Risk factors and predictors for tumor site origin in metastatic adenocarcinoma of unknown primary site

Li, Xinrong; Shao, Yan; Sheng, Liqiang; Zhu, Junquan; Wang, Zeming; Guo, Kaibo; Sun, Leitao

doi:10.1002/cam4.3684

Cited by 6 publications

(6 citation statements)

References 22 publications

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“…The model features in the study contained five variables: age, lung metastasis, liver metastasis, radiation, and chemotherapy. These variables were also proved to be associated with survival outcome among CUP patients in other studies (20,23). Furthermore, a recent study showed that gender, Eastern Cooperative Oncology Group performance status, histology, number of metastatic sites, and neutrophil-lymphocyte ratio were independent prognostic factors for survival among CUP patients (20).…”

Section: Model Featuresmentioning

confidence: 82%

Development of a web-based calculator to predict three-month mortality among patients with bone metastases from cancer of unknown primary: An internally and externally validated study using machine-learning techniques

et al. 2022

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BackgroundIndividualized therapeutic strategies can be carried out under the guidance of expected lifespan, hence survival prediction is important. Nonetheless, reliable survival estimation in individuals with bone metastases from cancer of unknown primary (CUP) is still scarce. The objective of the study is to construct a model as well as a web-based calculator to predict three-month mortality among bone metastasis patients with CUP using machine learning-based techniques.MethodsThis study enrolled 1010 patients from a large oncological database, the Surveillance, Epidemiology, and End Results (SEER) database, in the United States between 2010 and 2018. The entire patient population was classified into two cohorts at random: a training cohort (n=600, 60%) and a validation cohort (410, 40%). Patients from the validation cohort were used to validate models after they had been developed using the four machine learning approaches of random forest, gradient boosting machine, decision tree, and eXGBoosting machine on patients from the training cohort. In addition, 101 patients from two large teaching hospital were served as an external validation cohort. To evaluate each model’s ability to predict the outcome, prediction measures such as area under the receiver operating characteristic (AUROC) curves, accuracy, and Youden index were generated. The study’s risk stratification was done using the best cut-off value. The Streamlit software was used to establish a web-based calculator.ResultsThe three-month mortality was 72.38% (731/1010) in the entire cohort. The multivariate analysis revealed that older age (P=0.031), lung metastasis (P=0.012), and liver metastasis (P=0.008) were risk contributors for three-month mortality, while radiation (P=0.002) and chemotherapy (P<0.001) were protective factors. The random forest model showed the highest area under curve (AUC) value (0.796, 95% CI: 0.746-0.847), the second-highest precision (0.876) and accuracy (0.778), and the highest Youden index (1.486), in comparison to the other three machine learning approaches. The AUC value was 0.748 (95% CI: 0.653-0.843) and the accuracy was 0.745, according to the external validation cohort. Based on the random forest model, a web calculator was established: https://starxueshu-codeok-main-8jv2ws.streamlitapp.com/. When compared to patients in the low-risk groups, patients in the high-risk groups had a 1.99 times higher chance of dying within three months in the internal validation cohort and a 2.37 times higher chance in the external validation cohort (Both P<0.001).ConclusionsThe random forest model has promising performance with favorable discrimination and calibration. This study suggests a web-based calculator based on the random forest model to estimate the three-month mortality among bone metastases from CUP, and it may be a helpful tool to direct clinical decision-making, inform patients about their prognosis, and facilitate therapeutic communication between patients and physicians.

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Section: Model Featuresmentioning

confidence: 82%

Development of a web-based calculator to predict three-month mortality among patients with bone metastases from cancer of unknown primary: An internally and externally validated study using machine-learning techniques

et al. 2022

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“…Histopathologically, the gallbladder tumor was diagnosed as a benign hyperplastic polyp. Based on the results of immunochemical staining, the liver tumor was diagnosed as poorly differentiated adenocarcinoma, highly suspected of liver metastases from the stomach, duodenum or small intestine (10,22,23). However, postoperative whole-body PET/CT and small intestine fluoroscopy showed no suspicious primary lesion.…”

Section: Discussionmentioning

confidence: 99%

“…Liver tumors were positive for CK20, CD10 and MUC5AC and negative for CK7, hepatocyte, PSA, CDK2 and CEA (Figure 2D). This immune phenotype suggested the liver tumors were poorly differentiated adenocarcinoma that originated from the stomach, duodenum or small intestine (10,22,23).…”

Section: Preoperative Diagnostic Images Contrast-enhanced Computed Tomography (Ct) Coronal Images In the Portal Venous Phase Showing The mentioning

confidence: 99%

“…In patients with liver metastases, to identify the primary site, various assessments are required, including patient history, serum tumor markers, detailed diagnostic imaging, as well as histopathological examination (10,11). Metastatic adenocarcinoma is the most common CUP.…”

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confidence: 99%

“…Metastatic adenocarcinoma is the most common CUP. The primary site of approximately one-third of patients of metastatic adenocarcinoma of unknown primary site (MACUP) has been identified in a digestive organ (10). Occurrence in digestive organs is significantly linked with liver [odds ratio (OR)=13.21, p<0.001] or lung (OR=2.36, p=0.001) metastases (10).…”

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Laparoscopic Surgery for a Patient With Multiple Liver Metastases of Unknown Origin Concomitant With Gallbladder Tumor

Hara¹,

Yamamura²,

Matsumura³

et al. 2021

In Vivo

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Background: The liver is the digestive organ where metastatic adenocarcinoma of unknown primary site is most often observed. Case Report: A 74-year-old man was diagnosed with a growing gallbladder tumor and multiple liver tumors limited to the left lateral sector. Liver tumors were suggested to be primary or secondary adenocarcinoma with no relation to the gallbladder tumor. Also for diagnostic purposes, laparoscopic full-thickness resection of the gallbladder, laparoscopic lateral sectionectomy and lymph node sampling were performed. The final histopathological diagnosis was hyperplastic polyp of the gallbladder and metastatic poorly differentiated adenocarcinoma of the liver. Liver tumors were suspected to originate from the stomach, duodenum, or small intestine; however, the primary sites could not be identified. The patient has been closely followed up without any chemotherapy 3 months after surgery. Conclusion: Laparoscopic surgery can be strongly recommended for patients with multiple liver tumors of unknown origin concomitant with a gallbladder tumor.

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Descriptive epidemiology of cancer of unknown primary in South Korea, 1999–2017

Boo

Park

Lim

et al. 2021

Cancer Epidemiology

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Risk factors and predictors for tumor site origin in metastatic adenocarcinoma of unknown primary site

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 6 publications

References 22 publications

Development of a web-based calculator to predict three-month mortality among patients with bone metastases from cancer of unknown primary: An internally and externally validated study using machine-learning techniques

Development of a web-based calculator to predict three-month mortality among patients with bone metastases from cancer of unknown primary: An internally and externally validated study using machine-learning techniques

Laparoscopic Surgery for a Patient With Multiple Liver Metastases of Unknown Origin Concomitant With Gallbladder Tumor

Descriptive epidemiology of cancer of unknown primary in South Korea, 1999–2017

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