Colorectal cancer is the third most common cancer in Korea and the third leading cause of death from cancer. Treatment outcomes for colon cancer are steadily improving due to national health screening programs with advances in diagnostic methods, surgical techniques, and therapeutic agents.. The Korea Colon Cancer Multidisciplinary (KCCM) Committee intends to provide professionals who treat colon cancer with the most up-to-date, evidence-based practice guidelines to improve outcomes and help them make decisions that reflect their patients’ values and preferences. These guidelines have been established by consensus reached by the KCCM Guideline Committee based on a systematic literature review and evidence synthesis and by considering the national health insurance system in real clinical practice settings. Each recommendation is presented with a recommendation strength and level of evidence based on the consensus of the committee.

Background/Aims: Epidermal growth factor receptor (EGFR) mutation is important in determining the treatment strategy for advanced lung cancer patients with malignant pleural effusion (MPE). Contrary to serum carcinoembryonic antigen (S-CEA) levels, the associations between pleural fluid CEA (PF-CEA) levels and EGFR mutation status as well as between PF-CEA levels and treatment efficacy have rarely been investigated in lung adenocarcinoma patients with MPE. Methods: This retrospective study enrolled lung adenocarcinoma patients with MPE and available PF-CEA levels and EGFR mutation results. The patients were categorized based on PF-CEA levels: < 10 ng/mL, 10–100 ng/mL, 100–500 ng/mL, and ≥ 500 ng/mL. The association between PF-CEA levels and EGFR mutation status as well as their therapeutic impact on overall survival was compared among the four groups. Results: This study included 188 patients. PF-CEA level was found to be an independent predictor of EGFR mutation but not S-CEA level. The EGFR mutation rates were higher as the PF-CEA levels increased, regardless of cytology results or sample types. Among EGFR-mutant lung adenocarcinoma patients receiving EGFR-tyrosine kinase inhibitor (TKI) treatment, those with high PF-CEA levels had significantly better survival outcomes than those with low PF-CEA levels. Conclusion High PF-CEA levels were associated with high EGFR mutation rate and may lead to a favorable clinical outcome of EGFR-TKI treatment in EGFR-mutant lung adenocarcinoma patients with MPE. These findings highlight the importance of actively investigating EGFR mutation detection in patients with suspected MPE and elevated PF-CEA levels despite negative cytology results.

Background/Aims: The prognostic significance of 18F-fluorodeoxyglucose (FDG)-positron emission tomography-computed tomography (PET/CT) in peripheral T-cell lymphomas (PTCLs) are controversial. We explored the prognostic impact of sequential 18F-FDG PET/CT during frontline chemotherapy of patients with PTCLs. Methods: In total, 143 patients with newly diagnosed PTCLs were included. Sequential 18F-FDG PET/CTs were performed at the time of diagnosis, during chemotherapy, and at the end of chemotherapy. The baseline total metabolic tumor volume (TMTV) was calculated using the the standard uptake value with a threshold method of 2.5. Results: A baseline TMTV of 457.0 cm3 was used to categorize patients into high and low TMTV groups. Patients with a requirehigh TMTV had shorter progression-free survival (PFS) and overall survival (OS) than those with a low TMTV (PFS, 9.8 vs. 26.5 mo, p = 0.043; OS, 18.9 vs. 71.2 mo, p = 0.004). The interim 18F-FDG PET/CT response score was recorded as 1, 2–3, and 4–5 according to the Deauville criteria. The PFS and OS showed significant differences according to the interim 18F-FDG PET/CT response score (PFS, 120.7 vs. 34.1 vs. 5.1 mo, p < 0.001; OS, not reached vs. 61.1 mo vs. 12.1 mo, p < 0.001). Conclusions The interim PET/CT response based on visual assessment predicts disease progression and survival outcome in PTCLs. A high baseline TMTV is associated with a poor response to anthracycline-based chemotherapy in PTCLs. However, TMTV was not an independent predictor for PFS in the multivariate analysis.

Purpose: We evaluated the characteristics of CCAAT/enhancer-binding protein α (CEBPA) mutations and the significance of a basic leucine zipper in-frame mutation (bZIPin-f) of CEBPA in patients with acute myeloid leukemia with a normal karyotype. Materials and Methods: Based on updated knowledge of CEBPA mutations, we conducted next-generation sequencing analyses in a previously established real-world cohort. Results: Among 78 of a total of 395 patients (19.7%), 50 had bZIPin-f CEBPA, and 28 had non-bZIPin-f CEBPA. In the multivariate analysis, patients with NPM1mut, those with bZIPin-f CEBPA, and those who underwent allogeneic hematopoietic cell transplantation (allo-HCT) had favorable overall survival (OS), but FLT3-ITDmut was a poor prognostic indicator. For relapse-free survival (RFS) and cumulative incidence of relapse, bZIPin-f CEBPA, and allo-HCT were associated with favorable outcomes; FLT3-ITDpos was associated with worse outcomes. In the CEBPA double-mutated group (CEBPAdm), bZIPin-f CEBPA was associated with superior outcomes in terms of OS (p=0.007) and RFS (p=0.007) compared with non-bZIPin-f CEBPA. Of 50 patients with bZIPin-f CEBPA, 36 patients had at least one mutation. When grouped by the presence of mutations in chromatic/DNA modifiers (C), cohesion complex (C), and splicing genes (S) (CCS mutations), CCS-mutated bZIPin-f CEBPA was associated with poor OS (p=0.044; hazard ratio [HR], 2.419) and a trend in inferior RFS (p=0.186; HR, 1.838). Conclusion Only bZIPin-f CEBPA was associated with favorable outcomes in patients with CEBPAdm. However, some mutations accompanying bZIPin-f CEBPA showed inferior OS; thus, further studies with larger numbers of patients are required for clear conclusions of the significance of bZIPin-f CEBPA.

Background/Aims: We evaluated the role of next-generation sequencing (NGS)-based disease monitoring for elderly patients diagnosed with acute myeloid leukemia (AML) who received decitabine therapy. Methods: A total of 123 patients aged > 65 years with AML who received decitabine were eligible. We analyzed the dynamics of variant allele frequency (VAF) in 49 available follow-up samples after the fourth cycle of decitabine. The 58.6% VAF clearance (Δ, [VAF at diagnosis − VAF at follow-up] × 100 / VAF at diagnosis) was the optimal cut-off for predicting overall survival (OS). Results: The overall response rate was 34.1% (eight patients with complete remission [CR], six of CR with incomplete hematologic recovery, 22 with partial responses, and six with morphologic leukemia-free status). Responders (n = 42) had significantly better OS compared with non-responders (n = 42) (median, 15.3 months vs. 6.5 months; p < 0.001). Of the 49 patients available for follow-up targeted NGS analysis, 44 had trackable gene mutations. The median OS of patients with ΔVAF ≥ 58.6% (n=24) was significantly better than that of patients with ΔVAF < 58.6% (n = 19) (20.5 months vs. 9.8 months, p = 0.010). Moreover, responders with ΔVAF ≥ 58.6% (n = 20) had a significantly longer median OS compared with responders with VAF < 58.6% (n = 11) (22.5 months vs. 9.8 months, p = 0.004). Conclusions This study suggested that combining ΔVAF ≥ 58.6%, a molecular response, with morphologic and hematologic responses can more accurately predict OS in elderly AML patients after decitabine therapy.

Background: and Purpose This study aimed to determine the ability of deep learning using convolutional neural networks (CNNs) to diagnose transient global amnesia (TGA) based on electroencephalography (EEG) data, and to differentiate between patients with recurrent TGA events and those with a single TGA event. Methods: We retrospectively enrolled newly diagnosed patients with TGA and healthy controls. All patients with TGA and the healthy controls underwent EEG. The EEG signals were converted into images using time-frequency analysis with short-time Fourier transforms. We employed two CNN models (AlexNet and VGG19) to classify the patients with TGA and the healthy controls, and for further classification of patients with recurrent TGA events and those with a single TGA event. Results: We enrolled 171 patients with TGA and 68 healthy controls. The accuracy and area under the curve (AUC) of the AlexNet and VGG19 models in classifying patients with TGA and healthy controls were 70.4% and 71.8%, and 0.718 and 0.743, respectively. In addition, the accuracy and AUC of the AlexNet and VGG19 models in classifying patients with recurrent TGA events and those with a single TGA event were 71.1% and 88.4%, and 0.773 and 0.873, respectively. Conclusions We have successfully demonstrated the feasibility of deep learning in diagnosing TGA based on EEG data, and used two different CNN models to distinguish between patients with recurrent TGA events and those with a single TGA event.

Ataxia is presented by various etiologies, including acquired, genetic and degenerative disorders. Although hereditary ataxia is suspected when typical symptom of ataxia with concurrent is identified, it is sometimes difficult to diagnose hereditary ataxia without genetic test. Clinically, next generation sequencing technology has been developed and widely used for diagnosis of hereditary disease. Hereby, we experienced cases of genetically confirmed OPA1 mutation, which are presented with various clinical manifestations including ataxic gait and decreased visual acuity.