A clinical model to predict the risk of synchronous bone metastasis in newly diagnosed colorectal cancer: a population-based study

Guan, Xu; Ma, Chenxi; Quan, Jichuan; Li, Shuai; Zhao, Zhixun; Chen, Haipeng; Yang, Ming; Liu, Zheng; Jiang, Zheng; Wang, Xishan

doi:10.1186/s12885-019-5912-x

Cited by 19 publications

(22 citation statements)

References 18 publications

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“…Our nomogram included only seven variables, and all of them were routinely examined items during the followup. Consistent with previous studies (9,13,14), G3 tumor differentiation and lymph node involvement of the primary tumor were included in our risk model, which may demonstrate that a high degree of malignancy of the primary tumor is associated with the risk of BM. A positive CEA result may indicate the presence of residual tumor after radical surgery or a higher tumor burden, leading to a greater likelihood of bone infiltration and metastasis.…”

Section: Discussionsupporting

confidence: 83%

“…Until now, the diagnosis of BM has been entirely dependent on imaging techniques, partially inclusive of bone scintigraphy (BS), magnetic resonance imaging (MRI), and positron emission tomography/ computed tomography (PET/CT). However, due to the low incidence of BM among CRC patients, high-cost imaging examination for BM is not recommended for routine follow-up until obvious symptoms of skeletal-related events (SREs) occur (9). SREs include (but are not limited to) disturbance of homeostasis, pathological fracture, and spinal cord compression, which could lead to a significantly poor quality of life and increased costs of nursing care (10).…”

Section: Introductionmentioning

confidence: 99%

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Development and validation of risk and prognostic nomograms for bone metastases in Chinese advanced colorectal cancer patients

Wang¹,

Liu²,

Wu³

et al. 2021

Ann Transl Med

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Background: Bone metastases (BM) from colorectal cancer (CRC) are often accompanied by extraosseous metastases, resulting in a dismal prognosis. The present study aimed to determine the risk factors for BM in metastatic CRC (mCRC) and the prognostic factors for CRC patients with BM. Methods: The study was based on a training cohort of 214 mCRC patients (of which, 101 patients had BM) from our center, and a validation cohort of 511 mCRC patients (of which, 173 patients had BM) from another institute. Risk and prognostic nomograms for BM were developed using univariate and multivariate analyses. The goodness of fit, discrimination, and calibration performance of the nomograms were assessed by R², concordance statistics (C-statistics), and the calibration curve. The results were internally validated using bootstrap resampling in the training cohort, and externally validated in the validation cohort. Results: The novel BM risk nomogram comprised seven variables [degree of tumor differentiation, N-stage, serum alkaline phosphatase (ALP), lactate dehydrogenase (LDH), carcinoembryonic antigen (CEA), liver metastasis, and lung metastasis]. It showed good performance, with an R² of 0.447 and a C-statistic of 0.846 [95% confidence interval (CI), 0.793 to 0.898] in the training cohort, and an R² of 0.325 and a C-statistic of 0.792 (95% CI, 0.750 to 0.834) in the validation cohort. The optimal cutoff value to identify individuals at low or high risk was 56% probability, with a sensitivity of 71.3% and a specificity of 89.4%. The prognostic nomogram included five factors (tumor differentiation, number of extra-BM organs, number of BM lesions, ALP, and LDH), and had an R² of 0.284 and a C-statistic of 0.723 (95% CI, 0.657 to 0.789) in the training set. This nomogram was externally validated in the validation cohort, with an R² of 0.182 and a C-statistic of 0.682 (95% CI, 0.638 to 0.726). Conclusions:The developed and validated risk and prognostic nomograms showed good performance for predicting the occurrence of BM in mCRC as well as the prognosis of CRC patients with BM. The risk nomogram can be used as a cost-effective preliminary screening tool prior to bone scanning.

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Section: Discussionsupporting

confidence: 83%

Section: Introductionmentioning

confidence: 99%

Development and validation of risk and prognostic nomograms for bone metastases in Chinese advanced colorectal cancer patients

Wang¹,

Liu²,

Wu³

et al. 2021

Ann Transl Med

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“…Nomograms are useful tools that can assist in quantitatively predicting the prognosis for each patient ( 8 ). Previous retrospective studies based on the SEER database has assessed the risk factors of poor survival for CRC patients with lung and bone metastasis and established a nomogram to estimate the cancer survival, respectively ( 9 , 10 ). Synchronous colon cancer with liver metastasis (SCLM), a subtype of colon cancer with liver metastasis, is characterized with poor prognosis.…”

Section: Introductionmentioning

confidence: 99%

Predictive Risk Factors and Online Nomograms for Synchronous Colon Cancer With Liver Metastasis

Zhu

Chen

et al. 2020

Front. Oncol.

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Objectives To develop and validate predictive nomograms of cancer specific survival (CSS) and overall survival (OS) for synchronous colon cancer with liver metastasis (SCLM) patients. Methods Patients with pathologically diagnosed colon cancer with liver metastasis were retrieved from the SEER database between 2010 and 2015. Only SCLM patients were included. Univariate and multivariate cox regression analyses were conducted to identify the potential predictors of patients’ survival outcomes. The selected variables were integrated to create predictive nomograms via R tools. Furthermore, the concordance index Harrell’s C statistic (C-index) was calculated to describe the discrimination of nomograms. Calibration (1000 bootstrap resamples) curves were plotted to compare the predictions of nomograms with the observed outcomes. Decision curve analysis (DCA) and clinical impact curves were performed to evaluate the clinical effects of nomograms. Results A total of 22,378 SCLM patients were included. The median time of OS and CSS was 13 and 17 months, respectively. The 1-, 2-, and 3-year rate of OS was 50.6, 28.1, and 14.8%, respectively. While the 1-, 2-, and 3-year rate of CSS was 58.7, 36.8, and 22.5%, respectively. SCLM patients with increased age, left primary tumor location, AJCC IVb stage, and no chemotherapy were associated with an obviously reduced OS and CSS. Variables including age, histological grade, T/N/M stage, tumor size, bone/lung metastasis, CEA, surgery of primary site, and chemotherapy were closely related to the prognoses of SCLM patients. Nomograms of OS and CSS were built and displayed online for convenient utilization. The C-index of OS and CSS monograms were 0.74 and 0.73, respectively, indicating relatively good discrimination of the nomograms. The calibration curves suggested a good agreement between the actual observation and the nomogram prediction. DCAs and clinical impact curves reflected favorable potential clinical effects of predictive nomograms. Conclusion Chemotherapy, surgery of primary site, and age were important independent risk factors for the CSS and OS of SCLM patients. We built and validated two reliable nomograms of OS and CSS to predict the prognoses of SCLM patients, which can be accessed online at ( https://predictive-tool.shinyapps.io/CSS-DynNomapp/ ; https://predictive-tool.shinyapps.io/OS-DynNomapp/ ).

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“…Comparative cross-assessment between risk factors evaluated in the umbrella review and risk predictors applied in existing prediction models Prediction models for CRC metastasis Twelve prognostic models have been developed for prediction of CRC metastasis [22][23][24][25][26][27][28][29][30][31][32][33] (Table 3). The median number of included predictors was four (range 3-9), and 27 unique predictors were included in at least one model.…”

Section: Sensitivity Analysis Of Redefying the Disease Outcome Groupsmentioning

confidence: 99%

Risk factors and risk prediction models for colorectal cancer metastasis and recurrence: an umbrella review of systematic reviews and meta-analyses of observational studies

Wang

et al. 2020

BMC Med

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Background: There is a clear need for systematic appraisal of models/factors predicting colorectal cancer (CRC) metastasis and recurrence because clinical decisions about adjuvant treatment are taken on the basis of such variables. Methods: We conducted an umbrella review of all systematic reviews of observational studies (with/without metaanalysis) that evaluated risk factors of CRC metastasis and recurrence. We also generated an updated synthesis of risk prediction models for CRC metastasis and recurrence. We cross-assessed individual risk factors and risk prediction models. Results: Thirty-four risk factors for CRC metastasis and 17 for recurrence were investigated. Twelve of 34 and 4/17 risk factors with p < 0.05 were estimated to change the odds of the outcome at least 3-fold. Only one risk factor (vascular invasion for lymph node metastasis [LNM] in pT1 CRC) presented convincing evidence. We identified 24 CRC risk prediction models. Across 12 metastasis models, six out of 27 unique predictors were assessed in the umbrella review and four of them changed the odds of the outcome at least 3-fold. Across 12 recurrence models, five out of 25 unique predictors were assessed in the umbrella review and only one changed the odds of the outcome at least 3-fold. Conclusions: This study provides an in-depth evaluation and cross-assessment of 51 risk factors and 24 prediction models. Our findings suggest that a minority of influential risk factors are employed in prediction models, which indicates the need for a more rigorous and systematic model construction process following evidence-based methods.

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A clinical model to predict the risk of synchronous bone metastasis in newly diagnosed colorectal cancer: a population-based study

Cited by 19 publications

References 18 publications

Development and validation of risk and prognostic nomograms for bone metastases in Chinese advanced colorectal cancer patients

Development and validation of risk and prognostic nomograms for bone metastases in Chinese advanced colorectal cancer patients

Predictive Risk Factors and Online Nomograms for Synchronous Colon Cancer With Liver Metastasis

Risk factors and risk prediction models for colorectal cancer metastasis and recurrence: an umbrella review of systematic reviews and meta-analyses of observational studies

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