宫颈癌是女性中最常见的癌症之一，全球女性癌症发病率约占所有女性癌症的6.5％。早期检测和根据分期进行充分治疗可以提高患者的生存期。预测模型可能有助于治疗决策，但关于宫颈癌患者的预测模型的系统回顾文章尚未出现。我们按照PRISMA指南进行了宫颈癌预测模型的系统回顾。从文章中提取用于模型训练和验证的关键特征，以及终点数据进行分析。选择的文章根据预测终点分组，即分组1：总生存期，分组2：无进展生存期，分组3：复发或远处转移，分组4：治疗反应，分组5：毒副作用或生活质量。我们制定了一个评估手稿的评分系统。根据我们的标准，研究基于我们的评分系统获得的分数分为四组，最重要的研究（得分> 60％），显著研究（60％>分数> 50％），适度显著研究（50％>分数> 40％）和最不显著研究（分数<40％）。对所有组进行了元分析。 搜索的首行选择了1358篇文章，最终选择了39篇文章作为回顾的可包含文章。根据我们的评估标准，16项，13项和10项研究分别被认为是最重要的，显著的和适度显著的。第1组，第2组，第3组，第4组和第5组的组内汇总相关系数分别为0.76 [0.72，0.79]，0.80 [0.73，0.86]，0.87 [0.83，0.90]，0.85 [0.77，0.90]，0.88 [0.85，0.90]。在终点预测中，所有模型均被认为是良好的（预测准确度[c-index / AUC / R2]> 0.7）。 宫颈癌毒副作用、局部或远处复发和生存期预测的预测模型显示出有希望的结果，具有合理的预测准确度[c-index / AUC / R2> 0.7]。这些模型还应在外部数据上得到验证，并在前瞻性临床研究中得到评估。 版权所有 © 2023作者。Elsevier B.V.发表。保留所有权利。

Cervical cancer is one of the most common cancers in women with an incidence of around 6.5 % of all the cancer in women worldwide. Early detection and adequate treatment according to staging improve the patient's life expectancy. Outcome prediction models might aid treatment decisions, but a systematic review on prediction models for cervical cancer patients is not available.We performed a systematic review for prediction models in cervical cancer following PRISMA guidelines. Key features that were used for model training and validation, the endpoints were extracted from the article and data were analyzed. Selected articles were grouped based on prediction endpoints i.e. Group1: Overall survival, Group2: progression-free survival; Group3: recurrence or distant metastasis; Group4: treatment response; Group5: toxicity or quality of life. We developed a scoring system to evaluate the manuscript. As per our criteria, studies were divided into four groups based on scores obtained in our scoring system, the Most significant study (Score > 60 %); Significant study (60 % > Score > 50 %); Moderately Significant study (50 % > Score > 40 %); least significant study (score < 40 %). A meta-analysis was performed for all the groups separately.The first line of search selected 1358 articles and finally 39 articles were selected as eligible for inclusion in the review. As per our assessment criteria, 16, 13 and 10 studies were found to be the most significant, significant and moderately significant respectively. The intra-group pooled correlation coefficient for Group1, Group2, Group3, Group4, and Group5 were 0.76 [0.72, 0.79], 0.80 [0.73, 0.86], 0.87 [0.83, 0.90], 0.85 [0.77, 0.90], 0.88 [0.85, 0.90] respectively. All the models were found to be good (prediction accuracy [c-index/AUC/R2] >0.7) in endpoint prediction.Prediction models of cervical cancer toxicity, local or distant recurrence and survival prediction show promising results with reasonable prediction accuracy [c-index/AUC/R2 > 0.7]. These models should also be validated on external data and evaluated in prospective clinical studies.Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.