Browsing by Author "Mom, CH"

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Improved Risk Prediction in Human Papillomavirus-Associated Endocervical Adenocarcinoma Through Assessment of Binary Silva Pattern-based Classification: An International Multicenter Retrospective Observational Study Led by the International Society of Gynecological Pathologists (ISGyP)
(Lippincott Williams and Wilkins, 2024) Powell, A; Hodgson, A; Cohen, PA; Rabban, TJ; Park, KJ; McCluggage, WG; Gilks, CB; Singh, N; Oliva, E; Cardinal, LH; Díaz, LB; Falcón, F; Garcia, Kamermann, FA; Sciaccaluga, MD; Bittinger, S; Bulsara, M; Codde, J; Newman, MR; Spinderjeet, S; Talia, KL; Volchek, M; Djordevic, B; Hoang, L; Parra-Herran, C; Turashvili, G; Gao, H-W; Jiang, Q; Li, J; Liu, A; Sun, P-L; Wang, Y; Zhang, J; Bazalová, B; Bouda, J; Dundr, P; Ondic, O; Gotthardt, N; Hoehn, AK; Horn, L-C; Akakpo, KP; Ayabilah, EA; Yarney, J; Tse, K-Y; Wong, RW; Wong, TS; Ip, PPC; Rai, B; Srinivasan, R; Conlon, N; Ardighieri, L; Bignotti, E; Ferrari, F; Mandato, VD; Mastrofilippo, V; Odicino, F; Palicelli, A; Pesci, A; Zanelli, M; Zannoni, GF; Kiyokawa, T; Alvarado-Cabrero, I; Esperanza, M; Webb, P; Bartosch, C; Felix, A; Ferreira, J; Lérias, S; SoutoMoura, M; Kim, K-R; Akkour, KM; Aljehani, AM; Arafah, MA; Tulbah, AM; Wadee, R; Guarch, R; Guerra, E; Hardisson, D; Matias-Guiu, X; Palacios, J; Pérez-Mies, B; Rakislova, N; Saco, MA; Mateoiu, C; Bleeker, MCG; Mom, CH; Ozdemir, DA; Salman, C; Usubütün, A; Abu-Sinn, D; Arif, S; Attygalle, A; Bhatnagar, A; Biddlestone, LR; Culora, G; Haider, S; Ibrahim, S; Johnson, S; Kaushik, S; Khan, R; Leen, SLS; Latimer, A; Mandalia, T; Milan, D; Mukonoweshuro, P; Syed, S; Vergine, M; Vroobels, K; Wise, O; Wong, J; Hui, P; JoehlinPrice, AS; Adamson, K; Balzer, B; Banet, N; Bennett, JA; Brainard, J; Buza, N; Fadare, O; Gupta, M; Isacson, C; Kehr, E; Kong, C; Leonard, WA; Lieberman, R; Longacre, TA; Masand, RP; McGregor, SM; Medeiros, F; Miller, M; Moisini, I; Ordulu, Z; Paczos, T; Parkash, V; Pinto, A; Nicolas, MP; Quddus, MR; Riopel, MA; Rivera-Colon, G; Roma, AA; Safdar, NS; Segura, S; Shukla, P; Summey, RM; Tafe, LJ; Varghese, S; Williams-Brown, MY; Wolsky, RJ; Wong, S; Yemelyanova, A; Zhang, G; Zheng, W
Endocervical adenocarcinomas (EACs) are a group of malignant neoplasms associated with diverse pathogenesis, morphology, and clinical behavior. As a component of the International Society of Gynecological Pathologists International Endocervical Adenocarcinoma Project, a large international retrospective cohort of EACs was generated in an effort to study potential clinicopathological features with prognostic significance that may guide treatment in these patients. In this study, we endeavored to develop a robust human papillomavirus (HPV)-associated EAC prognostic model for surgically treated International Federation of Gynecology and Obstetrics (FIGO) stage IA2 to IB3 adenocarcinomas incorporating patient age, lymphovascular space invasion (LVSI) status, FIGO stage, and pattern of invasion according to the Silva system (traditionally a 3-tier system). Recently, a 2-tier/binary Silva pattern of invasion system has been proposed whereby adenocarcinomas are classified into low-risk (pattern A/pattern B without LVSI) and high-risk (pattern B with LVSI/pattern C) categories. Our cohort comprised 792 patients with HPV-associated EAC. Multivariate analysis showed that a binary Silva pattern of invasion classification was associated with recurrence-free and disease-specific survival (P < 0.05) whereas FIGO 2018 stage I substages were not. Evaluation of the current 3-tiered system showed that disease-specific survival for those patients with pattern B tumors did not significantly differ from that for those patients with pattern C tumors, in contrast to that for those patients with pattern A tumors. These findings underscore the need for prospective studies to further investigate the prognostic significance of stage I HPV-associated EAC substaging and the inclusion of the binary Silva pattern of invasion classification (which includes LVSI status) as a component of treatment recommendations. Copyright © 2024 by the International Society of Gynecological Pathologists.
Post-recurrence survival in patients with cervical cancer
(Academic Press Inc., 2022) Cibula, D; Dostálek, L; Jarkovsky, J; Mom, CH; Lopez, A; Falconer, H; Scambia, G; Ayhan, A; Kim, SH; Isla Ortiz, D; Klat, J; Obermair, A; Di Martino, G; Pareja, R; Manchanda, R; Kosťun, J; Dos Reis, R; Meydanli, MM; Odetto, D; Laky, R; Zapardiel, I; Weinberger, V; Benešová, K; Borčinová, M; Cardenas, F; Wallin, E; Pedone Anchora, L; Akilli, H; Abu-Rustum, NR; Barquet-Muñoz, SA; Javůrková, V; Fischerová, D; van Lonkhuijzen LRCW
Background: Up to 26% of patients with early-stage cervical cancer experience relapse after primary surgery. However, little is known about which factors influence prognosis following disease recurrence. Therefore, our aims were to determine post-recurrence disease-specific survival (PR-DSS) and to identify respective prognostic factors for PR-DSS. Methods: Data from 528 patients with early-stage cervical cancer who relapsed after primary surgery performed between 2007 and 2016 were obtained from the SCANN study (Surveillance in Cervical CANcer). Factors related to the primary disease and recurrence were combined in a multivariable Cox proportional hazards model to predict PR-DSS. Results: The 5-year PR-DSS was 39.1% (95% confidence interval [CI] 22.7%-44.5%), median disease-free interval between primary surgery and recurrence (DFI1) was 1.5 years, and median survival after recurrence was 2.5 years. Six significant variables were identified in the multivariable analysis and were used to construct the prognostic model. Two were related to primary treatment (largest tumour size and lymphovascular space invasion) and four to recurrence (DFI1, age at recurrence, presence of symptoms, and recurrence type). The C-statistic after 10-fold cross-validation of prognostic model reached 0.701 (95% CI 0.675-0.727). Three risk-groups with significantly differing prognoses were identified, with 5-year PR-DSS rates of 81.8%, 44.6%, and 12.7%. Conclusions: We developed the robust model of PR-DSS to stratify patients with relapsed cervical cancer according to risk profiles using six routinely recorded prognostic markers. The model can be utilised in clinical practice to aid decision-making on the strategy of recurrence management, and to better inform the patients.