Long-term survival by repeat resection for metastases from primary retroperitoneal leiomyosarcoma: A case report

Kitasaki, Nao; Abe, Tomoyuki; Oshita, Akihiko; Kobayashi, Tsuyoshi; Yonehara, Shuji; Ohdan, Hideki; Noriyuki, Toshio; Nakahara, Masaaki

doi:10.1016/j.ijscr.2021.105891

Cited by 2 publications

(1 citation statement)

References 20 publications

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“…While complete resection remains the gold standard of treatment, with a 50% chance of a 5 years survival rate 6 , adjacent organs are always infiltrated by tumours and are typically removed concurrently. The invasion of prominent blood vessels by RLS is a common cause of the incomplete removal of a tumour, resulting in a recurrence rate of up to 80% after resection 7 . RLS also exhibits malignant characteristics, resulting in a poor prognosis and a low 5-year survival rate 8 .…”

Section: Introductionmentioning

confidence: 99%

A novel nomogram model to predict the overall survival of patients with retroperitoneal leiomyosarcoma: a large cohort retrospective study

Huang

et al. 2022

Sci Rep

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Retroperitoneal leiomyosarcomas (RLS) are the second most common type of retroperitoneal sarcoma and one of the most aggressive tumours. The lack of early warning signs and delay in regular checkups lead to a poor prognosis. This study aims to create a nomogram to predict RLS patients' overall survival (OS). Patients diagnosed with RLS in the Surveillance, Epidemiology, and End Results (SEER) database between 2000 and 2018 were enrolled in this study. First, univariable and multivariable Cox regression analyses were used to identify independent prognostic factors, followed by constructing a nomogram to predict patients' OS at 1, 3, and 5 years. Secondly, the nomogram's distinguishability and prediction accuracy were assessed using receiver operating characteristic (ROC) and calibration curves. Finally, the decision curve analysis (DCA) investigated the nomogram's clinical utility. The study included 305 RLS patients, and they were divided into two groups at random: a training set (216) and a validation set (89). The training set's multivariable Cox regression analysis revealed that surgery, tumour size, tumour grade, and tumour stage were independent prognostic factors. ROC curves demonstrated that the nomogram had a high degree of distinguishability. In the training set, area under the curve (AUC) values for 1, 3, and 5 years were 0.800, 0.806, and 0.788, respectively, while in the validation set, AUC values for 1, 3, and 5 years were 0.738, 0.780, and 0.832, respectively. As evidenced by the calibration curve, the nomogram had high prediction accuracy. Moreover, DCA revealed that the nomogram had high clinical utility. Furthermore, the risk stratification system based on the nomogram could effectively categorise patients into three mortality risk subgroups. Therefore, the developed nomogram and risk stratification system may aid in optimising the treatment decisions of RLS patients to improve treatment prognosis and maximise their healthcare outcomes.

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Section: Introductionmentioning

confidence: 99%

A novel nomogram model to predict the overall survival of patients with retroperitoneal leiomyosarcoma: a large cohort retrospective study

Huang

et al. 2022

Sci Rep

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Web-based nomograms for predicting overall survival and cancer-specific survival in retroperitoneal leiomyosarcoma: a population-based analysis

Feng

2023

J Cancer Res Clin Oncol

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Long-term survival by repeat resection for metastases from primary retroperitoneal leiomyosarcoma: A case report

Cited by 2 publications

References 20 publications

A novel nomogram model to predict the overall survival of patients with retroperitoneal leiomyosarcoma: a large cohort retrospective study

A novel nomogram model to predict the overall survival of patients with retroperitoneal leiomyosarcoma: a large cohort retrospective study

Web-based nomograms for predicting overall survival and cancer-specific survival in retroperitoneal leiomyosarcoma: a population-based analysis

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