Fourth, due to the lack of external data, we were unable to design a validation group to verify our findings. In conclusion, our study first reported the correlation between the preoperative AGR and prognosis of early NSCLC. regression analyses were used to identify independent prognostic factors, and the KaplanCMeier method was used to estimate survival curves. Results: A total of 279 early stage NSCLC patients were enrolled in our study with the median follow-up of 39 months (range 1C56 months). The statistical analyses manifested that the age (hazard ratio (HR)=1.045, 95% confidence interval (95% CI): 1.010C1.081, (%)145 (51.97)Age, mean SD, years62.169.25Smoking history, (%)124 (44.44)Preoperative comorbidityHypertension, (%)77 (27.60)Diabetes mellitus, (%)28 (10.04)COPD, (%)39 (13.98)CHD, (%)13 (4.66)Emphysema, (%)42 (15.05)Any, (%)128 (45.88)Tumor location (left), (%)101 (36.20)HistologyAC, (%)194 (69.53)SC, (%)50 (17.92)Others, (%)35 (12.54)Extent of resectionLobectomy, (%)190 (68.10)Segmentectomy, (%)89 (31.90)TNM stageI, (%)246 (88.17)II, (%)33 (11.83) Open in a separate windows Abbreviations: SD, standard deviation; COPD, chronic obstructive pulmonary disease; CHD, coronary heart disease; VE-822 AC, adenocarcinoma; SC, squamous carcinoma; TNM, VE-822 tumor-node-metastasis. The optimal cutoff values according to ROC curves The cutoff value of the AGR for predicting OS was 1.51 (sensitivity of 69.1% and specificity of 67.0%, area under the curve (AUC) =0.698) (Figure 2A). The cutoff value of the AGR for predicting DFS was also 1.51 (sensitivity of 57.1% and specificity of 64.1%, AUC =0.589) (Figure 2B). Open in a separate window Physique 2 (A) ROC curve of the AGR for predicting OS. (B) ROC curve of the AGR for predicting DFS. Abbreviations: ROC, receiver operating characteristic; AGR, albumin-globulin ratio; OS, overall survival; DFS, disease-free survival. Associations between the AGR and clinicopathologic characteristics According to the optimal cutoff value of AGR, we divided 112 patients with AGR 1.51 into the low AGR group and 167 patients with AGR 1.51 into the high AGR group and then we compared differences of clinicopathological characteristics between the two groups (Table 2). The preoperative AGR significantly correlated with the FEV1 ((%)58 (51.79)87 (52.10)0.959Age, mean SD, years63.248.5761.449.640.110Smoking history, (%)54 (48.21)70 (41.92)0.299BMI, mean SD, kg/m223.143.1623.652.750.155Preoperative comorbidityHypertension, (%)29 (25.89)48 (28.74)0.602Diabetes mellitus, (%)12 (10.71)16 (9.58)0.757COPD, (%)19 (16.96)20 (11.98)0.239CHD, (%)6 (5.36)7 (4.19)0.651Emphysema, (%)21 (18.75)21 (12.57)0.157Preoperative lung functionFEV1, mean SD, L2.130.602.310.740.038FVC, mean SD, L2.880.723.120.870.026FEV1/FVC, %74.2210.8474.1211.740.946Tumor location (Left), (%)40 (35.71)61 (36.53)0.890Tumor size, median, cm2.911.522.301.14 0.001Histology (AC), (%)72 (64.29)122 (73.05)0.238Resection (lobectomy), (%)85 (75.89)105 (62.87)0.195TNM stage I, (%)92 (82.14)154 (92.22)0.011Preoperative albumin level, g/L40.253.2943.233.11 0.001Preoperative globulin level, g/L30.643.6824.712.50 0.001 Open in a separate window Abbreviations: AGR, albuminCglobulin ratio; SD, standard deviation; BMI, body mass index; COPD, chronic obstructive pulmonary disease; CHD, coronary heart disease; FEV1, forced expiratory volume in one second; FVC, forced vital capacity; AC, adenocarcinoma; SC, squamous carcinoma; TNM, tumor-node-metastasis. Univariate and multivariate Cox regression analyses for OS Univariate analyses exhibited that the age ( em P /em =0.002), history of smoking ( em P /em =0.039), history of emphysema ( em P /em =0.040), tumor size ( em P /em =0.043), low albumin level ( em P /em =0.001), high globulin level ( em P /em 0.001) and AGR 1.51 ( em P /em 0.001) were potential risk factors for any worse OS. Multivariate analyses indicated that only the age (hazard ratio (HR)=1.045, 95% confidence interval (95% CI): 1.010C1.081, em P /em =0.011) and AGR 1.51 (HR=3.424, 95% CI: 1.600C7.331, em P /em =0.002) significantly correlated with poor OS. Detailed information is shown in Table 3. Table 3 Univariate and multivariate Cox regression analyses to assess the prognostic factors of OS thead th rowspan=”1″ colspan=”1″ Characteristics /th th colspan=”2″ rowspan=”1″ Univariate analysis /th th colspan=”2″ rowspan=”1″ Multivariate analysis /th th rowspan=”1″ colspan=”1″ HR (95%CI) /th th rowspan=”1″ colspan=”1″ em P /em -value /th th rowspan=”1″ colspan=”1″ HR (95%CI) /th th rowspan=”1″ colspan=”1″ em P /em -value /th VE-822 VE-822 /thead Male1.193 (0.701C2.029)0.515Age1.051 (1.018C1.085)0.0021.045 (1.010C1.081)0.011Smoking history1.752 (1.028C2.986)0.0391.521 (0.864C2.678)0.146BMI1.000 (0.913C1.096)0.996Hypertension0.798 (0.429C1.487)0.478Diabetes mellitus0.292 (0.071C1.198)0.087COPD1.702 (0.878C3.301)0.115CHD1.317 (0.411C4.218)0.643Emphysema1.923 (1.032C3.586)0.0401.263 (0.653C2.442)0.487Preoperative lung functionFEV10.690 (0.452C1.054)0.086FVC0.758 (0.533C1.080)0.125FEV1/FVC0.993 (0.970C1.016)0.538Tumor location (left)1.040 (0.600C1.803)0.888Tumor size1.196 (1.006C1.421)0.0430.990 (0.814C1.205)0.921Histology1.113 (0.700C1.771)0.650Lobectomy1.511 (0.811C2.816)0.194TNM stage II1.882 (0.948C3.737)0.071Preoperative albumin0.875 (0.811C0.945)0.0011.018 VE-822 (0.949C1.093)0.610Preoperative globulin1.096 (1.045C1.149) 0.0010.966 (0.887C1.052)0.422AGR 1.514.304 (2.425C7.638) 0.0013.424 (1.600C7.331)0.002 Open in a separate window Abbreviations: OS, overall survival; BMI, body mass index; COPD, chronic obstructive pulmonary disease; CHD, coronary heart disease; FEV1, forced expiratory volume in one second; FVC, forced vital capacity; TNM, tumor-node-metastasis; AGR, albuminCglobulin ratio. Univariate and multivariate Cox regression analyses for DFS Univariate analyses manifested that the history of COPD ( em P /em =0.022), history of emphysema ( em P /em Rabbit Polyclonal to Stefin A =0.015), tumor size ( em P /em 0.001), lobectomy ( em P /em =0.013), high globulin level ( em P /em =0.043) and AGR 1.51 ( em P /em =0.001) were potential risk factors for any worse DFS. On multivariate analysis, larger.