Literature DB >> 14693338

Modulation of surgery in early invasive cervical cancer.

Pierluigi Benedetti Panici1, Giuseppe Cutillo, Roberto Angioli.   

Abstract

In modern oncology increasing attention is given to patient quality of life issues. Reduction of morbidity and preservation of reproductive organs are aspects of major concern for surgeons treating women affected by gynecologic tumors. To achieve these goals both improvements of surgical technique and peri-operative management, but mainly a better individualization of therapy are needed. This requires: (1) advanced knowledge of the natural history of disease, (2) accurate pathological evaluation, (3) innovative diagnostic tools. In the last decades remarkable progresses have been made in these fields making modulation of surgery a concrete option in the treatment of early invasive cervical cancer. Currently, tumor volume measurements by step serial section of cone specimen (stage IA(2) and small volume IB(1)), sentinel nodal group lymphadenectomy and sentinel node biopsy (stage IB(1)) represent the best techniques available for assessing the risk of extracervical spread of disease allowing tailoring of patient management to optimize the patients outcome and quality of life.

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Year:  2003        PMID: 14693338     DOI: 10.1016/s1040-8428(03)00124-0

Source DB:  PubMed          Journal:  Crit Rev Oncol Hematol        ISSN: 1040-8428            Impact factor:   6.312


  3 in total

1.  Less versus more radical surgery in stage IB1 cervical cancer: A population-based study of long-term survival.

Authors:  Jill H Tseng; Alessia Aloisi; Yukio Sonoda; Ginger J Gardner; Oliver Zivanovic; Nadeem R Abu-Rustum; Mario M Leitao
Journal:  Gynecol Oncol       Date:  2018-07       Impact factor: 5.482

2.  Treatment and Outcomes of Early and Operable Recurrent Cervical Cancer: A Prospective Study.

Authors:  Nikhil Mehta; Sanjay M Desai; Vinod Dhakad; Dhruv Patel; Elroy Saldanha
Journal:  Niger J Surg       Date:  2021-03-09

3.  Application of gene expression programming and neural networks to predict adverse events of radical hysterectomy in cervical cancer patients.

Authors:  Maciej Kusy; Bogdan Obrzut; Jacek Kluska
Journal:  Med Biol Eng Comput       Date:  2013-10-18       Impact factor: 2.602

  3 in total

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