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Preoperative AminoIndex Cancer Screening (AICS) abnormalities predict postoperative recurrence in patients undergoing curative resection for non-small cell lung cancer.

ABSTRACT: BACKGROUND:AminoIndex™ Cancer Screening (AICS (lung)) was developed as a screening test for lung cancer using a multivariate analysis of plasma-free amino acid (PFAA) profiles. According to the developed index composed of PFAA, the probability of lung cancer was categorized into AICS (lung) ranks A, B, and C in order of increasing risk. The aim of the present study was to investigate the relationship between the preoperative AICS (lung) rank and surgical outcomes in patients who underwent curative resection for non-small cell lung cancer (NSCLC). METHODS:Preoperative blood samples were collected from 297 patients who underwent curative resection for NSCLC between 2006 and 2015. PFAA concentrations were measured. The relationship between the preoperative AICS (lung) rank and clinicopathological factors was examined. The effects of the preoperative AICS (lung) rank on postoperative outcomes were also analyzed. RESULTS:The AICS (lung) rank was A in 93 patients (31.3%), B in 82 (27.6%), and C in 122 (41.1%). The AICS (lung) rank did not correlate with any clinicopathological factors, except for age. Based on follow-up data (median follow-up period of 6?years), postoperative recurrence was observed in 22 rank A patients (23.7%), 15 rank B (18.3%) and 49 rank C (40.2%). In the univariate analysis, preoperative AICS (lung) rank C was a worse factor of recurrence-free survival (p?=?0.0002). The multivariate analysis identified preoperative AICS (lung) rank C (HR: 2.17, p?=?0.0005) as a significant predictor of postoperative recurrence, particularly in patients with early-stage disease or adenocarcinoma. CONCLUSION:Preoperative AICS (lung) rank C is a high-risk predictor of postoperative recurrence in patients undergoing curative resection for NSCLC.

SUBMITTER: Higashiyama M

PROVIDER: S-EPMC7659101 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Preoperative AminoIndex Cancer Screening (AICS) abnormalities predict postoperative recurrence in patients undergoing curative resection for non-small cell lung cancer.

Higashiyama Masahiko M Miyazaki Ryohei R Yamamoto Hiroshi H Anayama Takashi T Kikuchi Shinya S Hirohashi Kentaro K Okami Jiro J Maniwa Tomohiro T Kimura Toru T Orihashi Kazumasa K Imamura Fumio F

BMC cancer 20201112 1

<h4>Background</h4>AminoIndex™ Cancer Screening (AICS (lung)) was developed as a screening test for lung cancer using a multivariate analysis of plasma-free amino acid (PFAA) profiles. According to the developed index composed of PFAA, the probability of lung cancer was categorized into AICS (lung) ranks A, B, and C in order of increasing risk. The aim of the present study was to investigate the relationship between the preoperative AICS (lung) rank and surgical outcomes in patients who underwen ...[more]

PMID: 33183251

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Project description:ObjectiveTo determine the benefits of preoperative breathing exercises on hospital length of stay (LOS), pneumonia, postoperative pulmonary complications (PPC), 6-minute walk distance (6MWD), forced expiratory volume in 1 second (FEV1), and health-related quality of life (HRQOL) in patients undergoing surgical lung cancer resection.Data sourcesPubMed, EMBASE, Web of Science Core Collection, and Cochrane Central Register of Controlled Trials were comprehensively searched from inception to March 2021.Study selectionOnly studies including preoperative inspiratory muscle training (IMT) and/or breathing exercises compared with a nontraining control group were included. The meta-analysis was done using Cochrane software for multiple variables including LOS, pneumonia, PPC, 6MWD, FEV1, mortality, and HRQOL.Data extractionTwo authors extracted the data of the selected studies. The primary outcomes were LOS and PPC.Data synthesisA total of 10 studies were included in this meta-analysis, 8 of which had both IMT and aerobic exercise. Pooled data for patients who performed preoperative breathing exercises, compared with controls, demonstrated a decrease in LOS with a pooled mean difference of -3.44 days (95% confidence interval [CI], -4.14 to -2.75; P<.01). Subgroup analysis also demonstrated that LOS was further reduced when breathing exercises were combined with aerobic exercise (χ2, 4.85; P=.03). Preoperative breathing exercises reduce pneumonia and PPCs with an odds ratio of 0.37 (95% CI, 0.18-0.75; P<.01) and 0.37 (95% CI, 0.21-0.65; P<.01), respectively. An increase in 6MWD of 20.2 meters was noted in those performing breathing exercises (95% CI, 9.12-31.21; P<.01). No significant differences were noted in FEV1, mortality, or HRQOL.ConclusionsPreoperative breathing exercises reduced LOS, PPC, and pneumonia and potentially improved 6MWD in patients undergoing surgical lung cancer resection. Breathing exercises in combination with aerobic exercise yielded greater reductions in LOS. Randomized controlled trials are needed to test the feasibility of introducing a preoperative breathing exercise program in this patient population.

Project description:BACKGROUND:High-quality randomized controlled trials have demonstrated the benefit of radiotherapy (RT) in patients with radical resected gastric cancer (GC), however, utilization rates of postoperative RT remain remarkably low. Patterns, incidences, and time of recurrence provide biological bases for clinical monitoring of GC patients and guiding potential complementary therapies. Thus, the aim of this study is to understand the location of locoregional recurrence which may allow individualized RT strategies and minimize radiation-related toxic effects. METHODS:A relatively large sample of GC patients in a single institution who had undergone curative D2 resection was retrospectively reviewed and the relevant recurrence patterns were illustrated. Independent recurrence-related risk factors were analyzed by logistic regression analysis. New logistic regression models were further developed to predict the probability of recurrence. RESULTS:Overall, among 776 GC patients who had continuous and complete follow-up data, 300 cases relapsed after curative resection. Lymphovascular invasion, lymph node metastases, and tumor stage were indicators for early recurrence. Peritoneal, regional, local, and distant recurrence initially occurred in 51 (6.6%), 151 (19.4%), 56 (7.2%), and 164 (21.1%) patients, respectively. Among patients with regional recurrence, the most common sites were lymph node stations 16a2, 8, 12, 16b1, and 9. Remnant stomach recurrence was not so prominent that it seemed reasonable to be excluded from an irradiation field for patients with negative surgical/pathologic margins. CONCLUSIONS:For GC patients who underwent radical D2 resection, distant and regional recurrences were still common. Besides, optimizing regional control of lymph nodes outside the D2 dissected area was crucial for rational design of the RT field. Furthermore, the new logistic regression models might act as useful tools to evaluate recurrence risk and determine which patients should receive postoperative chemoradiotherapy.

Project description:ImportanceAdrenocortical carcinoma (ACC) is a rare but aggressive endocrine tumor, and the prognostic factors associated with long-term outcomes after surgical resection remain poorly defined.ObjectivesTo define clinicopathological variables associated with recurrence-free survival (RFS) and overall survival (OS) after curative surgical resection of ACC and to propose nomograms for individual risk prediction.Design, setting, and participantsNomograms to predict RFS and OS after surgical resection of ACC were proposed using a multi-institutional cohort of patients who underwent curative-intent surgery for ACC at 13 major institutions in the United States between March 17, 1994, and December 22, 2014. The dates of our study analysis were April 15, 2015, to May 12, 2015.Main outcomes and measuresThe discriminative ability and calibration of the nomograms to predict RFS and OS were tested using C statistics, calibration plots, and Kaplan-Meier curves.ResultsIn total, 148 patients who underwent surgery for ACC were included in the study. The median patient age was 53 years, and 65.5% (97 of 148) of the patients were female. One-third of the patients (35.1% [52 of 148]) had a functional tumor, and the median tumor size was 11.2 cm. Most patients (77.7% [115 of 148]) underwent R0 resection, and 8.8% (13 of 148) of the patients had N1 disease. Using backward stepwise selection of clinically important variables with the Akaike information criterion, the following variables were incorporated in the prediction of RFS: tumor size of at least 12 cm (hazard ratio [HR], 3.00; 95% CI, 1.63-5.70; P < .001), positive nodal status (HR, 4.78; 95% CI, 1.47-15.50; P = .01), stage III/IV (HR, 1.80; 95% CI, 0.95-3.39; P = .07), cortisol-secreting tumor (HR, 2.38; 95% CI, 1.27-4.48; P = .01), and capsular invasion (HR, 1.96; 95% CI, 1.02-3.74; P = .04). Factors selected as predicting OS were tumor size of at least 12 cm (HR, 1.78; 95% CI, 1.00-3.17; P = .05), positive nodal status (HR, 5.89; 95% CI, 2.05-16.87; P = .001), and R1 margin (HR, 2.83; 95% CI, 1.51-5.30; P = .001). The discriminative ability and calibration of the nomograms revealed good predictive ability as indicated by the C statistics (0.74 for RFS and 0.70 for OS).Conclusions and relevanceIndependent predictors of survival and recurrence risk after curative-intent surgery for ACC were selected to create nomograms predicting RFS and OS. The nomograms were able to stratify patients into prognostic groups and performed well on internal validation.

Project description:PurposePatients with rectal cancer without distant metastases are typically treated with radical surgery. Post curative resection, several factors can affect tumor recurrence. This study aimed to analyze factors related to rectal cancer recurrence after curative resection using different machine learning techniques.MethodsConsecutive patients who underwent curative surgery for rectal cancer between 2004 and 2018 at Gil Medical Center were included. Patients with stage IV disease, colon cancer, anal cancer, other recurrent cancer, emergency surgery, or hereditary malignancies were excluded from the study. The Synthetic Minority Oversampling Technique with Tomek link (SMOTETomek) technique was used to compensate for data imbalance between recurrent and no-recurrent groups. Four machine learning methods, logistic regression (LR), support vector machine (SVM), random forest (RF), and Extreme gradient boosting (XGBoost), were used to identify significant factors. To overfit and improve the model performance, feature importance was calculated using the permutation importance technique.ResultsA total of 3320 patients were included in the study. After exclusion, the total sample size of the study was 961 patients. The median follow-up period was 60.8 months (range:1.2-192.4). The recurrence rate during follow-up was 13.2% (n = 127). After applying the SMOTETomek method, the number of patients in both groups, recurrent and non-recurrent group were equalized to 667 patients. After analyzing for 16 variables, the top eight ranked variables {pathologic Tumor stage (pT), sex, concurrent chemoradiotherapy, pathologic Node stage (pN), age, postoperative chemotherapy, pathologic Tumor-Node-Metastasis stage (pTNM), and perineural invasion} were selected based on the order of permutational importance. The highest area under the curve (AUC) was for the SVM method (0.831). The sensitivity, specificity, and accuracy were found to be 0.692, 0.814, and 0.798, respectively. The lowest AUC was obtained for the XGBoost method (0.804), with a sensitivity, specificity, and accuracy of 0.308, 0.928, and 0.845, respectively. The variable with highest importance was pT as assessed through SVM, RF, and XGBoost (0.06, 0.12, and 0.13, respectively), whereas pTNM had the highest importance when assessed by LR (0.05).ConclusionsIn the current study, SVM showed the best AUC, and the most influential factor across all machine learning methods except LR was found to be pT. The rectal cancer patients who have a high pT stage during postoperative follow-up are need to be more close surveillance.

Project description:BackgroundLiver resection is the most effective treatment for intrahepatic cholangiocarcinoma. Recurrent disease is frequent; however, recurrence patterns are ill-defined and prognostic models are lacking.Study designA primary cohort of 189 patients who underwent resection for intrahepatic cholangiocarcinoma was used for recurrence patterns analysis within and after 24 months. Based on independent factors for disease-free survival identified in Cox regression analysis, preoperative and postoperative models were developed using a recursive partitioning method. Models were externally validated using a multicenter cohort of 522 resected patients (Association Française de Chirurgie intrahepatic cholangiocarcinoma study group).ResultsRecurrence within 24 months most often involved the liver (82.7%), and most recurrences after 24 months were strictly extrahepatic (61.1%). In multivariable analysis of the primary cohort, independent preoperative factors for disease-free survival were tumor size and multifocality (based on imaging); tumor size, multifocality, vascular invasion, and lymph node metastases (based on pathology) were independent postoperative factors. The preoperative model allowed patient classification into low-risk and high-risk groups for recurrence. In the validation cohort (n = 522), high-risk patients had a greater likelihood of recurrence (hazard ratio = 2.17; 95% CI, 1.74-2.72; p < 0.001). The postoperative model included tumor size, vascular invasion, and positive nodal disease on pathology and classified patients in low-, intermediate-, and high-risk groups in the primary cohort. As compared with low-risk patients in the validation cohort, intermediate- and high-risk patients were more likely to experience recurrence (hazard ratio = 1.9; 95% CI, 1.41-2.47; p < 0.001 and hazard ratio = 2.99; 95% CI, 2.08-4.31; p < 0.001, respectively).ConclusionsRecurrence patterns are time dependent. Both models as developed and validated in this study classified patients in distinct recurrence risk groups, which can guide treatment recommendations.

Project description:ObjectivesTo explore the role of preoperative gadoxetic acid-enhanced MRI in stratifying the risk of early recurrence in patients with LR-5 hepatocellular carcinoma (HCC) by LI-RADS v2018 after curative resection.MethodsBetween July 2015 and August 2018, this study evaluated consecutive treatment-naïve at-risk LR-5 HCC patients who underwent gadoxetic acid-enhanced MRI examination within 2 weeks before curative resection. The Cox regression analysis was performed to identify potential predictors of early recurrence. Disease-free survival (DFS) rates were analyzed and compared by using the Kaplan-Meier method and log-rank tests.ResultsFifty-three of 103 (51.5%) patients experienced early recurrence. Three MRI findings were significantly associated with early recurrence: corona enhancement (hazard ratio [HR]: 2.116; p = 0.013), peritumoral hypointensity on hepatobiliary phase (HBP) (HR: 2.262; p = 0.007), and satellite nodule (HR: 2.777; p = 0.005). An additional risk factor was AFP level > 400 ng/mL (HR: 1.975; p = 0.016). Based on the number of MRI predictors, LR-5 HCC patients were stratified into three subgroups: LR-5a (60/103; no predictor), LR-5b (26/103; one predictor), and LR-5c (17/103; two or three predictors), with low, medium, and high risk of early recurrence, respectively. The 2-year DFS rate of LR-5a, LR-5b, and LR-5c patients was 65.0%, 38.5%, and 5.9%, respectively, while the corresponding median DFS was undefined, 17.1 months, and 5.1 months, respectively (p < 0.001).ConclusionsIn at-risk LR-5 HCC patients, corona enhancement, peritumoral hypointensity on HBP, and satellite nodule could be used to preoperatively stratify the risk of early recurrence after hepatectomy.Key points• Corona enhancement, peritumoral hypointensity on HBP, satellite nodule, and serum AFP level > 400 ng/mL were significant predictors of early recurrence in patients with LR-5 HCC after hepatectomy. • Based on the number of predictive MRI findings, LR-5 HCC patients could be preoperatively stratified into three subgroups: LR-5a, LR-5b, and LR-5c, with significantly different risk of early recurrence and disease-free survival. • Preoperative risk stratification is essential for the identification of patients at increased risk of postoperative early recurrence, which may contribute to risk-based personalized management for LR-5 HCC patients.

Dataset Information

Preoperative AminoIndex Cancer Screening (AICS) abnormalities predict postoperative recurrence in patients undergoing curative resection for non-small cell lung cancer.

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Preoperative AminoIndex Cancer Screening (AICS) abnormalities predict postoperative recurrence in patients undergoing curative resection for non-small cell lung cancer.

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