Prognostic factors in patients with clinical stage I nonseminoma—beyond lymphovascular invasion: a systematic review

Zengerling, Friedemann; Beyersdorff, Dirk; Busch, Jonas; Heinzelbecker, Julia; Pfister, D.; Ruf, Christian; Albers, Peter; Kliesch, Sabine; Schmidt, Stefanie

doi:10.1007/s00345-022-04063-7

Cited by 7 publications

(6 citation statements)

References 36 publications

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“…Third, only one (imaging) modality and the circulating tumour markers (β-subunit of human chorionic gonadotropin (β-HCG) and alpha-fetoprotein (AFP) were used in this study. In stage I seminoma, among other prognostic factors such as rete testis or lymphovascular invasion, tumour size is the most valuable prognostic factor for relapse (77,78). Our study included solely clinical and laboratory parameters that can be collected easily, quickly, and non-invasively so that a preoperative risk assessment of the individual patient can already be made at the time of CT.…”

Section: Discussionmentioning

confidence: 99%

CT Radiomics and Clinical Feature Model to Predict Lymph Node Metastases in Early-Stage Testicular Cancer

Lisson¹,

Manoj²,

Wolf³

et al. 2023

Preprint

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Accurate retroperitoneal lymph node metastasis (LNM) prediction in early-stage testicular germ cell tumours (TGCT) harbours the potential to significantly reduce over- or undertreatment and treatment-related morbidity in this group of young patients as an important survivorship imperative. We investigated the role of computed tomography (CT) radiomics models integrating clinical predictors for the individualized prediction of LNM in early-stage TGCT. Ninety-one patients with surgically proven testicular germ cell tumours and contrast-enhanced CT were included in this retrospective study. Dedicated radiomics software was used to segment 273 retroperitoneal lymph nodes and extract features. After feature selection, radiomics-based machine learning models were developed to predict LN metastasis. The robustness of the procedure was controlled by 10-fold cross-validation. Using multivariable logistic regression modelling, we developed three prediction models: A radiomics-only model, a clinical-only model and a combined radiomics-clinical model. The models' performance was evaluated using the area under the receiver operating characteristic curve (AUC). Finally, decision curve analysis was performed to estimate the clinical usefulness of the predictive model. The radiomics-only model for predicting lymph node metastasis reached a greater discrimination power than the clinical-only model, with an AUC of 0.84 (± 0.17; 95% CI ) vs 0.60 (± 0.22; 95% CI) in our study cohort. The combined model integrating clinical risk factors and selected radiomics features outperformed the clinical-only and the radiomics-only prediction models and showed good discrimination with an area under the curve of 0.94 ( ± 0.10; 95% CI). The decision curve analysis demonstrated the clinical usefulness of our proposed combined model. The presented combined CT-based radiomics-clinical model represents an exciting non-invasive prediction tool for individualized prediction of LN metastasis in testicular germ cell tumours. Multi-centre validation is required to generate high-quality evidence for its clinical application.

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Section: Discussionmentioning

confidence: 99%

CT Radiomics and Clinical Feature Model to Predict Lymph Node Metastases in Early-Stage Testicular Cancer

Lisson¹,

Manoj²,

Wolf³

et al. 2023

Preprint

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show abstract

“…Moreover, only one (imaging) modality and the circulating tumour markers β-HCG and AFP were used in this study. Among other prognostic factors, such as lymphovascular or rete testis invasion, tumour size is the most valuable prognostic factor for early-stage seminoma relapse [65,66]. Our study included solely clinical and laboratory parameters that can be collected easily, quickly, and non-invasively so that a preoperative risk assessment of the individual patient can already be made at the time of CT.…”

Section: Discussionmentioning

confidence: 99%

CT Radiomics and Clinical Feature Model to Predict Lymph Node Metastases in Early-Stage Testicular Cancer

Lisson

Manoj

Wolf

et al. 2023

Onco

Self Cite

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Accurate retroperitoneal lymph node metastasis (LNM) prediction in early-stage testicular germ cell tumours (TGCTs) harbours the potential to significantly reduce over- or undertreatment and treatment-related morbidity in this group of young patients as an important survivorship imperative. We investigated the role of computed tomography (CT) radiomics models integrating clinical predictors for the individualised prediction of LNM in early-stage TGCT. Ninety-one patients with surgically proven testicular germ cell tumours and contrast-enhanced CT were included in this retrospective study. Dedicated radiomics software was used to segment 273 retroperitoneal lymph nodes and extract features. After feature selection, radiomics-based machine learning models were developed to predict LN metastasis. The robustness of the procedure was controlled by 10-fold cross-validation. Using multivariable logistic regression modelling, we developed three prediction models: a radiomics-only model, a clinical-only model, and a combined radiomics–clinical model. The models’ performances were evaluated using the area under the receiver operating characteristic curve (AUC). Finally, decision curve analysis was performed to estimate the clinical usefulness of the predictive model. The radiomics-only model for predicting lymph node metastasis reached a greater discrimination power than the clinical-only model, with an AUC of 0.87 (±0.04; 95% CI) vs. 0.75 (±0.08; 95% CI) in our study cohort. The combined model integrating clinical risk factors and selected radiomics features outperformed the clinical-only and the radiomics-only prediction models, and showed good discrimination with an area under the curve of 0.89 (±0.03; 95% CI). The decision curve analysis demonstrated the clinical usefulness of our proposed combined model. The presented combined CT-based radiomics–clinical model represents an exciting non-invasive tool for individualised LN metastasis prediction in testicular germ cell tumours. Multi-centre validation is required to generate high-quality evidence for its clinical application.

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“…The treatment and prognosis of testicular germ cell tumors is based on primary tumor (T-stage), reginal lymph node (N-stage), distant metastases (M-stage), serum tumor markers (S-stage), as well as the distinctions between seminoma and non-seminoma germ ell tumors [ 1 , 2 ]. The impact of histological subtypes within the non-seminoma germ cell tumor, specifically regarding pure embryonal carcinoma as a risk factor for recurrence in stage I patients, has been addressed in previous studies [ 3 , 4 , 5 , 6 , 7 , 8 ]. However, the effect of pure embryonal carcinoma vs. mixed germ cell tumor, especially in advanced testicular cancer (stages II and III), on survival is not well established.…”

Section: Introductionmentioning

confidence: 99%

Survival of Testicular Pure Embryonal Carcinoma vs. Mixed Germ Cell Tumor Patients across All Stages

et al. 2023

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Background and Objectives: The impact of pure histological subtypes in testicular non-seminoma germ cell tumors on survival, specifically regarding pure embryonal carcinoma, is not well established. Therefore, this study aimed to test for differences between pure embryonal carcinoma and mixed germ cell tumor patients within stages I, II and III in a large population-based database. Materials and Methods: We relied on the Surveillance, Epidemiology and End Results (SEER) database (2004–2019) to identify testicular pure embryonal carcinoma vs. mixed germ cell tumor patients. Cumulative incidence plots depicted cancer-specific mortality that represented the main endpoint of interest. Multivariable competing risks regression models tested for differences between pure embryonal carcinoma and mixed germ cell tumor patients in analyses addressing cancer-specific mortality and adjusted for other-cause mortality. Results: Of 11,223 patients, 2473 (22%) had pure embryonal carcinoma. Pure embryonal carcinoma patients exhibited lower cancer-specific mortality relative to their mixed germ cell tumor counterparts for both stage III (13.9 vs. 19.4%; p < 0.01) and stage II (0.5 vs. 3.4%, p < 0.01), but not in stage I (0.9 vs. 1.6%, p = 0.1). In multivariable competing risks regression models, pure embryonal carcinoma exhibited more favorable cancer-specific mortality than mixed germ cell tumor in stage III (hazard ratio 0.71, p = 0.01) and stage II (hazard ratio 0.11, p < 0.01). Conclusions: Pure embryonal carcinoma exhibits a more favorable cancer-specific mortality profile relative to mixed germ cell tumor in stage II and III testicular cancers. Consequently, the presence of mixed germ cell tumor elements may be interpreted as a risk factor for cancer-specific survival.

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Prognostic factors in patients with clinical stage I nonseminoma—beyond lymphovascular invasion: a systematic review

Cited by 7 publications

References 36 publications

CT Radiomics and Clinical Feature Model to Predict Lymph Node Metastases in Early-Stage Testicular Cancer

CT Radiomics and Clinical Feature Model to Predict Lymph Node Metastases in Early-Stage Testicular Cancer

CT Radiomics and Clinical Feature Model to Predict Lymph Node Metastases in Early-Stage Testicular Cancer

Survival of Testicular Pure Embryonal Carcinoma vs. Mixed Germ Cell Tumor Patients across All Stages

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