Jha Ashish Kumar, Mithun Sneha, Sherkhane Umeshkumar B, Jaiswar Vinay, Osong Biche, Purandare Nilendu, Kannan Sadhana, Prabhash Kumar, Gupta Sudeep, Vanneste Ben, Rangarajan Venkatesh, Dekker Andre, Wee Leonard
Department of Radiation Oncology (Maastro), GROW School for Oncology, Maastricht University Medical Centre+, Maastricht, the Netherlands; Department of Nuclear Medicine, Tata Memorial Hospital, Mumbai, Maharashtra, India; Homi Bhabha National Institute, Mumbai, Maharashtra, India.
Department of Radiation Oncology (Maastro), GROW School for Oncology, Maastricht University Medical Centre+, Maastricht, the Netherlands; Department of Nuclear Medicine, Tata Memorial Hospital, Mumbai, Maharashtra, India; Homi Bhabha National Institute, Mumbai, Maharashtra, India.
Artif Intell Med. 2023 May;139:102549. doi: 10.1016/j.artmed.2023.102549. Epub 2023 Apr 11.
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/R] >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/R > 0.7]. These models should also be validated on external data and evaluated in prospective clinical studies.
宫颈癌是女性最常见的癌症之一，在全球女性所有癌症中的发病率约为6.5%。早期检测并根据分期进行适当治疗可提高患者的预期寿命。结果预测模型可能有助于治疗决策，但目前尚无关于宫颈癌患者预测模型的系统评价。
我们按照PRISMA指南对宫颈癌预测模型进行了系统评价。提取用于模型训练和验证的关键特征、终点指标，并对数据进行分析。入选的文章根据预测终点进行分组，即第1组：总生存期；第2组：无进展生存期；第3组：复发或远处转移；第4组：治疗反应；第5组：毒性或生活质量。我们开发了一个评分系统来评估这些稿件。根据我们的标准，根据在评分系统中获得的分数，研究分为四组：最显著研究（得分>60%）；显著研究（60%>得分>50%）；中度显著研究（50%>得分>40%）；最不显著研究（得分<40%）。对所有组分别进行荟萃分析。
首轮检索筛选出1358篇文章，最终39篇文章被选为符合纳入综述的条件。根据我们的评估标准，分别有16项、13项和10项研究被发现是最显著、显著和中度显著的。第1组、第2组、第3组、第4组和第5组的组内合并相关系数分别为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]。所有模型在终点预测方面均表现良好（预测准确性[c指数/AUC/R]>0.7）。
宫颈癌毒性、局部或远处复发及生存预测模型显示出有前景的结果，预测准确性合理[c指数/AUC/R>0.7]。这些模型还应在外部数据上进行验证，并在前瞻性临床研究中进行评估。
