Dataset Information

Development of a Nomogram Predicting the Risk of Persistence/Recurrence of Cervical Dysplasia.

ABSTRACT: Background: Cervical dysplasia persistence/recurrence has a great impact on women's health and quality of life. In this study, we investigated whether a prognostic nomogram may improve risk assessment after primary conization. Methods: This is a retrospective multi-institutional study based on charts of consecutive patients undergoing conization between 1 January 2010 and 31 December 2014. A nomogram assessing the importance of different variables was built. A cohort of patients treated between 1 January 2015 and 30 June 2016 was used to validate the nomogram. Results: A total of 2966 patients undergoing primary conization were analyzed. The median (range) patient age was 40 (18-89) years. At 5-year of follow-up, 6% of patients (175/2966) had developed a persistent/recurrent cervical dysplasia. Median (range) recurrence-free survival was 18 (5-52) months. Diagnosis of CIN3, presence of HR-HPV types, positive endocervical margins, HPV persistence, and the omission of HPV vaccination after conization increased significantly and independently of the risk of developing cervical dysplasia persistence/recurrence. A nomogram weighting the impact of all variables was built with a C-Index of 0.809. A dataset of 549 patients was used to validate the nomogram, with a C-index of 0.809. Conclusions: The present nomogram represents a useful tool for counseling women about their risk of persistence/recurrence after primary conization. HPV vaccination after conization is associated with a reduced risk of CIN2+.

SUBMITTER: Bogani G

PROVIDER: S-EPMC9029732 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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Development of a Nomogram Predicting the Risk of Persistence/Recurrence of Cervical Dysplasia.

Bogani Giorgio G Lalli Luca L Sopracordevole Francesco F Ciavattini Andrea A Ghelardi Alessandro A Simoncini Tommaso T Plotti Francesco F Casarin Jvan J Serati Maurizio M Pinelli Ciro C Bergamini Alice A Gardella Barbara B Dell'Acqua Andrea A Monti Ermelinda E Vercellini Paolo P Palaia Innocenza I Perniola Giorgia G Fischetti Margherita M Santangelo Giusi G Fracassi Alice A D'Ippolito Giovanni G Aguzzoli Lorenzo L Mandato Vincenzo Dario VD Giannella Luca L Scaffa Cono C Falcone Francesca F Borghi Chiara C Malzoni Mario M Giannini Andrea A Salerno Maria Giovanna MG Liberale Viola V Contino Biagio B Donfrancesco Cristina C Desiato Michele M Perrone Anna Myriam AM Dondi Giulia G De Iaco Pierandrea P Ferrero Simone S Sarpietro Giuseppe G Matarazzo Maria G MG Cianci Antonio A Cianci Stefano S Bosio Sara S Ruisi Simona S Mosca Lavinia L Tinelli Raffaele R De Vincenzo Rosa R Zannoni Gian Franco GF Ferrandina Gabriella G Petrillo Marco M Capobianco Giampiero G Dessiole Salvatore S Carlea Annunziata A Zullo Fulvio F Muschiato Barbara B Palomba Stefano S Greggi Stefano S Spinillo Arsenio A Ghezzi Fabio F Colacurci Nicola N Angioli Roberto R Benedetti Panici Pierluigi P Muzii Ludovico L Scambia Giovanni G Raspagliesi Francesco F Di Donato Violante V

Vaccines 20220409 4

<b>Background:</b> Cervical dysplasia persistence/recurrence has a great impact on women's health and quality of life. In this study, we investigated whether a prognostic nomogram may improve risk assessment after primary conization. <b>Methods:</b> This is a retrospective multi-institutional study based on charts of consecutive patients undergoing conization between 1 January 2010 and 31 December 2014. A nomogram assessing the importance of different variables was built. A cohort of patients tr ...[more]

PMID: 35455328

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Project description:BackgroundVarious studies reported that the prognosis of patients with cervical cancer (CC) was significantly associated with immunity, whereas limited studies have explored whether immune-associated genes could be classifiers for recurrence-free survival (RFS) of stage I CC. Thus, an improved immune-related gene signature for stage I CC patients' prognosis is urgently required.Materials and methodsWe retrospectively analyzed the gene expression profiles of stage I CC patients in the GSE44001 set from the Gene Expression Omnibus (GEO) database. The stage I CC patients were randomly divided into the training group and the internal validation group. The training patients were adopted to develop a prognostic immune gene-based signature; meanwhile, the internal validation patients were used to validate the power of the selected immune gene-related signature using univariate Cox proportional hazard analysis, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis. The accuracy and reliability of the immune gene-related signature were evaluated based on Kaplan-Meier analysis and time-dependent receiver operating characteristic (ROC) curves.ResultsHigh power of the 8-immune gene signature was found on the basis of ROC analysis (AUC at 1, 3, and 5 years were exhibited in the internal validation group (0.702, 0.715, and 0.728, respectively), external validation group (0.702, 0.825, and 0.842, respectively), and entire GEO dataset (0.840, 0.894, and 0.852, respectively)). Besides, C-index, ROC, calibration plots, and decision curve analysis (DCA) also acted well in our nomogram, suggestive of a high ability of the nomogram to elevate the prognostic prediction of stage I CC patients.ConclusionsIn this study, we successfully constructed an integrated 8-immune gene-based signature which could accurately identify patients with low prognostic risk from those with high prognostic risk. In addition, we developed an immune-related nomogram which can elevate the prognostic prediction of stage I CC patients.

Project description:BackgroundAfter radical surgery, early detection of recurrence and metastasis is a crucial factor in enhancing the prognosis and survival of patients with gastric cancer (GC). Therefore, assessing the risk of recurrence in gastric cancer patients and determining the timing for postoperative recurrence is crucial.MethodsThe clinicopathological data of 521 patients with recurrent gastric cancer, who underwent radical gastrectomy at Zhejiang Cancer Hospital between January 2010 and January 2017, were retrospectively analyzed. These patients were randomly divided into two groups: a training group (n = 365) and a validation group (n = 156). In the training set, patients were further categorized into early recurrence (n = 263) and late recurrence (n = 102) groups based on a 2-year boundary. Comparative analyses of clinicopathological features and prognoses were conducted between these two groups. Subsequently, a nomogram for predicting early recurrence was developed and validated.ResultsIn this study, the developed nomogram incorporated age, serous infiltration, lymph node metastasis, recurrence mode, and the tumour marker CA19-9. In the training cohort, the area under the curve (AUC value) was 0.739 (95% CI, 0.682-0.798), with a corresponding C-index of 0.739. This nomogram was subsequently validated in an independent validation cohort, yielding an AUC of 0.743 (95% CI, 0.652-0.833) and a C-index of 0.743. Furthermore, independent risk factors for prognosis were identified, including age, absence of postoperative chemotherapy, early recurrence, lymph node metastasis, abdominal metastasis, and vascular cancer embolus.ConclusionIndependent risk factors for gastric cancer recurrence following radical surgery were utilized to construct a nomogram for predicting early relapse. This nomogram effectively assesses the risk of recurrence, aids in treatment decision-making and follow-up planning in clinical settings, and demonstrated strong performance in the validation cohort.

Project description:ObjectiveThe aim of this study was to establish a nomogram model for predicting the risk of short-term recurrence in glioma patients.MethodsThe clinical data of recurrent glioma patients were summarized and analyzed in this study. Univariate and multivariate logistic regression analyses were performed to analyze the correlation between clinical data and the risk of short-term recurrence after operation. A nomogram was established based on the multivariate logistic regression model results.ResultsA total of 175 patients with recurrent glioma were enrolled, with 53 patients in the short-term recurrence (STR) group (recurrent time ≤6 months) and 122 patients in the long-term recurrence (LTR) group (recurrent time ≥36 months). Univariate analysis revealed that age at diagnosis, Karnofsky performance scores (KPSs), tumor location, glioma grade, glioma type, extent of resection (EOR), adjuvant chemotherapy (ad-CT), concurrent chemotherapy (co-CT), and isocitrate dehydrogenase (IDH) status were significantly associated with the short-term glioma recurrence. Multivariate analyses revealed that age at diagnosis, KPS, glioma grade, EOR, and IDH were independent risk factors for short-term glioma recurrence. A risk nomogram for the short-term recurrence of glioma was established, with the concordance index (C-index) of 0.971. The findings of calibration and receiver operating characteristic (ROC) curves showed that our nomogram model had good performance and discrimination to estimate short-term recurrence probability.ConclusionThis nomogram model provides reliable information about the risk of short-term glioma recurrence for oncologists and neurosurgeons. This model can predict the short-term recurrence probability and give assistance to decide the interval of follow-up or formulate individualized treatment strategies based on the predicted results. A free online prediction risk tool for this nomogram is provided: https://rj2021.shinyapps.io/Nomogram_ recurrence-risk/.

Dataset Information

Development of a Nomogram Predicting the Risk of Persistence/Recurrence of Cervical Dysplasia.

Publications

Development of a Nomogram Predicting the Risk of Persistence/Recurrence of Cervical Dysplasia.

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