Role of laparoscopic hysterectomy in cervical and endometrial cancer: a narrative review.
Georgios GitasGeorge PadosAntonio Simone LaganàVeronika GuentherJohannes Ackermannİbrahim AlkatoutPublished in: Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy (2022)
Endometrial cancer is the most common carcinoma of the female genital organs and cervical cancer is the leading cause of cancer death in women worldwide. The aim of this review is to evaluate the role of laparoscopic hysterectomy in patients with endometrial and cervical cancer in this period, and analyze the outcome of hysterectomy in terms of survival. Moreover, we present the historical background, new techniques, the anatomical features, and surgical steps of radical hysterectomy. According to new evidence, minimally invasive surgery in patients with cervical cancer is associated with higher rates of recurrence and mortality compared to the open approach. Despite the numerous explanations offered for this phenomenon, the reasons for these results are unclear. Additional large trials have been launched to reevaluate the above-mentioned data. On contrary, the laparoscopic approach provides surgical outcomes and similar survival rates as open surgery in patients with early endometrial carcinoma. Furthermore, the radicality of hysterectomy does not influence local recurrence rates or overall survival in cases with complete surgical removal of the tumor. A laparoscopic radical hysterectomy is no longer an option in patients with cervical cancer. When minimally invasive surgery is offered, the patients must be counseled in detail about the current debate.
Keyphrases
- endometrial cancer
- robot assisted
- minimally invasive
- free survival
- ejection fraction
- newly diagnosed
- electronic health record
- risk factors
- pregnant women
- acute coronary syndrome
- prognostic factors
- squamous cell carcinoma
- metabolic syndrome
- atrial fibrillation
- coronary artery bypass
- machine learning
- big data
- coronary artery disease
- pregnancy outcomes
- artificial intelligence
- chronic kidney disease
- childhood cancer