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Combined Reporting of Surgical Quality and Cancer Control after Surgical Treatment for Penile Tumors with Inguinal Lymph Node Dissection: The <i>Tetrafecta</i> Achievement
oleh: Aldo Brassetti, Umberto Anceschi, Gabriele Cozzi, Julian Chavarriaga, Pavel Gavrilov, Josep Maria Gaya Sopena, Alfredo Maria Bove, Francesco Prata, Mariaconsiglia Ferriero, Riccardo Mastroianni, Leonardo Misuraca, Gabriele Tuderti, Giulia Torregiani, Marco Covotta, Diego Camacho, Gennaro Musi, Rodolfo Varela, Alberto Breda, Ottavio De Cobelli, Giuseppe Simone
| Format: | Article |
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| Diterbitkan: | MDPI AG 2023-02-01 |
Deskripsi
Background: To optimize results reporting after penile cancer (PC) surgery, we proposed a <i>Tetrafecta</i> and assessed its ability to predict overall survival (OS) probabilities. Methods: A purpose-built multicenter, multi-national database was queried for stage I–IIIB PC, requiring inguinal lymphadenectomy (ILND), from 2015 onwards. Kaplan–Meier (KM) method assessed differences in OS between patients achieving <i>Tetrafecta</i> or not. Univariable and multivariable regression analyses identified its predictors. Results: A total of 154 patients were included in the analysis. The 45 patients (29%) that achieved the <i>Tetrafecta</i> were younger (59 vs. 62 years; <i>p</i> = 0.01) and presented with fewer comorbidities (ASA score ≥ 3: 0% vs. 24%; <i>p</i> < 0.001). Although indicated, ILND was omitted in 8 cases (5%), while in 16, a modified template was properly used. Although median LNs yield was 17 (IQR: 11–27), 35% of the patients had <7 nodes retrieved from the groin. At Kaplan–Maier analysis, the <i>Tetrafecta</i> cohort displayed significantly higher OS probabilities (Log Rank = 0.01). Uni- and multivariable logistic regression analyses identified age as the only independent predictor of <i>Tetrafecta</i> achievement (OR: 0.97; 95%CI: 0.94–0.99; <i>p</i> = 0.04). Conclusions: Our <i>Tetrafecta</i> is the first combined outcome to comprehensively report results after PC surgery. It is widely applicable, based on standardized and reproducible variables and it predicts all-cause mortality.