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      A retrospective and prospective study to establish a preoperative difficulty predicting model for video-assisted thoracoscopic lobectomy and mediastinal lymph node dissection

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          Abstract

          Background

          In previous studies, the difficulty of surgery has rarely been used as a research object. Our study aimed to develop a predictive model to enable preoperative prediction of the technical difficulty of video-assisted thoracoscopic lobectomy and mediastinal lymph node dissection using retrospective data and to validate our findings prospectively.

          Methods

          Collected data according to the designed data table and took the operation time as the outcome variable. A nomogram to predict the difficulty of surgery was established through Lasso logistic regression. The prospective datasets were analyzed and the outcome was the operation time.

          Results

          This retrospective study enrolled 351 patients and 85 patients were included in the prospective datasets. The variables in the retrospective research were selected by Lasso logistic regression (only used for modeling and not screening), and four significantly related influencing factors were obtained: FEV1/FVC (forced expiratory volume in the first second/forced vital capacity) ( p < 0.001, OR, odds ratio = 0.89, 95% CI, confidence interval = 0.84–0.94), FEV1/pred FEV1 (forced expiratory volume in the first second/forced expiratory volume in the first second in predicted) ( p = 0.076, OR = 0.98, 95% CI = 0.95–1.00), history of lung disease ( p = 0.027, OR = 4.00, 95% CI = 1.27–15.64), and mediastinal lymph node enlargement or calcification ( p < 0.001, OR = 9.78, 95% CI = 5.10–19.69). We used ROC (receiver operating characteristic) curves to evaluate the model. The training set AUC (area under curve) value was 0.877, the test set’s AUC was 0.789, and the model had a good calibration curve. In a prospective study, the data obtained in the research cohort were brought into the model again for verification, and the AUC value was 0.772.

          Conclusion

          Our retrospective study identified four preoperative variables that are correlated with a longer surgical time and can be presumed to reflect more difficult surgical procedures. Our prospective study verified that the variables in the prediction model (including prior lung disease, FEV1/pred FEV1, FEV1/FVC, mediastinal lymph node enlargement or calcification) were related to the difficulty.

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          Most cited references17

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          Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

          This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.
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            Development and Validation of a Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer.

            To develop and validate a radiomics nomogram for preoperative prediction of lymph node (LN) metastasis in patients with colorectal cancer (CRC).
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              PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies

              Clinical prediction models combine multiple predictors to estimate risk for the presence of a particular condition (diagnostic models) or the occurrence of a certain event in the future (prognostic models). PROBAST (Prediction model Risk Of Bias ASsessment Tool), a tool for assessing the risk of bias (ROB) and applicability of diagnostic and prognostic prediction model studies, was developed by a steering group that considered existing ROB tools and reporting guidelines. The tool was informed by a Delphi procedure involving 38 experts and was refined through piloting. PROBAST is organized into the following 4 domains: participants, predictors, outcome, and analysis. These domains contain a total of 20 signaling questions to facilitate structured judgment of ROB, which was defined to occur when shortcomings in study design, conduct, or analysis lead to systematically distorted estimates of model predictive performance. PROBAST enables a focused and transparent approach to assessing the ROB and applicability of studies that develop, validate, or update prediction models for individualized predictions. Although PROBAST was designed for systematic reviews, it can be used more generally in critical appraisal of prediction model studies. Potential users include organizations supporting decision making, researchers and clinicians who are interested in evidence-based medicine or involved in guideline development, journal editors, and manuscript reviewers.
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                Author and article information

                Contributors
                daqiangsun@sina.com
                Journal
                BMC Surg
                BMC Surg
                BMC Surgery
                BioMed Central (London )
                1471-2482
                8 April 2022
                8 April 2022
                2022
                : 22
                : 135
                Affiliations
                [1 ]GRID grid.265021.2, ISNI 0000 0000 9792 1228, Tianjin Medical University, ; Heping, Tianjin, 300070 People’s Republic of China
                [2 ]GRID grid.417020.0, ISNI 0000 0004 6068 0239, Department of Thoracic Surgery, , Tianjin Chest Hospital, ; Jinnan, Tianjin, 300222 People’s Republic of China
                [3 ]GRID grid.417036.7, Department of Thoracic Surgery, , Tianjin Hospital of ITCWM Nankai Hospital, ; No. 6 Changjiang Road, Nankai, Tianjin, 300100 People’s Republic of China
                Article
                1566
                10.1186/s12893-022-01566-3
                8991718
                35392865
                269b1368-eb3f-4c00-993d-caa59e567786
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 25 July 2021
                : 18 March 2022
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                Surgery
                surgical difficulty,thoracoscopic lobectomy,mediastinal lymph node dissection,predicting model,nomogram

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