We are analyzing https://link.springer.com/article/10.1186/s12885-024-11862-1.

Title:
Effectiveness of CT radiomic features combined with clinical factors in predicting prognosis in patients with limited-stage small cell lung cancer | BMC Cancer
Description:
Background The prognosis of SCLC is poor and difficult to predict. The aim of this study was to explore whether a model based on radiomics and clinical features could predict the prognosis of patients with limited-stage small cell lung cancer (LS-SCLC). Methods Simulated positioning CT images and clinical features were retrospectively collected from 200 patients with histological diagnosis of LS-SCLC admitted between 2013 and 2021, which were randomly divided into the training (n = 140) and testing (n = 60) groups. Radiomics features were extracted from simulated positioning CT images, and the t-test and the least absolute shrinkage and selection operator (LASSO) were used to screen radiomics features. We then constructed radiomic score (RadScore) based on the filtered radiomics features. Clinical factors were analyzed using the Kaplan–Meier method. The Cox proportional hazards model was used for further analyses of possible prognostic features and clinical factors to build three models including a radiomic model, a clinical model, and a combined model including clinical factors and RadScore. When a model has prognostic predictive value (AUC > 0.7) in both train and test groups, a nomogram will be created. The performance of three models was evaluated using area under the receiver operating characteristic curve (AUC) and Kaplan–Meier analysis. Results A total of 1037 features were extracted from simulated positioning CT images which were contrast enhanced CT of the chest. The combined model showed the best prediction, with very poor AUC for the radiomic model and the clinical model. The combined model of OS included 4 clinical features and RadScore, with AUCs of 0.71 and 0.70 in the training and test groups. The combined model of PFS included 4 clinical features and RadScore, with AUCs of 0.72 and 0.71 in the training and test groups. T stages, ProGRP and smoke status were the independent variables for OS in the combined model, whereas T stages, ProGRP and prophylactic cranial irradiation (PCI) were the independent factors for PFS. There was a statistically significant difference between the low- and high-risk groups in the combined model of OS (training group, p < 0.0001; testing group, p = 0.0269) and PFS (training group, p < 0.0001; testing group, p < 0.0001). Conclusion Combined models involved RadScore and clinical factors can predict prognosis in LS-SCLC and show better performance than individual radiomics and clinical models.
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Keywords {🔍}

cancer, patients, lung, features, clinical, model, radiomics, pubmed, cell, article, models, study, combined, google, scholar, small, factors, radiomic, lssclc, prognosis, sclc, group, survival, prognostic, pfs, radiotherapy, training, auc, wang, analysis, liu, predict, images, based, positioning, testing, prediction, central, simulated, data, groups, included, oncol, zhang, predicting, tumor, fig, limitedstage, zhao, extracted,

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51\times wavelet-lhh\_glcm\_correlation$$ $$os\_c=0 01\times wavelet-llh\_glcm\_clustershade-1 68\times wavelet-llh\_glcm\_mcc+0 01\times wavelet-llh\_firstorder\_90percentile-0 44\times wavelet-llh\_firstorder\_skewness+4 grey-level run-length matrix 03\times wavelet-llh\_glszm\_sae-1 06\times wavelet-lhl\_firstorder\_skewness+3 small-cell lung cancer small-cell lung cancer preoperative 18f-fdg pet/ct coefficient profile plot 00\times pro-grp$$ $$os\_rc=0 00\times pro-grp$$ $$pfs\_rc=0 grey-level dependence matrix 03\times logsigma40mm3d\_glcm\_contrast +2 central lung cancer pro-gastrin-releasing peptide intensity-modulated radiotherapy individualised therapeutic decision-making 02\times logsigma50mm3d\_glszm\_glnu+1 98\times logsigma50mm3d\_glszm\_sznun-0 27\times logsigma50mm3d\_glszm\_sznun+0 stage i-iii disease article download pdf neuron-specific enolase log-sigma-4–0-mm-3d_glcm_jointaverage log-sigma-4–0-mm-3d_glcm_sumaverage 01\times original\_shape\_maximum2ddiameterslice+0 thyroid transcription factor-1 lasso coefficient profiles kaplan–meier curve confirmed simulated positioning ct ct-based radiomics signature kaplan–meier survival analysis cancer-related deaths [45] positioning ct images nonenhanced computed tomography stage iii unresectable ct-based radiomics nomogram receiver operating characteristic privacy choices/manage cookies full access positron emission tomography progression-free survival prediction clinical research center hhh-filtered images solid lung adenocarcinoma cancer biol med writing-review & editing

Questions {❓}

Does the response to induction chemotherapy impact the timing of thoracic radiotherapy for limited-stage small-cell lung cancer?
Factors affecting the risk of brain metastasis in small cell lung cancer with surgery: is prophylactic cranial irradiation necessary for stage I-III disease?

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            Texture analysis
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            Cancer Research
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            Health Promotion and Disease Prevention
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      description:The prognosis of SCLC is poor and difficult to predict. The aim of this study was to explore whether a model based on radiomics and clinical features could predict the prognosis of patients with limited-stage small cell lung cancer (LS-SCLC). Simulated positioning CT images and clinical features were retrospectively collected from 200 patients with histological diagnosis of LS-SCLC admitted between 2013 and 2021, which were randomly divided into the training (n = 140) and testing (n = 60) groups. Radiomics features were extracted from simulated positioning CT images, and the t-test and the least absolute shrinkage and selection operator (LASSO) were used to screen radiomics features. We then constructed radiomic score (RadScore) based on the filtered radiomics features. Clinical factors were analyzed using the Kaplan–Meier method. The Cox proportional hazards model was used for further analyses of possible prognostic features and clinical factors to build three models including a radiomic model, a clinical model, and a combined model including clinical factors and RadScore. When a model has prognostic predictive value (AUC > 0.7) in both train and test groups, a nomogram will be created. The performance of three models was evaluated using area under the receiver operating characteristic curve (AUC) and Kaplan–Meier analysis. A total of 1037 features were extracted from simulated positioning CT images which were contrast enhanced CT of the chest. The combined model showed the best prediction, with very poor AUC for the radiomic model and the clinical model. The combined model of OS included 4 clinical features and RadScore, with AUCs of 0.71 and 0.70 in the training and test groups. The combined model of PFS included 4 clinical features and RadScore, with AUCs of 0.72 and 0.71 in the training and test groups. T stages, ProGRP and smoke status were the independent variables for OS in the combined model, whereas T stages, ProGRP and prophylactic cranial irradiation (PCI) were the independent factors for PFS. There was a statistically significant difference between the low- and high-risk groups in the combined model of OS (training group, p < 0.0001; testing group, p = 0.0269) and PFS (training group, p < 0.0001; testing group, p < 0.0001). Combined models involved RadScore and clinical factors can predict prognosis in LS-SCLC and show better performance than individual radiomics and clinical models.
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         Small cell lung cancer
         Radiomics
         Prognosis
         Texture analysis
         Simulated positioning CT
         Cancer Research
         Oncology
         Surgical Oncology
         Health Promotion and Disease Prevention
         Biomedicine
         general
         Medicine/Public Health
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            name:Lehigh University
            address:
               name:College of Arts and Sciences, Lehigh University, Bethlehem, USA
               type:PostalAddress
            type:Organization
      name:Lujun Zhao
      affiliation:
            name:Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy
            address:
               name:Department of Radiation Oncology, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
               type:PostalAddress
            type:Organization
      name:Jiawei Song
      affiliation:
            name:the People’s Hospital of Ganyu District
            address:
               name:Department of Oncology, the People’s Hospital of Ganyu District, Lianyungang, China
               type:PostalAddress
            type:Organization
      name:Wei Wang
      affiliation:
            name:Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy
            address:
               name:Department of Radiation Oncology, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
               type:PostalAddress
            type:Organization
      name:Yining Yang
      affiliation:
            name:Tianjin First Central Hospital
            address:
               name:The Department of Radiotherapy, Tianjin First Central Hospital, Tianjin, China
               type:PostalAddress
            type:Organization
      name:Ningbo Liu
      affiliation:
            name:Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy
            address:
               name:Department of Radiation Oncology, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
               type:PostalAddress
            type:Organization
            name:Hetian District People’s Hospital
            address:
               name:Hetian District People’s Hospital, Hetian, China
               type:PostalAddress
            type:Organization
      email:[email protected]
PostalAddress:
      name:Department of Radiation Oncology, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
      name:Langfang Health Vocational College, Langfang, China
      name:Department of Radiation Oncology, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
      name:Department of Radiation Oncology, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
      name:Department of Radiation Oncology, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
      name:College of Arts and Sciences, Lehigh University, Bethlehem, USA
      name:Department of Radiation Oncology, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
      name:Department of Oncology, the People’s Hospital of Ganyu District, Lianyungang, China
      name:Department of Radiation Oncology, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
      name:The Department of Radiotherapy, Tianjin First Central Hospital, Tianjin, China
      name:Department of Radiation Oncology, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
      name:Hetian District People’s Hospital, Hetian, China

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