Background

The COVID-19 pandemic has strained health system capacity worldwide due to a surge of hospital admissions, while mitigation measures have simultaneously reduced patients' access to health care, affecting the diagnosis and treatment of other diseases such as cancer. We estimated the impact of delayed diagnosis on cancer outcomes in Chile using a novel modelling approach to inform policies and planning to mitigate the forthcoming cancer-related health impacts of the pandemic in Chile.

Methods

We developed a microsimulation model of five cancers in Chile (breast, cervix, colorectal, prostate, and stomach) for which reliable data were available, which simulates cancer incidence and progression in a nationally representative virtual population, as well as stage-specific cancer detection and survival probabilities. We calibrated the model to empirical data on monthly detected cases, as well as stage at diagnosis and 5-year net survival. We accounted for the impact of COVID-19 on excess mortality and cancer detection by month during the pandemic, and projected diagnosed cancer cases and outcomes of stage at diagnosis and survival up to 2030. For comparison, we simulated a no COVID-19 scenario in which the impacts of COVID-19 on excess mortality and cancer detection were removed.

Findings

Our modelling showed a sharp decrease in the number of diagnosed cancer cases during the COVID-19 pandemic, with a large projected short-term increase in future diagnosed cases. Due to the projected backlog in diagnosis, we estimated that in 2021 there will be an extra 3198 cases (95% uncertainty interval [UI] 1356–5017) diagnosed among the five modelled cancers, an increase of nearly 14% compared with the no COVID-19 scenario, falling to a projected 10% increase in 2022 with 2674 extra cases (1318–4032) diagnosed. As a result of delayed diagnosis, we found a worse stage distribution for detected cancers in 2020–22, which is estimated to lead to 3542 excess cancer deaths (95% UI 2236–4816) in 2022–30, compared with the no COVID-19 scenario, among the five modelled cancers, most of which (3299 deaths, 2151–4431) are projected to occur before 2025.

Interpretation

In addition to a large projected surge in diagnosed cancer cases, we found that delays in diagnosis will result in worse cancer stage at presentation, leading to worse survival outcomes. These findings can help to inform surge capacity planning and highlight the importance of ensuring appropriate health system capacity levels to detect and care for the increased cancer cases in the coming years, while maintaining the timeliness and quality of cancer care. Potential delays in treatment and adverse impacts on quality of care, which were not considered in this model, are likely to contribute to even more excess deaths from cancer than projected.

Funding

Harvard TH Chan School of Public Health.

Translations

For the Spanish and Portuguese translations of the abstract see Supplementary Materials section.

中文翻译：

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估计 2020 年至 2030 年 COVID-19 大流行对智利五种癌症的诊断和生存的影响：基于模拟的分析

 背景

由于入院人数激增，COVID-19 大流行导致全球卫生系统能力紧张，而缓解措施同时减少了患者获得医疗保健的机会，影响了癌症等其他疾病的诊断和治疗。我们使用一种新颖的建模方法估计了延迟诊断对智利癌症结果的影响，为政策和规划提供信息，以减轻智利大流行即将对癌症相关的健康影响。

 方法

我们开发了智利五种癌症（乳腺癌、宫颈癌、结直肠癌、前列腺癌和胃癌）的微观模拟模型，该模型有可靠的数据，可以模拟全国代表性虚拟人群中的癌症发病率和进展，以及特定阶段的癌症检测和生存概率。我们根据每月检测到的病例、诊断分期和 5 年净生存率的经验数据对模型进行了校准。我们按月计算了大流行期间 COVID-19 对超额死亡率和癌症检出率的影响，并预测了确诊的癌症病例和诊断阶段的结果以及到 2030 年的生存率。为了进行比较，我们模拟了没有 COVID-19 的情况其中消除了 COVID-19 对超额死亡率和癌症检测的影响。

 发现

我们的模型显示，在 COVID-19 大流行期间，诊断出的癌症病例数量急剧下降，预计未来诊断病例的短期内将大幅增加。由于预计诊断积压，我们估计 2021 年，五种模型癌症中将额外诊断出 3198 例（95% 不确定性区间 [UI] 1356-5017），与无新冠病例相比增加近 14% -19 情景，预计到 2022 年将增加 10%，诊断出 2674 例额外病例 (1318-4032)。由于诊断延迟，我们发现 2020-22 年检测到的癌症的分期分布更差，与未发现新冠病毒的情况相比，预计 2022-30 年将导致 3542 例癌症死亡（95% UI 2236-4816）。 19 种情景，在五种模拟癌症中，其中大多数（3299 例死亡，2151-4431 例）预计将在 2025 年之前发生。

 解释

除了预计确诊的癌症病例将大幅增加之外，我们发现诊断延迟还会导致就诊时癌症分期更差，从而导致生存结果更差。这些发现有助于为激增的能力规划提供信息，并强调确保适当的卫生系统能力水平的重要性，以发现和护理未来几年增加的癌症病例，同时保持癌症护理的及时性和质量。该模型没有考虑潜在的治疗延误和对护理质量的不利影响，这些因素可能会导致比预期更多的癌症死亡。

 资金

哈佛大学陈曾熙公共卫生学院。

 翻译

有关摘要的西班牙语和葡萄牙语翻译，请参阅补充材料部分。