | <0.001 | |
| T4 vs. T1 | 6.841 (2.979−15.709) | <0.001 | 8.102 (2.728−24.060) | <0.001 | |
| Lymph node status | <0.001 | 0.013 | |||
| N1 vs. N0 | 1.748 (0.872−3.501) | 0.115 | 0.773 (0.340−1.754) | 0.538 | |
| N2 vs. N0 | 2.521 (1.299−4.893) | 0.006 | 0.937 (0.423−2.078) | 0.873 | |
| N3 vs. N0 | 6.551 (3.711−11.562) | <0.001 | 2.039 (0.988−4.209) | 0.054 | |
| Metastasis (M1 vs. M0) | 3.819 (2.275−6.411) | <0.001 | 0.381 (0.068−2.147) | 0.274 | |
| Tumor size (cm) (≥5 vs. <5) | 2.606 (1.731−3.923) | <0.001 | 1.136 (0.689−1.874) | 0.617 | |
S1. Multivariate Cox regression analyses of risk factors for CSS before PSM.
| Variables | HR (95% CI) | P |
| CSS, cancer-specific survival; PSM, propensity score matching; T2DM, type 2 diabetes mellitus; HR, hazard ratio; 95% CI, 95% confidence interval. | ||
| T2DM (Yes vs. No) | 1.070 (0.685−1.482) | 0.685 |
| Ascites (Yes vs. No) | 1.760 (1.365−2.267) | <0.001 |
| Gastrectomy | 0.136 | |
| Proximal vs. Total | 0.909 (0.677−1.222) | 0.528 |
| Distal vs. Total | 0.850 (0.724−0.997) | 0.046 |
| Lymphadenectomy (D2/D2+ vs. others) | 0.728 (0.500−1.059) | 0.097 |
| Radical Resection (Yes vs. No) | 0.525 (0.361−0.764) | 0.001 |
| Grade | 0.172 | |
| G3−4vs. G1−2 | 1.059 (0.867−1.293) | 0.574 |
| Unknown vs. G1−2 | 1.263 (0.973−1.639) | 0.079 |
| Vascular invasion (Yes vs. No) | 1.112 (0.925−1.336) | 0.258 |
| Primary tumor invasion | <0.001 | |
| T2 vs. T1 | 2.083 (1.282−3.385) | 0.003 |
| T3 vs. T1 | 2.686 (1.661−4.342) | <0.001 |
| T4 vs. T1 | 3.503 (2.385−5.146) | <0.001 |
| Lymph node status | <0.001 | |
| N1 vs. N0 | 1.555 (1.194−2.024) | 0.001 |
| N2 vs. N0 | 2.266 (1.785−2.876) | <0.001 |
| N3 vs. N0 | 3.751 (2.982−4.718) | <0.001 |
| Metastasis (M1 vs. M0) | 0.997 (0.681−1.461) | 0.989 |
| Tumor size (cm) (≥5 vs. <5) | 1.098 (0.933−1.293) | 0.261 |
S2. Multivariate Cox regression analyses of risk factors for PFS before PSM.
| Variables | HR (95% CI) | P |
| PFS, progress-free survival; PSM, propensity score matching; T2DM, type 2 diabetes mellitus; HR, hazard ratio; 95% CI, 95% confidence interval. | ||
| T2DM (Yes vs. No) | 1.396 (1.001−1.945 ) | 0.049 |
| Ascites (Yes vs. No) | 1.590 (1.233−2.050) | <0.001 |
| Gastrectomy | 0.148 | |
| Proximal vs. Total | 0.845 (0.588−1.214) | 0.362 |
| Distal vs. Total | 0.769 (0.586−1.008) | 0.057 |
| Lymphadenectomy (D2/D2+ vs. others) | 0.522 (0.368−0.740) | <0.001 |
| Radical resection (Yes vs. No) | 0.473 (0.334−0.670) | <0.001 |
| Grade | 0.069 | |
| G3−4vs. G1−2 | 0.990 (0.813−1.204) | 0.918 |
| Unknown vs. G1−2 | 1.271 (0.979−1.649) | 0.071 |
| Vascular invasion (Yes vs. No) | 1.078 (0.894−1.301) | 0.431 |
| Primary tumor invasion | 0.001 | |
| T2 vs. T1 | 2.123 (1.316−3.424) | 0.002 |
| T3 vs. T1 | 2.720 (1.699−4.354) | <0.001 |
| T4 vs. T1 | 3.332 (2.285−4.858) | <0.001 |
| Lymph node status | <0.001 | |
| N1 vs. N0 | 1.667 (1.284−2.164) | <0.001 |
| N2 vs. N0 | 2.434 (1.917−3.091) | <0.001 |
| N3 vs. N0 | 3.669 (2.914−4.619) | <0.001 |
| Metastasis (M1 vs. M0) | 0.938 (0.642−1.371) | 0.742 |
| Tumor size (cm) (≥5 vs. <5) | 0.834 (0.638−1.091) | 0.072 |
Impact of metformin use and blood glucose control on survival for T2DM group
In T2DM group, metformin use subgroup was associated with superior 5-year CSS and PFS compared with non-metformin use subgroup, although the difference was not statistically significant [5-year CSS: 48.0% (95% CI: 32.60%−62.10%)vs. 45.4% (95% CI: 25.02%−65.78%), HR=0.680, 95% CI: 0.352−1.313, P=0.246; 5-year PFS: 43.5% (95% CI: 27.23%−59.77%)vs. 35.7% (95% CI: 15.12%−56.28%), HR=0.763, 95% CI: 0.400−1.454; P=0.406] (Figure 3 ). The 5-year CSS rate was 47.5% (95% CI: 32.60%−62.10%) in good glycemic control subgroup and 44.1% (95% CI: 19.21%−68.99%) in poor glycemic control subgroup, with no significant difference between the groups (HR=0.826, 95% CI: 0.398−1.713, P=0.605) (Figure 4A ). And both two subgroups yielded a similar 5-year PFS rate [42.2% (95% CI: 27.70%−56.70%)vs. 36.3% (95% CI: 11.02%−61.58%), HR=0.908, 95% CI: 0.441−1.871, P=0.792] (Figure 4B ).
3.
Long-term oncologic outcomes of metformin use subgroup and non-metformin use subgroup of GC patients after gastrectomy in T2DM group. (A) 5-year CSS rate between metformin use subgroup and non-metformin use subgroup [48.0% vs. 45.4%, HR=0.680 (95% CI: 0.352−1.313), P=0.246]; (B) 5-year PFS rate between metformin use subgroup and non-metformin use subgroup [43.5%vs. 35.7%, HR=0.763 (95% CI: 0.400−1.454), P=0.406]. GC, gastric cancer; T2DM, type 2 diabetes mellitus; CSS, cancer-specific survival; HR, hazard ratio; 95% CI, 95% confidence interval; PFS, progress-free survival.
4.
Long-term oncologic outcomes of good glycemic control subgroup and poor glycemic control subgroup of GC patients after gastrectomy in T2DM group. (A) 5-year CSS rate between good glycemic control subgroup and poor glycemic control subgroup [47.5% vs. 44.1%, HR=0.826 (95% CI: 0.398−1.713), P=0.605]; (B) 5-year PFS rate between good glycemic control subgroup and poor glycemic control subgroup. [42.2%vs. 36.3%, HR=0.908 (95% CI: 0.441−1.871), P=0.792]. GC, gastric cancer; T2DM, type 2 diabetes mellitus; CSS, cancer-specific survival; HR, hazard ratio; 95% CI, 95% confidence interval; PFS, progress-free survival.
Discussion
Our study investigated the impact of T2DM on long-term oncologic outcomes of GC patients after gastrectomy and found that T2DM is an independent adverse factor of PFS. However, further analysis showed that for GC patients in T2DM group, metformin use was associated with superior survival but without statistical significance, while good control of blood glucose could not improve their prognosis.
Similar to our finding that T2DM had an adverse effect on disease PFS, some other studies have also indicated that T2DM is related to an increased risk and inferior prognosis in many other cancer types (12,19,29,38). And consistent with the clinical consequences, preclinical data have shown that multiple metabolic changes factors, including hyperinsulinemia and insulin-like growth factor I, hyperglycemia, dyslipidemia, adipokines and cytokines, and the gut microbiome (39), potentially contributed to the progression of cancer in T2DM patients. Not only metabolic changes factors that may play a role in promoting tumor growth were discovered, some researchers even further revealed its detailed mechanisms. For example, the dysregulation of the 5’-AMP-activated protein kinase pathway and crosstalk between RAS and insulin-like growth factor 1-cholesterol pathways give rise to a cancer-promoting milieu (40). Also, Wu et al. (41) found hyperglycemic conditions have an adverse effect on the DNA 5-hydroxymethylome, which activate the subsequent molecular pathway and reprogram the epigenome towards an oncogenic state. Their findings indicated that sustained hyperglycemia destabilizes tumor suppressor TET2 and deregulates levels of 5hmC, and glucose-AMPK-TET2-5hmC axis links the level of extracellular glucose to the dynamic regulation of 5hmC, which connects DM to cancer.
However, there are also studies that reported the negative relationship between DM and the prognosis of GC (21,24). In a large cohort of US adults, diabetes was not associated with fatal GC in males or females after 16 years of mortality follow-up. A systematic analysis even showed that overall risk estimates do not present an association between DM and GC (24). Many reasons may result in the inconclusive evidence of the association between DM and risk and cancer prognosis of GC. The heterogeneity of clinical characteristics and biological characteristics, such as the difference of studying population (i.e. East population vs. Western population), the H. pylori infection, TMN stage, treatment strategies and molecular subtypes, usually cannot be comprehensively balanced in the previous studies (24). Further, GC is relatively less common in Western countries, studies in these countries evaluating the association between GC and DM were not powered to evaluate the risk of GC in detail. Besides, the gastrectomy and digestive tract reconstruction could also obviously change the dietary habit, calorie intake, and exercises of patients who had DM, while gastrectomy and digestive tract reconstruction differed in each center.
Metformin is a commonly used oral diabetic agent that reduces hyperinsulinemia and has been reported to be linked to decreased cancer incidence and mortality (30,42-44). Specifically, there was an investigation suggested that metformin may favorably affect the outcome in patients with DM and GC (45). Likewise, recently, research based on East cohort reveals that metformin use was associated with a lower GC risk among H. pylori-eradicated DM patients in duration- and dose-response way (46). Further, preclinical data have provided evidence for the mechanism that may contribute to antineoplastic effects of metformin. Kato et al. (47) showed that metformin inhibits GC cell proliferation and blocks cell cycle in G(0)-G(1) in vitro and in vivo. Specifically, Wu et al. unravelled metformin mediates epigenetic pathway to suppression tumor (41). The metformin use protects AMP-activated protein kinase (AMPK)-mediated phosphorylation of serine 99, thereby increasing TET2 stability and 5hmC levels. This finding indicated that epigenetic regulation by glucose-AMPK-TET2-5hmC axis has a direct effect on the efficacy of metformin in preventing cancer. Consistently, Zakikhani et al. also demonstrated metformin is an AMPK-dependent growth inhibitor for tumor (48). More interesting, a recent study revealed that AMPK activates Krüppel-like factor 4 in progenitors to decrease self-renewal and promote acid-secreting parietal cells fate, while AMPK-PGC1α activation within the acid-secreting parietal cells lineage promotes maturation. The finding explained the potential mechanism that metformin increases acid secretion and lowers the risk of suffering GC in humans (49). Encouragingly, the specific mechanisms of metformin’s role in cancer immunity have also been uncovered recently. Cha et al. (50,51) showed that metformin increases T lymphocyte activity by reducing the stability and membrane localization of programmed death ligand-1 (PD-L1) with AMPK pathway activation, while the hindering of the inhibitory signal of PD-L1 boosts cytotoxic T lymphocyte activity against cancer cells. The revealing of these biological mechanisms provides novel avenues for future clinical investigation about the anti-cancer effect of metformin use and make clinical research more reasonable. However, taking into consideration of the conflicting relationship between T2DM and GC prognosis (19-24) and the complexity that gastrectomy may lead to reliving of hyperglycemia in some T2DM patients with GC (52,53), the association between metformin use and prognosis after radical surgery for GC remains uncertain. Notably, both metformin use and good control of blood glucose cannot confer significantly better prognosis in our research. However, as the complexity of preventing cancer mechanism and effect of metformin, a simple analysis by dichotomizing based on metformin use in our study to determine the anti-GC effect of metformin is not adequate. Thus, subsequent studies are necessary to investigate if some dose of metformin can cause anti-GC effects. And from the perspective of clinical data, TOSCA study sub-analysis indicated there is no association between metformin use or dosages and patient survival on resected CRC patients (54). But on the contrary, Cheung et al. recently showed that metformin use was linked to a lower GC risk among H. pylori-eradicated DM patients in duration- and dose-response mode (46). Hence, although metformin use could not result in statistically significant superior survival, we still could not deny anti-GC effects of metformin in the result of our study. Whether cumulative use could reverse the impact of T2DM on clinical outcomes of patients with GC after gastrectomy might require further study.
Remarkably, the metastasis stage was not an independent prognostic factor for CSS and PFS in our research. However, it has been demonstrated that metastasis stage was associated with a dismal prognosis (55-57). Reviewing the analysis process, we found the following reasons may be attributed to the abnormal result: 1) Patients with metastasis present a lower percentage (10%, 21/210), and the limited number of metastasis status impaired the ability to detect its impact; 2) Patients with metastasis status enrolled in our study were those underwent gastrectomy, and some of them achieved good survival with multi-model treatment. One of the patients with metastasis in this study survived 143 months after surgical treatment. Some patients with metastasis achieved satisfied survival have been reported by our team and other centers (57,58). Thus, some of patients with metastasis status achieved satisfied survival further impaired the survival distinction between M0 and M1 subgroup in our study.
Another point that attracts our attention is that T2DM was only showed statistically significant for PFS of GC patients’ cohort, but not for CSS. It seemed that the reasons may be attributed as follows: 1) After recurring, management of GC patients will be intensified, which will dilute the oncological effect of DM on GC, leading to negative results of CSS; 2) Recurrence and metastasis are very complex multistep processes which are affected by many factors, thus the impact of DM on recurrence and prognosis may fluctuate as time went on; 3) CSS was more prone to be affected by variables of socioeconomic status or performance status (59-61).
There are some limitations in our study. Since the cumulative duration and dose of metformin might affect its anti-cancer effect, this factor had better be taken into considerations in our study. Nevertheless, as the retrospective characteristics of our study, we could not exactly identify the duration of metformin use. But it did not deny the value of this retrospective research. The subsequent well-designed, prospective controlled trials should be designed on the basis of reliable retrospective studies. Also, because of inherent limitations of retrospective studies, some clinical characteristics, such as age, was unbalanced between T2DM and non-T2DM group. Hence, PSM was conducted to avoid potential confounding effects. Along with most basic variables (age, sex), the pT stage, N stage and M stage which were considered as the most important factors to assess the disease status, were included as the covariates of PSM. To make the important variables comparable further, we set caliper of matching as 0.01; and to make the oncologic effect to be assessed adequately in retrospective study, we only enrolled patients who underwent gastrectomy before the year of 2016 and conducted last follow-up in January 2019. Also, the gastrectomy and digestive tract reconstruction could also obviously change the dietary habit, calorie intake, and exercises of patients, which make assessment of DM effect on GC more complicated. But luckily, after PSM, the variables of gastrectomy and digestive tract reconstruction were well balanced. Besides, nearby 15% of the majority of advanced tumors were not radically resected. However, these data characteristics accorded with the epidemiologic features of GC in China and Western countries where advanced GC accounts for far larger proportion. To emphasize experience and evidence focused on the real world, we did not exclude these advanced tumors.
Conclusions
T2DM promoted disease progress of GC after gastrectomy but did not lead to the significant prognosis discrepancy of CSS in the cohort of Nanfang Hospital. The anticancer effect of metformin needs to be further confirmed by well-designed, prospective controlled trials on GC patients with T2DM and with the exact information of cumulative duration of metformin and dynamic monitoring the control of blood glucose. Also, as the adjuvant treatment strategies based on GC subgroups of specific pathological stages have achieved great progress, treatment tactics according to specific biological characteristics are moving forward (62-64). Thus, researches to explore the biological behavior of GC with DM and the mechanism of the impact of DM on GC are necessary for GC to make adjuvant treatments more tailored and individualized.
Acknowledgements
The current study was supported by the National Natural Science Foundation of China (No. 81872013); Clinical Research Program of Nanfang Hospital, Southern Medical University (No. 2018CR017); National Key Clinical Specialty Discipline Construction Program of China (No. [2012]121); Science and Technology Planning Project of Guangdong Province (No. 2017B020226005).
Footnote
Conflicts of Interest: The authors have no conflicts of interest to declare.
Contributor Information
Tuanjie Li, Email: ehbhltj@hotmail.com.
Guoxin Li, Email: gzliguoxin@163.com.
Jiang Yu, Email: balbc@163.com.
References
- 1.Bray F, Ferlay J, Soerjomataram I, et al Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68:394–424. doi: 10.3322/caac.21492. [DOI] [PubMed] [Google Scholar]
- 2.Sexton RE, Hallak M, Uddin MH, et al Gastric cancer heterogeneity and clinical outcomes. Technol Cancer Res Treat. 2020;19:1533033820935477. doi: 10.1177/1533033820935477. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Siegel RL, Miller KD, Jemal A Cancer statistics, 2019. CA Cancer J Clin. 2019;69:7–34. doi: 10.3322/caac.21551. [DOI] [PubMed] [Google Scholar]
- 4.National Health Commission of the People’s Republic of China Chinese guidelines for diagnosis and treatment of gastric cancer 2018 (English version) Chin J Cancer Res. 2019;31:707–37. doi: 10.21147/j.issn.1000-9604.2019.05.01. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Yu J, Huang C, Sun Y, et al Effect of laparoscopic vs. open distal gastrectomy on 3-year disease-free survival in patients with locally advanced gastric cancer: The CLASS-01 randomized clinical trial . JAMA. 2019;321:1983–92. doi: 10.1001/jama.2019.5359. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Chen XH, Hu YF, Luo J, et al The safety of esophagojejunostomy via a transorally inserted-anvil method vs extracorporeal anastomosis using a circular stapler during total gastrectomy for Siewert type 2 adenocarcinoma of the esophagogastric junction. Gastroenterol Rep (Oxf) 2020;8:242–51. doi: 10.1093/gastro/goz046. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Xue K, Ying X, Bu Z, et al Oxaliplatin plus S-1 or capecitabine as neoadjuvant or adjuvant chemotherapy for locally advanced gastric cancer with D2 lymphadenectomy: 5-year follow-up results of a phase II-III randomized trial. Chin J Cancer Res. 2018;30:516–25. doi: 10.21147/j.issn.1000-9604.2018.05.05. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.D’Angelica M, Gonen M, Brennan MF, et al Patterns of initial recurrence in completely resected gastric adenocarcinoma. Ann Surg. 2004;240:808–16. doi: 10.1097/01.sla.0000143245.28656.15. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Simmons RK, Echouffo-Tcheugui JB, Sharp SJ, et al Screening for type 2 diabetes and population mortality over 10 years (ADDITION-Cambridge): a cluster-randomised controlled trial. Lancet. 2012;380:1741–8. doi: 10.1016/S0140-6736(12)61422-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Engelgau MM, Gregg EW Tackling the global diabetes burden: will screening help? Lancet. 2012;380:1716–8. doi: 10.1016/S0140-6736(12)61682-1. [DOI] [PubMed] [Google Scholar]
- 11.Giovannucci E, Harlan DM, Archer MC, et al Diabetes and cancer: a consensus report. Diabetes Care. 2010;33:1674–85. doi: 10.2337/dc10-0666. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Shi Y, Hu FB The global implications of diabetes and cancer. Lancet. 2014;383:1947–8. doi: 10.1016/S0140-6736(14)60886-2. [DOI] [PubMed] [Google Scholar]
- 13.Arcidiacono B, Iiritano S, Nocera A, et al Insulin resistance and cancer risk: an overview of the pathogenetic mechanisms. Exp Diabetes Res. 2012;2012:789174. doi: 10.1155/2012/789174. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Srokowski TP, Fang S, Hortobagyi GN, et al Impact of diabetes mellitus on complications and outcomes of adjuvant chemotherapy in older patients with breast cancer. J Clin Oncol. 2009;27:2170–6. doi: 10.1200/JCO.2008.17.5935. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Peairs KS, Barone BB, Snyder CF, et al Diabetes mellitus and breast cancer outcomes: a systematic review and meta-analysis. J Clin Oncol. 2011;29:40–6. doi: 10.1200/JCO.2009.27.3011. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Meyerhardt JA, Catalano PJ, Haller DG, et al Impact of diabetes mellitus on outcomes in patients with colon cancer. J Clin Oncol. 2003;21:433–40. doi: 10.1200/JCO.2003.07.125. [DOI] [PubMed] [Google Scholar]
- 17.Vernieri C, Pusceddu S, de Braud F Impact of metformin on systemic metabolism and survival of patients with advanced pancreatic neuroendocrine tumors. Front Oncol. 2019;9:902. doi: 10.3389/fonc.2019.00902. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Bensimon L, Yin H, Suissa S, et al Type 2 diabetes and the risk of mortality among patients with prostate cancer. Cancer Causes Control. 2014;25:329–38. doi: 10.1007/s10552-013-0334-6. [DOI] [PubMed] [Google Scholar]
- 19.Rao Kondapally Seshasai S, Kaptoge S, Thompson A, et al Diabetes mellitus, fasting glucose, and risk of cause-specific death. N Engl J Med. 2011;364:829–41. doi: 10.1056/NEJMoa1008862. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Ge Z, Ben Q, Qian J, et al Diabetes mellitus and risk of gastric cancer: a systematic review and meta-analysis of observational studies. Eur J Gastroenterol Hepatol. 2011;23:1127–35. doi: 10.1097/MEG.0b013e32834b8d73. [DOI] [PubMed] [Google Scholar]
- 21.Coughlin SS, Calle EE, Teras LR, et al Diabetes mellitus as a predictor of cancer mortality in a large cohort of US adults. Am J Epidemiol. 2004;159:1160–7. doi: 10.1093/aje/kwh161. [DOI] [PubMed] [Google Scholar]
- 22.Inoue M, Iwasaki M, Otani T, et al Diabetes mellitus and the risk of cancer: results from a large-scale population-based cohort study in Japan. Arch Intern Med. 2006;166:1871–7. doi: 10.1001/archinte.166.17.1871. [DOI] [PubMed] [Google Scholar]
- 23.Yoon JM, Son KY, Eom CS, et al Pre-existing diabetes mellitus increases the risk of gastric cancer: a meta-analysis. World J Gastroenterol. 2013;19:936–45. doi: 10.3748/wjg.v19.i6.936. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Marimuthu SP, Vijayaragavan P, Moysich KB, et al Diabetes mellitus and gastric carcinoma: Is there an association? J Carcinog. 2011;10:30. doi: 10.4103/1477-3163.90481. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Zhang H, Gao C, Fang L, et al Metformin and reduced risk of hepatocellular carcinoma in diabetic patients: a meta-analysis. Scand J Gastroenterol. 2013;48:78–87. doi: 10.3109/00365521.2012.719926. [DOI] [PubMed] [Google Scholar]
- 26.Kumar S, Meuter A, Thapa P, et al Metformin intake is associated with better survival in ovarian cancer: a case-control study. Cancer. 2013;119:555–62. doi: 10.1002/cncr.27706. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Zhou PT, Li B, Liu FR, et al Metformin is associated with survival benefit in cancer patients with concurrent type 2 diabetes: a systematic review and meta-analysis. Oncologist. 2017;8:25242–50. doi: 10.18632/oncotarget.15692. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Landman GW, Kleefstra N, van Hateren KJ, et al Metformin associated with lower cancer mortality in type 2 diabetes: ZODIAC-16. Diabetes Care. 2010;33:322–6. doi: 10.2337/dc09-1380. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Kim HJ, Lee S, Chun KH, et al Metformin reduces the risk of cancer in patients with type 2 diabetes: An analysis based on the Korean National Diabetes Program Cohort. Medicine (Baltimore) 2018;97:e0036. doi: 10.1097/MD.0000000000010036. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Evans JM, Donnelly LA, Emslie-Smith AM, et al Metformin and reduced risk of cancer in diabetic patients. BMJ. 2005;330:1304–5. doi: 10.1136/bmj.38415.708634.F7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Lee CK, Jung M, Jung I, et al Cumulative metformin use and its impact on survival in gastric cancer patients after gastrectomy. Ann Surg. 2016;263:96–102. doi: 10.1097/SLA.0000000000001086. [DOI] [PubMed] [Google Scholar]
- 32.Chen W, Zheng R, Baade PD, et al Cancer statistics in China, 2015. CA Cancer J Clin. 2016;66:115–32. doi: 10.3322/caac.21338. [DOI] [PubMed] [Google Scholar]
- 33.Hu YF, Yu J, Zhang C, et al Development and implementation of a clinical data mining system for gastric cancer surgery. Zhonghua Wei Chang Wai Ke Za Zhi. 2010;13:510–5. [PubMed] [Google Scholar]
- 34.Washington K 7th edition of the AJCC cancer staging manual: stomach. Ann Surg Oncol. 2010;17:3077–9. doi: 10.1245/s10434-010-1362-z. [DOI] [PubMed] [Google Scholar]
- 35.Ettinger DS, Kuettel M, Malin J, et al NCCN roundtable: What are the characteristics of an optimal clinical practice guideline? J Natl Compr Canc Netw. 2015;13(5 suppl):640–2. doi: 10.6004/jnccn.2015.0190. [DOI] [PubMed] [Google Scholar]
- 36.Smyth EC, Verheij M, Allum W, et al Gastric cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2016;27(Suppl 5):v38–v49. doi: 10.1093/annonc/mdw350. [DOI] [PubMed] [Google Scholar]
- 37.Chen X, Chen Y, Hu Y, et al The methods of lymph node examination make a difference to node staging and detection of N3b node status for gastric cancer. Front Oncol. 2020;10:123. doi: 10.3389/fonc.2020.00123. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Du W, Simon MS Racial disparities in treatment and survival of women with stage I-III breast cancer at a large academic medical center in metropolitan Detroit. Breast Cancer Res Treat. 2005;91:243–8. doi: 10.1007/s10549-005-0324-9. [DOI] [PubMed] [Google Scholar]
- 39.Gallagher EJ, LeRoith D Obesity and diabetes: The increased risk of cancer and cancer-related mortality. Physiol Rev. 2015;95:727–48. doi: 10.1152/physrev.00030.2014. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Yang X, Lee HM, Chan JC Drug-subphenotype interactions for cancer in type 2 diabetes mellitus. Nat Rev Endocrinol. 2015;11:372–9. doi: 10.1038/nrendo.2015.37. [DOI] [PubMed] [Google Scholar]
- 41.Wu D, Hu D, Chen H, et al Glucose-regulated phosphorylation of TET2 by AMPK reveals a pathway linking diabetes to cancer. Nature. 2018;559:637–41. doi: 10.1038/s41586-018-0350-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Tsai MJ, Yang CJ, Kung YT, et al Metformin decreases lung cancer risk in diabetic patients in a dose-dependent manner. Lung Cancer. 2014;86:137–43. doi: 10.1016/j.lungcan.2014.09.012. [DOI] [PubMed] [Google Scholar]
- 43.Nie Z, Zhu H, Gu M Reduced colorectal cancer incidence in type 2 diabetic patients treated with metformin: a meta-analysis. Pharm Biol. 2016;54:2636–42. doi: 10.1080/13880209.2016.1176057. [DOI] [PubMed] [Google Scholar]
- 44.Zingales V, Distefano A, Raffaele M, et al Metformin: A bridge between diabetes and prostate cancer. Front Oncol. 2017;7:243. doi: 10.3389/fonc.2017.00243. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Greenhill C Gastric cancer. Metformin improves survival and recurrence rate in patients with diabetes and gastric cancer. Nat Rev Gastroenterol Hepatol. 2015;12:124. doi: 10.1038/nrgastro.2015.9. [DOI] [PubMed] [Google Scholar]
- 46.Cheung KS, Chan EW, Wong A, et al Metformin use and gastric cancer risk in diabetic patients after Helicobacter pylori eradication . J Natl Cancer Inst. 2019;111:484–9. doi: 10.1093/jnci/djy144. [DOI] [PubMed] [Google Scholar]
- 47.Kato K, Gong J, Iwama H, et al The antidiabetic drug metformin inhibits gastric cancer cell proliferation in vitro and in vivo . Mol Cancer Ther. 2012;11:549–60. doi: 10.1158/1535-7163.MCT-11-0594. [DOI] [PubMed] [Google Scholar]
- 48.Zakikhani M, Dowling R, Fantus IG, et al Metformin is an AMP kinase-dependent growth inhibitor for breast cancer cells. Cancer Res. 2006;66:10269–73. doi: 10.1158/0008-5472.CAN-06-1500. [DOI] [PubMed] [Google Scholar]
- 49.Miao ZF, Adkins-Threats M, Burclaff JR, et al A metformin-responsive metabolic pathway controls distinct steps in gastric progenitor fate decisions and maturation. Cell Stem Cell. 2020;26:910–25. doi: 10.1016/j.stem.2020.03.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Cha JH, Yang WH, Xia W, et al Metformin promotes antitumor immunity via endoplasmic-reticulum-associated degradation of PD-L1. Mol Cell. 2018;71:606–20. doi: 10.1016/j.molcel.2018.07.030. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Eikawa S, Nishida M, Mizukami S, et al Immune-mediated antitumor effect by type 2 diabetes drug, metformin. Proc Natl Acad Sci U S A. 2015;112:1809–14. doi: 10.1073/pnas.1417636112. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Kwon Y, Abdemur A, Lo ME, et al The foregut theory as a possible mechanism of action for the remission of type 2 diabetes in low body mass index patients undergoing subtotal gastrectomy for gastric cancer. Surg Obes Relat Dis. 2014;10:235–42. doi: 10.1016/j.soard.2013.09.013. [DOI] [PubMed] [Google Scholar]
- 53.An JY, Kim YM, Yun MA, et al Improvement of type 2 diabetes mellitus after gastric cancer surgery: short-term outcome analysis after gastrectomy. World J Gastroenterol. 2013;19:9410–7. doi: 10.3748/wjg.v19.i48.9410. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Vernieri C, Galli F, Ferrari L, et al Impact of metformin use and diabetic status during adjuvant fluoropyrimidine-oxaliplatin chemotherapy on the outcome of patients with resected colon cancer: A TOSCA study subanalysis. Oncologist. 2019;24:385–93. doi: 10.1634/theoncologist.2018-0442. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Li Z, Fan B, Shan F, et al Gastrectomy in comprehensive treatment of advanced gastric cancer with synchronous liver metastasis: a prospectively comparative study. World J Surg Oncol. 2015;13:212. doi: 10.1186/s12957-015-0627-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56.Luo Z, Rong Z, Huang C Surgery strategies for gastric cancer with liver metastasis. Front Oncol. 2019;9:1353. doi: 10.3389/fonc.2019.01353. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57.Yamaguchi K, Yoshida K, Tanahashi T, et al The long-term survival of stage IV gastric cancer patients with conversion therapy. Gastric Cancer. 2018;21:315–23. doi: 10.1007/s10120-017-0738-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Geng X, Liu H, Lin T, et al Survival benefit of gastrectomy for gastric cancer with peritoneal carcinomatosis: a propensity score-matched analysis. Cancer Med. 2016;5:2781–91. doi: 10.1002/cam4.877. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 59.Fontana V, Decensi A, Orengo MA, et al Socioeconomic status and survival of gastric cancer patients. Eur J Cancer. 1998;34:537–42. doi: 10.1016/s0959-8049(97)10098-3. [DOI] [PubMed] [Google Scholar]
- 60.Vercelli M, Lillini R, Capocaccia R, et al Cancer survival in the elderly: effects of socio-economic factors and health care system features (ELDCARE project) Eur J Cancer. 2006;42:234–42. doi: 10.1016/j.ejca.2005.07.032. [DOI] [PubMed] [Google Scholar]
- 61.Kogevinas M, Porta M Socioeconomic differences in cancer survival: a review of the evidence. IARC Sci Publ. 1997;138:177–206. [PubMed] [Google Scholar]
- 62.Chen X, Liu H, Li G, et al Implications of clinical research on adjuvant chemotherapy for gastric cancer: Where to go next? Chin J Cancer Res. 2019;31:892–900. doi: 10.21147/j.issn.1000-9604.2019.06.05. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 63.Chen L, Hao Y, Cong X, et al Peripheral venous blood platelet-to-lymphocyte ratio (PLR) for predicting the survival of patients with gastric cancer treated with SOX or XELOX regimen neoadjuvant chemotherapy. Technol Cancer Res Treat. 2019;18:1533033819829485. doi: 10.1177/1533033819829485. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 64.Zhang Z, Xie T, Zhang X, et al Immune checkpoint inhibitors for treatment of advanced gastric or gastroesophageal junction cancer: Current evidence and future perspectives. Chin J Cancer Res. 2020;32:287–302. doi: 10.21147/j.issn.1000-9604.2020.03.02. [DOI] [PMC free article] [PubMed] [Google Scholar]