癌症被认为是COVID-19死亡率的危险因素,然而,一些国家报告说,在COVID-19大流行期间,患有主要癌症的死亡人数仍处于历史水平。这里,我们进一步阐明了美国人群中癌症死亡率与COVID-19之间的关系.我们比较了6种癌症的基础和多因(MC)死亡数据中与大流行相关的死亡率模式,糖尿病,和老年痴呆症。编码实践中与大流行相关的任何变化都应通过研究MC数据来消除。在2020年全国范围内,MC癌症死亡率仅比大流行前的基线上升了3%,相当于约13,600例超额死亡。死亡率升高在致命性较低的癌症(乳腺癌,结直肠,和血液学,2-7%)比生存率低的癌症(肺癌和胰腺癌,0-1%)。相比之下,糖尿病(37%)和阿尔茨海默病(19%)导致的MC死亡显著升高。为了理解这些差异,我们使用COVID-19发作率模拟了每种情况的预期超额死亡率,预期寿命,人口规模,以及生活在每种情况下的个体的平均年龄。我们发现,观察到的死亡率差异主要是由预期寿命的差异来解释的,与致命癌症死亡的风险超过COVID-19死亡的风险。
确定像COVID-19这样的大流行的真实死亡人数是困难的,因为实验室测试通常太有限,无法直接计算可归因于特定病原体的死亡人数。为了克服这一点,研究人员分析了超额死亡率-也就是说,他们根据前几年的趋势将观察到的死亡人数与预期水平进行了比较.这些技术已经使用了100多年来估计大流行性流感的负担,并成为估计COVID-19大流行死亡的流行方法。超额死亡率也可以揭示COVID-19对患有慢性病的亚人群的影响。例如,以前的研究表明,糖尿病死亡,被列为主要死亡原因的心脏病和阿尔茨海默氏病在COVID-19浪潮期间增加。癌症死亡没有表现出这样的模式,然而,尽管一些流行病学研究确定癌症是COVID-19死亡的危险因素。为了理解为什么会这样,汉森等人。在大流行的第一年,审查了来自美国不同州的死亡证明。他们对多原因死亡记录的分析(在死亡证明上列出癌症,不仅仅是死亡的主要原因)表明,大流行期间的死亡证明编码实践并不能解释癌症死亡率过高的原因。虽然预期寿命较长的癌症(乳腺癌,例如),预期寿命较低的癌症未观察到升高,比如胰腺癌。分析表明,特别致命的癌症缺乏超额死亡率可以通过竞争风险来解释-换句话说,死于癌症本身的高风险远远超过了COVID-19带来的额外风险。这些发现揭示了竞争性死亡风险如何掩盖COVID-19对癌症死亡率的真正影响,并解释了队列研究和超额死亡率研究之间的明显差异。为了充分理解COVID-19对癌症患者的影响,未来的研究应该着眼于大流行封锁期间晚期诊断导致癌症死亡率长期增加的可能性,和严重疾病的风险增加。
Cancer is considered a risk factor for COVID-19 mortality, yet several countries have reported that deaths with a primary code of cancer remained within historic levels during the COVID-19 pandemic. Here, we further elucidate the relationship between cancer mortality and COVID-19 on a population level in the US. We compared pandemic-related mortality patterns from underlying and multiple cause (MC) death data for six types of cancer, diabetes, and Alzheimer\'s. Any pandemic-related changes in coding practices should be eliminated by study of MC data. Nationally in 2020, MC cancer mortality rose by only 3% over a pre-pandemic baseline, corresponding to ~13,600 excess deaths. Mortality elevation was measurably higher for less deadly cancers (breast, colorectal, and hematological, 2-7%) than cancers with a poor survival rate (lung and pancreatic, 0-1%). In comparison, there was substantial elevation in MC deaths from diabetes (37%) and Alzheimer\'s (19%). To understand these differences, we simulated the expected excess mortality for each condition using COVID-19 attack rates, life expectancy, population size, and mean age of individuals living with each condition. We find that the observed mortality differences are primarily explained by differences in life expectancy, with the risk of death from deadly cancers outcompeting the risk of death from COVID-19.
Establishing the true death toll of a pandemic like COVID-19 is difficult, as laboratory testing is generally too limited to directly count the number of deaths that can be attributed to a particular pathogen. To overcome this, researchers analyse excess mortality – that is, they compare the observed number of deaths with the expected level based on trends in prior years. These techniques have been used for over 100 years to estimate the burden of pandemic influenza and became a popular way to estimate deaths due to the COVID-19 pandemic. Excess mortality can also reveal the impact of COVID-19 on sub-populations with chronic conditions. For example, previous studies showed that deaths with diabetes, heart disease and Alzheimer’s disease listed as the primary cause of death increased during waves of COVID-19. Cancer deaths did not show such a pattern, however, despite some epidemiological studies identifying cancer as a risk factor for COVID-19 mortality. To understand why this may be the case, Hansen et al. reviewed death certificates from different states in the United States during the first year of the pandemic. Their analyses of multiple-cause death records (listing cancer anywhere on the death certificate, not just as the primary cause of death) showed that death certificate coding practices during the pandemic did not explain the absence of excess cancer mortality. While a low level of excess mortality was detectable for cancers with longer life expectancy (breast cancer, for example), no elevation was observed for cancers with lower life expectancy, such as pancreatic cancer. The analyses demonstrate that the lack of excess mortality for especially deadly cancers can be explained through competing risks – in other words, the high risk of dying from the cancer itself vastly outweighs the additional risk posed by COVID-19. These findings shed light on how competing mortality risks might mask the true impact of COVID-19 on cancer mortality and explain the apparent discrepancy between cohort studies and excess mortality studies. To fully comprehend the impact of COVID-19 on patients living with cancers, future research should look at the possibility of longer-term increases in cancer mortality due to late diagnosis during pandemic lockdowns, and an elevated risk of severe illness.