Abstract：
Cancer remains a leading cause of worldwide mortality and is a growing, multifaceted global burden. As a result, cancer prevention and cancer mortality reduction are counted among the most pressing public health issues of the twenty-first century. In turn, accurate projections of cancer incidence and mortality rates are paramount for robust policymaking, aimed at creating efficient and inclusive public health systems and also for establishing a baseline to assess the impact of newly introduced public health measures. Within the European Union (EU), Romania consistently reports higher mortality from all types of cancer than the EU average, caused by an inefficient and underfinanced public health system and lower economic development that in turn have created the phenomenon of \"oncotourism\". This paper aims to develop novel cancer incidence/cancer mortality models based on historical links between incidence and mortality occurrence as reflected in official statistics and population web-search habits. Subsequently, it employs estimates of the web query index to produce forecasts of cancer incidence and mortality rates in Romania. Various statistical and machine-learning models-the autoregressive integrated moving average model (ARIMA), the Exponential Smoothing State Space Model with Box-Cox Transformation, ARMA Errors, Trend, and Seasonal Components (TBATS), and a feed-forward neural network nonlinear autoregression model, or NNAR-are estimated through automated algorithms to assess in-sample fit and out-of-sample forecasting accuracy for web-query volume data. Forecasts are produced with the overperforming model in the out-of-sample context (i.e., NNAR) and fed into the novel incidence/mortality models. Results indicate a continuation of the increasing trends in cancer incidence and mortality in Romania by 2026, with projected levels for the age-standardized total cancer incidence of 313.8 and the age-standardized mortality rate of 233.8 representing an increase of 2%, and, respectively, 3% relative to the 2019 levels. Research findings thus indicate that, under the no-change hypothesis, cancer will remain a significant burden in Romania and highlight the need and urgency to improve the status quo in the Romanian public health system.
摘要：
癌症仍然是全球死亡的主要原因，并且正在增长，多方面的全球负担。因此,预防癌症和降低癌症死亡率是21世纪最紧迫的公共卫生问题之一。反过来,癌症发病率和死亡率的准确预测对于强有力的决策至关重要，旨在建立有效和包容性的公共卫生系统，并建立基线以评估新引入的公共卫生措施的影响。在欧洲联盟(欧盟)内，罗马尼亚一直报告所有类型癌症的死亡率高于欧盟平均水平，由低效和资金不足的公共卫生系统和较低的经济发展造成的，这反过来又造成了“生态旅游”现象。本文旨在根据官方统计数据和人口网络搜索习惯反映的发病率和死亡率之间的历史联系，开发新的癌症发病率/癌症死亡率模型。随后，它使用网络查询索引的估计值来预测罗马尼亚的癌症发病率和死亡率。各种统计和机器学习模型-自回归综合移动平均模型(ARIMA)，基于Box-Cox变换的指数平滑状态空间模型,ARMA错误,趋势,和季节性成分(TBATS)，和前馈神经网络非线性自回归模型，或NNAR-通过自动算法进行估计，以评估网络查询量数据的样本内拟合和样本外预测准确性。预测是在样本外背景下使用表现优异的模型(即，NNAR)并纳入新的发病率/死亡率模型。结果表明，到2026年，罗马尼亚的癌症发病率和死亡率继续呈上升趋势，预计年龄标准化的癌症总发病率为313.8，年龄标准化的死亡率为233.8，增加了2%。and,分别,相对于2019年的水平，3%。因此，研究结果表明，在不变假设下，在罗马尼亚，癌症仍将是一个巨大的负担，并强调了改善罗马尼亚公共卫生系统现状的必要性和紧迫性。
