Predictive models for lymph node metastases in patients with testicular germ cell tumors

Verfasser / Beitragende:
[Yun Mao, Sandeep Hedgire, Duangkamon Prapruttam, Mukesh Harisinghani]
Ort, Verlag, Jahr:
2015
Enthalten in:
Abdominal Imaging, 40/8(2015-10-01), 3196-3205
Format:
Artikel (online)
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024 7 0 |a 10.1007/s00261-015-0526-5  |2 doi 
035 |a (NATIONALLICENCE)springer-10.1007/s00261-015-0526-5 
245 0 0 |a Predictive models for lymph node metastases in patients with testicular germ cell tumors  |h [Elektronische Daten]  |c [Yun Mao, Sandeep Hedgire, Duangkamon Prapruttam, Mukesh Harisinghani] 
520 3 |a Purpose: To develop predictive models for lymph node (LN) metastasis in testicular germ cell tumors. Materials and Methods: 291 patients with testicular germ cell tumors were included, which were divided into seminomatous and nonseminomatous groups. For screening the risk factors for LN metastasis, the tumor-related characteristics (including histopathological information and tumor markers) alpha fetoprotein and the lymph node-related features on CT were compared between metastatic cases and nonmetastatic cases. Two logistic regression models were built for each histological group, one depending on all tumor- and lymph node-related risk factors (Model 1) and another only on tumor-related factors (Model 2). Receivers operating characteristic curves were used to evaluate the predictive abilities of these models. Results: 117 positive nodes/regions were identified in 68 patients, including 51 metastases and 17 occult metastases. Based on the selected independent risk factors, the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of Models 1 and 2 in seminomatous and nonseminomatous groups were (95.5%, 95.3%, 95.3%, 77.8%, and 99.2%), (63.6%, 83.6%, 80.7%, 40.0%, and 93.0%), (93.5%, 94.7%, 94.3%, 89.6%, and 96.8%), and (89.1%, 44.2%, 58.9%, 43.6%, and 89.4%), respectively. Conclusion: Two predictive models for each seminomatous and nonseminomatous testicular tumor were established based on lymph node- and tumor-related risk factors. In patients with tumor and lymph node-related risk factors, regular CT surveillance is likely sufficient for predicting LN status, while in the patients without any tumor and lymph node-related risk factors a long interval-time CT follow-up should be considered. Additionally, right side tumors tend to involve contralateral LNs compared to left side ones. Positive inguinal LNs more frequently occur in patients with a history of groin surgery. 
540 |a Springer Science+Business Media New York, 2015 
690 7 |a Testicular cancer  |2 nationallicence 
690 7 |a Lymph nodes  |2 nationallicence 
690 7 |a CT surveillance  |2 nationallicence 
690 7 |a Seminoma  |2 nationallicence 
690 7 |a Nonseminomatous germ cell tumors  |2 nationallicence 
700 1 |a Mao  |D Yun  |u Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, 1 Youyi Street, Yuanjiagang Yuzhong District, 400016, Chongqing, China  |4 aut 
700 1 |a Hedgire  |D Sandeep  |u Division of Abdominal Imaging and Intervention, Massachusetts General Hospital-Harvard Medical School, 55 Fruit St, 02114, Boston, MA, USA  |4 aut 
700 1 |a Prapruttam  |D Duangkamon  |u Division of Abdominal Imaging and Intervention, Massachusetts General Hospital-Harvard Medical School, 55 Fruit St, 02114, Boston, MA, USA  |4 aut 
700 1 |a Harisinghani  |D Mukesh  |u Division of Abdominal Imaging and Intervention, Massachusetts General Hospital-Harvard Medical School, 55 Fruit St, 02114, Boston, MA, USA  |4 aut 
773 0 |t Abdominal Imaging  |d Springer US; http://www.springer-ny.com  |g 40/8(2015-10-01), 3196-3205  |x 0942-8925  |q 40:8<3196  |1 2015  |2 40  |o 261 
856 4 0 |u https://doi.org/10.1007/s00261-015-0526-5  |q text/html  |z Onlinezugriff via DOI 
898 |a BK010053  |b XK010053  |c XK010000 
900 7 |a Metadata rights reserved  |b Springer special CC-BY-NC licence  |2 nationallicence 
908 |D 1  |a research-article  |2 jats 
949 |B NATIONALLICENCE  |F NATIONALLICENCE  |b NL-springer 
950 |B NATIONALLICENCE  |P 856  |E 40  |u https://doi.org/10.1007/s00261-015-0526-5  |q text/html  |z Onlinezugriff via DOI 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Mao  |D Yun  |u Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, 1 Youyi Street, Yuanjiagang Yuzhong District, 400016, Chongqing, China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Hedgire  |D Sandeep  |u Division of Abdominal Imaging and Intervention, Massachusetts General Hospital-Harvard Medical School, 55 Fruit St, 02114, Boston, MA, USA  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Prapruttam  |D Duangkamon  |u Division of Abdominal Imaging and Intervention, Massachusetts General Hospital-Harvard Medical School, 55 Fruit St, 02114, Boston, MA, USA  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Harisinghani  |D Mukesh  |u Division of Abdominal Imaging and Intervention, Massachusetts General Hospital-Harvard Medical School, 55 Fruit St, 02114, Boston, MA, USA  |4 aut 
950 |B NATIONALLICENCE  |P 773  |E 0-  |t Abdominal Imaging  |d Springer US; http://www.springer-ny.com  |g 40/8(2015-10-01), 3196-3205  |x 0942-8925  |q 40:8<3196  |1 2015  |2 40  |o 261