Lung cancer staging: clinical and radiologic perspectives.
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ABSTRACT:
SUBMITTER: Chheang S
PROVIDER: S-EPMC3709937 | biostudies-other | 2013 Jun
REPOSITORIES: biostudies-other
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Project description:The tumour-node metastasis (TNM) classification system is anatomically based. We investigated whether the addition of simple physiological variables, age and body mass index (BMI), would affect survival curves, i.e. a composite anatomical and physiological staging system. We retrospectively analysed a prospectively validated thoracic surgery database (n = 1981). Cox multivariate analysis was performed to determine possible significant factors. Kaplan-Meier survival curves were constructed with combined anatomical and physiological factors. Cox multivariate analysis revealed age (P < 0.001) and BMI (P = 0.01) as significant factors affecting survival. Receiver operating curve analysis determined cut-off levels for age of 67 and BMI of 27.6. A composite anatomical and physiological survival curve based on TNM for BMI > 27.6 and age < 67 was produced. Age and BMI criteria resulted in significantly different survival curves, for stage I (P < 0.0001) and stage II (P = 0.0032), but not for stage III (P = 0.06). Neural network analysis confirmed the importance of BMI and age above cancer stage with regard to long-term survival. Combining age < 67, BMI > 27.6 and TNM anatomical classification results in very different estimated survival curves from the usual TNM system. Patients from stages I, II and III may have survival equivalent to a stage higher or lower depending on their age and BMI.
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Project description:ObjectivesThe ground-glass component of part-solid tumour (PST) was eliminated as a clinical T (cT) descriptor in the eighth edition of the tumour, node and metastasis (TNM) staging system. We aimed to validate the new cT descriptor and investigate the prognostic impact of PST in the new staging system.MethodsNon-small-cell lung cancer (NSCLC) patients (n = 1061) who underwent lung resection and were available for the assessment of thin-section computed tomography images were retrospectively reviewed. Tumours with a solid component (SC) size-to-whole tumour size (STR) ratio of 0, those with 0 < STR < 1 and those with an STR of 1 were defined as pure ground-glass tumours, PSTs and solid tumours (STs), respectively.ResultsTumours with an SC diameter of >30 mm were less frequently observed among PSTs than among STs (4.83% vs 32.6%, P < 0.001). The postoperative 5-year survival of NSCLC patients with ground-glass tumour, PST and ST was 97.6%, 89.0% and 76.3%, respectively. In the survival analysis of patients with an SC diameter ≤30 mm, significant differences were observed among PST and ST (5-year survival, 90.7% vs 74.6%, P < 0.001). The multivariable analysis showed that age <70 years old, female sex, procedures with a lobectomy or more, SC size, pN0 disease and PST were independent predictors of a better survival among all PST and ST patients.ConclusionsAmong patients with cT1 tumours, those with PST showed a significantly better survival than did those with ST. Small-sized PST tumours may not be suitable for the new cT descriptor.
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Project description:BackgroundTo determine which components should be measured and which window settings are appropriate for computerized tomography (CT) size measurements of lung adenocarcinoma (ADC) and to explore interobserver agreement and accuracy according to the eighth edition of TNM staging.MethodsA total of 165 patients with surgically resected lung ADC earlier than stage 3A were included in this study. One radiologist and two pulmonologists independently measured the total and solid sizes of components of tumors on different window settings and assessed solidity. CT measurements were compared with pathologic size measurements.ResultsIn categorizing solidity, 25% of the cases showed discordant results among observers. Measuring the total size of a lung adenocarcinoma predicted pathologic invasive components to a degree similar to measuring the solid component. Lung windows were more accurate (intraclass correlation [ICC] = 0.65-0.81) than mediastinal windows (ICC = 0.20-0.72) at predicting pathologic invasive components, especially in a part-solid nodule. Interobserver agreements for measurement of solid components were good with little significant difference (lung windows, ICC = 0.89; mediastinal windows, ICC = 0.91). A high level of interobserver agreement was seen between the radiologist and pulmonologists and between residents (from the division of pulmonology and critical care) versus a fellow (from the division of pulmonology and critical care) on different windows.ConclusionsA considerable percentage (25%) of discrepancies was encountered in categorizing the solidity of lesions, which may decrease the accuracy of measurements. Lung window settings may be superior to mediastinal windows for measuring lung ADCs, with comparable interobserver agreement and moderate accuracy for predicting pathologic invasive components.Key pointsSIGNIFICANT FINDINGS OF THE STUDY: Lung window settings are better for evaluating part-solid lung adenocarcinoma (ADC), with comparable interobserver agreement and moderate accuracy for predicting pathologic invasive components. The considerable percentage (25%) of discrepancies in categorizing solidity of the lesions may also have decreased the accuracy of measurements.What this study addsFor accurate measurement and categorization of lung ADC, robust quantitative analysis is needed rather than a simple visual assessment.
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Project description:In this study, we aimed to assess the prevalence of interstitial lung abnormalities (ILAs) and investigate the rates and risk factors associated with radiologic ILA progression among patients with lung cancer following surgical resection. Patients who underwent surgical resection for lung cancer at our institution from January 2015 to December 2020 were retrospectively evaluated and grouped according to their ILA status as having no ILAs, equivocal ILAs, or ILAs. Progression was determined by simultaneously reviewing the baseline and corresponding follow-up computed tomography (CT) scans. Among 346 patients (median age: 67 (interquartile range: 60-74) years, 204 (59.0%) men), 22 (6.4%) had equivocal ILAs, and 33 (9.5%) had ILAs detected upon baseline CT. Notably, six patients (6/291; 2.1%) without ILAs upon baseline CT later developed ILAs, and 50% (11/22) of those with equivocal ILAs exhibited progression. Furthermore, 75.8% (25/33) of patients with ILAs upon baseline CT exhibited ILA progression (76.9% and 71.4% with fibrotic and non-fibrotic ILAs, respectively). Multivariate analysis revealed that ILA status was a significant risk factor for ILA progression. ILAs and equivocal ILAs were associated with radiologic ILA progression after surgical resection in patients with lung cancer. Hence, early ILA detection can significantly affect clinical outcomes.
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Project description:BackgroundLung cancer diagnostic guidelines advocate for invasive mediastinal nodal staging (IMNS), but the survival benefits of this approach in patients with non-small cell lung cancer (NSCLC) without radiologic evidence of lymph node metastasis (rN0) remain uncertain. We aimed to investigate the impact of IMNS in patients with rN0 NSCLC by comparing the long-term survival between patients who underwent IMNS and those who did not (non-IMNS).MethodsIn this retrospective cohort study, we included patients with NSCLC but without radiologic evidence of lymph node metastasis from the Registry for Thoracic Cancer Surgery and the clinical data warehouse at the Samsung Medical Centre, Republic of Korea between January 2, 2008 and December 31, 2016. We compared the 5-year overall survival (OS) rate as the primary outcome after propensity score matching between the IMNS and non-IMNS groups. The age, sex, performance statue, tumor size, centrality, solidity, lung function, FDG uptake in PET-CT, and histological examination of the tumor before surgery were matched.FindingsA total of 4545 patients (887 in the IMNS group and 3658 in the non-IMNS group) who received curative treatment for NSCLC were included in this study. By the mediastinal node dissection, the overall incidence of unforeseen mediastinal node metastasis (N2) was 7.2% (317/4378 patients). Despite the IMNS, 67% of pathological N2 was missed (61/91 patients with unforeseen N2). Based on propensity score matching, 866 patients each for the IMNS and non-IMNS groups were assigned. There was no significant difference in 5-year OS and recurrence-free survival (RFS) between two groups: 5-year OS was 73.9% (95% confidence interval, CI: 71%-77%) for IMNS and 71.7% (95% CI: 68.6%-74.9%; p = 0.23), for non-IMNS (hazard ratio, HR 0.90, 95% CI: 0.77-1.07), while 5-year RFS was 64.7% (95% CI: 61.5%-68.2%) and 67.5% (95% CI: 64.3%-70.9%; p = 0.35 (HR 1.08, 95% CI: 0.92-1.27), respectively. Moreover, the timing and locations of recurrence were similar in both groups.InterpretationIMNS might not be required before surgery for patients with NSCLC without LN suspicious of metastasis. Further randomised trials are required to validate the findings of the present study.FundingNone.
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Project description:To address uncertainty of whether clinical stage groupings (cTNM) for esophageal cancer share prognostic implications with pathologic groupings after esophagectomy alone (pTNM), we report data-simple descriptions of patient characteristics, cancer categories, and non-risk-adjusted survival-for clinically staged patients from the Worldwide Esophageal Cancer Collaboration (WECC). Thirty-three institutions from six continents submitted data using variables with standard definitions: demographics, comorbidities, clinical cancer categories, and all-cause mortality from first management decision. Of 22,123 clinically staged patients, 8,156 had squamous cell carcinoma, 13,814 adenocarcinoma, 116 adenosquamous carcinoma, and 37 undifferentiated carcinoma. Patients were older (62 years) men (80%) with normal body mass index (18.5-25 mg/kg2 , 47%), little weight loss (2.4?±?7.8 kg), 0-1 ECOG performance status (67%), and history of smoking (67%). Cancers were cT1 (12%), cT2 (22%), cT3 (56%), cN0 (44%), cM0 (95%), and cG2-G3 (89%); most involved the distal esophagus (73%). Non-risk-adjusted survival for squamous cell carcinoma was not distinctive for early cT or cN; for adenocarcinoma, it was distinctive for early versus advanced cT and for cN0 versus cN+. Patients with early cancers had worse survival and those with advanced cancers better survival than expected from equivalent pathologic categories based on prior WECC pathologic data. Thus, clinical and pathologic categories do not share prognostic implications. This makes clinically based treatment decisions difficult and pre-treatment prognostication inaccurate. These data will be the basis for the 8th edition cancer staging manuals following risk adjustment for patient characteristics, cancer categories, and treatment characteristics and should direct 9th edition data collection.
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Project description:BackgroundComputed tomography (CT) reports record a large volume of valuable information about patients' conditions and the interpretations of radiology images from radiologists, which can be used for clinical decision-making and further academic study. However, the free-text nature of clinical reports is a critical barrier to use this data more effectively. In this study, we investigate a novel deep learning method to extract entities from Chinese CT reports for lung cancer screening and TNM staging.MethodsThe proposed approach presents a new named entity recognition algorithm, namely the BERT-based-BiLSTM-Transformer network (BERT-BTN) with pre-training, to extract clinical entities for lung cancer screening and staging. Specifically, instead of traditional word embedding methods, BERT is applied to learn the deep semantic representations of characters. Following the long short-term memory layer, a Transformer layer is added to capture the global dependencies between characters. Besides, pre-training technique is employed to alleviate the problem of insufficient labeled data.ResultsWe verify the effectiveness of the proposed approach on a clinical dataset containing 359 CT reports collected from the Department of Thoracic Surgery II of Peking University Cancer Hospital. The experimental results show that the proposed approach achieves an 85.96% macro-F1 score under exact match scheme, which improves the performance by 1.38%, 1.84%, 3.81%,4.29%,5.12%,5.29% and 8.84% compared to BERT-BTN, BERT-LSTM, BERT-fine-tune, BERT-Transformer, FastText-BTN, FastText-BiLSTM and FastText-Transformer, respectively.ConclusionsIn this study, we developed a novel deep learning method, i.e., BERT-BTN with pre-training, to extract the clinical entities from Chinese CT reports. The experimental results indicate that the proposed approach can efficiently recognize various clinical entities about lung cancer screening and staging, which shows the potential for further clinical decision-making and academic research.
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Project description:The staging of the central-chest lymph nodes is a major step in the management of lung-cancer patients. For this purpose, the physician uses a device that integrates videobronchoscopy and an endobronchial ultrasound (EBUS) probe. To biopsy a lymph node, the physician first uses videobronchoscopy to navigate through the airways and then invokes EBUS to localize and biopsy the node. Unfortunately, this process proves difficult for many physicians, with the choice of biopsy site found by trial and error. We present a complete image-guided EBUS bronchoscopy system tailored to lymph-node staging. The system accepts a patient's 3D chest CT scan, an optional PET scan, and the EBUS bronchoscope's video sources as inputs. System workflow follows two phases: (1) procedure planning and (2) image-guided EBUS bronchoscopy. Procedure planning derives airway guidance routes that facilitate optimal EBUS scanning and nodal biopsy. During the live procedure, the system's graphical display suggests a series of device maneuvers to perform and provides multimodal visual cues for locating suitable biopsy sites. To this end, the system exploits data fusion to drive a multimodal virtual bronchoscope and other visualization tools that lead the physician through the process of device navigation and localization. A retrospective lung-cancer patient study and follow-on prospective patient study, performed within the standard clinical workflow, demonstrate the system's feasibility and functionality. For the prospective study, 60/60 selected lymph nodes (100%) were correctly localized using the system, and 30/33 biopsied nodes (91%) gave adequate tissue samples. Also, the mean procedure time including all user interactions was 6 min 43 s All of these measures improve upon benchmarks reported for other state-of-the-art systems and current practice. Overall, the system enabled safe, efficient EBUS-based localization and biopsy of lymph nodes.
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Project description:ObjectiveTo harmonize eligibility criteria and radiographic disease assessments in clinical trials of adjuvant therapy for muscle-invasive bladder cancer (MIBC).MethodsNational experts in bladder cancer clinical trial research, including medical and urologic oncologists, radiologists, biostatisticians, and patient advocates, convened at a public workshop on November 28, 2017, to discuss eligibility, radiographic entry criteria, and assessment of disease recurrence in adjuvant clinical trials in patients with MIBC.ResultsThe key workshop conclusions for adjuvant MIBC clinical trials included the following points: (1) patients with urothelial carcinoma with divergent histologic differentiation should be allowed to enroll; (2) neoadjuvant chemotherapy is defined as at least 3 cycles of neoadjuvant cisplatin-based combination chemotherapy; (3) patients with muscle-invasive, upper-tract urothelial carcinoma should be included in adjuvant trials of MIBC; (4) patients with severe renal insufficiency can enroll into trials using agents that are not renally excreted; (5) patients with microscopic surgical margins can be included; (6) patients should undergo a standard bilateral lymph node dissection prior to enrollment; (7) computed tomographic (CT) imaging should be performed within 4 weeks prior to enrollment. For patients with renal insufficiency who cannot undergo CT imaging with contrast, noncontrast chest CT and magnetic resonance imaging of the abdomen and pelvis with gadolinium should be done; (8) biopsy of indeterminate lesions to evaluate for malignant disease should be done when feasible; (9) a uniform approach to evaluate indeterminate radiographic lesions when biopsy is not feasible should be included in any trial design; (10) a uniform approach to determining the date of recurrence is important in interpreting adjuvant trial results; and (11) new high-grade, upper-tract primary tumors and new MIBC tumors should be considered recurrence events.Conclusions and relevanceA uniform approach to eligibility criteria, definitions of no evidence of disease, and definitions of disease recurrence may lead to more consistent interpretations of adjuvant trial results in MIBC.
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Project description:BackgroundThe clinical staging of non-small cell lung cancer (NSCLC) is well known to be related to their prognosis. However, there is usually a discrepancy between clinical staging and pathological staging. There are few analyses of clinical staging accuracy in patients with NSCLC. We compared the concordance rate between clinical and pathological staging of NSCLC and evaluated factors affecting the accuracy in real-world data.MethodsAltogether, 811 patients with primary NSCLC who had undergone curative lung resection surgery in Severance Hospital from January 2019 to December 2020 were retrospectively reviewed. We used the eighth edition of the American Joint Committee on Cancer TNM staging.ResultsAmong 811 patients, endobronchial ultrasound (EBUS) and positron emission tomography (PET-CT) were performed in 31.6% and 96.7%, respectively. The concordance rates between clinical and pathological TNM staging, T factor, and N factor, were 68.7%, 77.7%, and 85.8%, respectively. With multivariable logistic regression analysis, current smokers (OR 0.49; 95% CI: 0.32-0.76, p = 0.001) and a higher clinical stage (p < 0.001) contributed to the clinical staging inaccuracy. Additionally, the presence of a bronchoscopy specialist was significantly associated with clinical staging accuracy (OR 1.53; 95% CI: 1.10-2.13, p = 0.011).ConclusionClinical staging accuracy in NSCLC improved compared to before the widespread use of PET-CT and EBUS in clinical staging work-up. Smoking history and absence of expert bronchoscopy specialists showed a meaningful correlation with the inaccuracy of clinical staging. Thus, training more bronchoscopy experts would improve the staging accuracy of NSCLC, which could positively affect the prognosis of NSCLC.
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