Objective: This study investigated the perioperative and oncological outcomes of laparoscopic retroperitoneal lymph node dissection (RPLND) procedures for post-chemotherapy patients with nonseminomatous testicular germ-cell tumor at a single center.
Methods: This study included patients with nonseminomatous testicular cancer who underwent RPLND after chemotherapy at the Kyushu University Hospital between 2016 and 2024. The preoperative clinicopathological characteristics, perioperative outcomes, and oncological outcomes were investigated.
Results: A total of 13 patients underwent laparoscopic RPLND. Median maximum retroperitoneal tumor size at post-chemotherapy before RPLND was 11 mm (range, 2-30 mm). RPLND template was one side and both sides in nine and four patients. Median operative time was 272 min (range, 129-490 min), and median estimated blood loss was 27 mL (range, 0-100 mL). Median time from operation to discharge was 8 days (range, 5-15 days). There was no severe perioperative and postoperative complication. Residual cancer and teratoma were detected in one and seven patients. During median follow-up of 18.6 months (range, 1.0-95.7 months), no case presented recurrence.
Conclusion: Laparoscopic RPLND presented safety in perioperative outcomes and favorable oncological outcomes. Thus, it was confirmed that laparoscopic RPLND is a feasible minimally invasive procedure for selected cases.
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http://dx.doi.org/10.1111/ases.13416 | DOI Listing |
Curr Oncol
November 2024
Department of Medicine and Surgery, Kore University of Enna, 94100 Enna, Italy.
(1) Background: Testicular cancer, although accounting for only 0.5% to 1% of all solid male cancers, is the most common malignancy in males aged 15 to 35 years. Non-seminomatous germ cell tumors (NSGCT) represent nearly half of all testicular germ cell tumors and are associated with a more aggressive clinical course.
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November 2024
Pathology, All India Institute of Medical Sciences, Rishikesh, Rishikesh, IND.
Germ cell tumors, the most common of the testicular neoplasms, originate from primordial germ cells. These tumors are known for their totipotent nature, capable of differentiating into various cell types. This case report presents a rare occurrence of mucinous cystadenoma in a patient who received chemotherapy for metastatic left non-seminomatous germ cell tumor (NSGCT) of the testis.
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November 2024
Urology, Broward Health Coral Springs, Coral Springs, USA.
Testicular cancer is one of the leading malignancies affecting young men, with germ cell tumors (GCTs) being the most prevalent type. These tumors are classified into two main subtypes: seminomas and non-seminomatous germ cell tumors (NSGCTs), with the latter known for their higher likelihood of metastasis. Early detection through imaging and tumor markers like alpha-fetoprotein (AFP) and beta-human chorionic gonadotropin (HCG) is crucial for favorable outcomes.
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November 2024
Pathology and Laboratory Medicine, University of California Davis Health System, Sacramento, USA.
We present a case of a 36-year-old male found to have a nonseminomatous germ cell tumor (NSGCT) with alpha-fetoprotein levels (AFP) of 737.9 ng/mL and beta-human chorionic gonadotropin (β-HCG) of 692 IU/mL. Pathology analysis after left orchiectomy showed a mixed germ cell tumor with 20% embryonal carcinoma, 20% yolk sac tumor, and 60% teratoma.
View Article and Find Full Text PDFCell Rep Med
December 2024
State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou 510060, P.R. China; Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, P.R. China. Electronic address:
Predicting the histopathology of residual retroperitoneal masses (RMMs) before post-chemotherapy retroperitoneal lymph node dissection in metastatic nonseminomatous germ cell tumors (NSGCTs) can guide individualized treatment and minimize complications. Previous single approach-based models perform poorly in validation. Herein, we introduce a machine learning model that evolves from a single-dimensional tumor diameter to incorporate high-dimensional radiomic features, with its effectiveness assessed using the macro-average area under the receiver operating characteristic curves (AUCs).
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