key: cord-1000211-dhawpez0 authors: Morais, Samantha; Antunes, Luís; Rodrigues, Jéssica; Fontes, Filipa; Bento, Maria José; Lunet, Nuno title: The impact of the COVID‐19 pandemic on the short‐term survival of patients with cancer in Northern Portugal date: 2021-03-13 journal: Int J Cancer DOI: 10.1002/ijc.33532 sha: 24e7a6601f7cb6403dd87d7c967269703b360b20 doc_id: 1000211 cord_uid: dhawpez0 The COVID‐19 pandemic led to potential delays in diagnosis and treatment of cancer patients, which may negatively affect the prognosis of these patients. Our study aimed to quantify the impact of COVID‐19 on the short‐term survival of cancer patients by comparing a period of 4 months after the outbreak began (2 March 2020) with an equal period from 2019. All cancer cases of the esophagus, stomach, colon and rectum, pancreas, lung, skin‐melanoma, breast, cervix, and prostate, from the Portuguese Oncology Institute of Porto (IPO‐Porto) and diagnosed between 2 March and 1 July of 2019 (before COVID‐19) and 2020 (after COVID‐19) were identified. Information regarding sociodemographic, clinical and treatment characteristics were collected from the cancer registry database and clinical files. Vital status was assessed to 31 October of the respective years. Cox proportional hazards regression was used to estimate crude and propensity score‐adjusted hazards ratio (HR) and 95% confidence intervals (95% CIs) of death. During follow‐up to 31 October, there were 154 (11.8%) deaths observed before COVID‐19 and 131 (17.2%) after COVID‐19, corresponding to crude and adjusted HRs (95% CI) of 1.51 (1.20‐1.91) and 1.10 (0.86‐1.40), respectively. Significantly higher adjusted hazards of death were observed for patients with Stage III cancer (HR = 2.37; 95% CI: 1.14‐4.94) and those undergoing surgical treatment (HR = 3.97; 95% CI: 1.14‐13.77) or receiving radiotherapy (HR = 1.96; 95% CI: 1.96‐3.74), while patients who did not receive any treatment had a lower mortality hazards (HR = 0.62; 95% CI: 0.46‐0.83). The higher overall short‐term mortality observed during the COVID‐19 pandemic largely reflects the effects of the epidemic on the case‐mix of patients being diagnosed with cancer. first death was confirmed on 16 March. 2 The country entered a lockdown (State of Emergency) on 18 March 2020, which began to be lifted on 2 May 2020. 3, 4 A wide range of measures to mitigate the spread and morbidity of the virus were adopted 5 to ensure that health systems had the ability to provide high-quality, accessible and sustainable services. Most health-care settings implemented minimal services with programmed activity being canceled or suspended, and patients may have delayed routine health procedures or assessment of serious symptoms, due to fear of visiting providers that were also handling suspected COVID-19 cases. [6] [7] [8] [9] [10] [11] Globally, the World Health Organization estimated that 40% of countries reported partial or complete disruptions for cancer treatment. 12 For patients with cancer, health-care professionals have had to consider how to balance the delay in diagnosis or treatment against the risk of COVID-19. This includes mitigating the risks for significant care disruptions associated with the social distancing limits in place and managing the appropriate allocation of available health-care resources, 13 involved in the diagnosis, treatment and follow-up of patients with cancer, all of which may impact patient prognosis. [14] [15] [16] In fact, a systematic review found that even 4 week delays in cancer treatment are associated with increased mortality. 17 This highlights that cancer treatment delays are a problem, and may have been exacerbated during the COVID-19 pandemic. Most research has focused on the direct mortality caused by . Specifically, individuals with underlying health conditions, such as active cancer, have been found to be more vulnerable to complications from COVID-19, 18-20 as well as higher mortality. 18, [20] [21] [22] Additionally, some studies have estimated the number of excess deaths associated with the pandemic. In the United States of America, over 25% of excess deaths between February and September 2020 were attributable to causes of death other than COVID-19. 23 Likewise, in Portugal, between March and April 2020, an excess of 2400 to 4000 deaths were estimated, yielding an excess mortality of 3.5-to 5-fold higher than what can be explained by the official number of COVID-19 deaths reported. 24 Nevertheless, less attention has been paid to the indirect impact of the pandemic on other health conditions, such as cancer, especially considering the potential delays in diagnosis and treatment. Therefore, our study intends to quantify the impact of the COVID-19 outbreak on the short-term survival of patients diag- IPO-Porto is one of the largest cancer-dedicated hospitals in Portugal, admitting patients from all over the country, although mainly from the Northern region. 25 IPO-Porto provides care to more than 45 000 patients covering the entire cancer continuum. 26 After the rapid spread of the novel coronavirus worldwide in early 2020, 27 For the current study, cancer cases, except for skin-melanoma, who received the first cancer treatment outside IPO-Porto were excluded, and only the first primary cancer diagnosed among each patient was considered. Data from 2 March to 1 July were used to evaluate differences in mortality before and after COVID-19. Data from February were used as "negative controls" to compare mortality during periods without COVID-19 cases in Portugal. 2 Survival was defined as the time between the date of the first primary cancer diagnosis and the date of death by any cause, and was calculated using the Kaplan-Meier estimator. 31 Patients who remained without an event by the end of the study period (31 October 2019 or 2020) were censored. Cox proportional hazards regression analyses were used to compute crude and adjusted for age and stage hazard ratios (HRs) for death by any cause with the corresponding 95% confidence intervals (95% CIs), whenever the number of events was at least four. The time-scale used in the Cox regression model was survival time. Additional Cox proportional hazards regression analyses were carried out using a propensity score regression adjustment (PSRA) to estimate the effect of the COVID-19 pandemic on mortality. A logistic regression model was used to estimate propensity scores in which a cancer diagnosis before or after COVID-19 was regressed on sex, age, cancer site, stage and symptoms. This approach was taken to reduce the number of covariates into a single score to be included as an adjustment variable, for a more efficient control of confounding. Propensity scores in the two groups were graphed using a histogram to evaluate balance. The proportional hazards assumption was evaluated using Schoenfeld residuals. Stratified analyses were conducted by sex, age, residence, cancer site, stage, symptoms, referral pathway, first treatment and month of diagnosis. All analyses were performed using STATA 15 (StataCorp, College Station, TX). Results were considered statistically significant for P-values less than .05 (two-sided). The sociodemographic and clinical characteristics of the patients diagnosed with cancer before and after COVID-19 are presented in T A B L E 1 Crude and adjusted hazard ratios and 95% confidence intervals for death before and after the onset of COVID-19 (2 March to 1 July 2019, and 2 March to 1 July 2020 with follow-up to 31 October 2019 or 2020, respectively) calculated using Cox regression, according to sociodemographic characteristics T A B L E 2 Crude and adjusted hazard ratios and 95% confidence intervals for death before and after the onset of COVID-19 (2 March to 1 July 2019, and 2 March to 1 July 2020 with follow-up to 31 October 2019 or 2020, respectively) calculated using Cox regression, according to cancer characteristics and referral pathway Figure 3) , T A B L E 3 Crude and adjusted hazard ratios and 95% confidence intervals for death before and after the onset of COVID-19 (2 March to 1 July 2019, and 2 March to 1 July 2020 with follow-up to 31 October 2019 or 2020, respectively) calculated using Cox regression, according to first treatment received Figure 6 ). among both patients and health-care professionals. 28 Moreover, many medical appointments, namely cancer screening, were canceled, postponed or replaced by telehealth in many health-care settings due to the COVID-19 pandemic. 35 Additionally, patients themselves may have delayed routine health procedures or the assessment of mild symptoms, due to fear of visiting health-care providers that were also handling suspected COVID-19 cases. 37 Nevertheless, patients with well recognized symptoms will be more likely to visit health-care services, while vague cancer symptoms may be dismissed by patients. 14 In line with these observations, we also found that cases were more often symptomatic, and referred to IPO-Porto by a doctor or after an appointment at IPO-Porto, which may have led to a delayed diagnosis. Additionally, although patients were less often referred through cancer screening or from another hospital, after COVID-19 the latter had a higher mortality. The decrease in the overall mortality hazard estimates after adjusting for potential confounders that was observed in the present analysis supports the hypothesis that the pre-post pandemic differences are largely explained by changes in the characteristics of the cases being diagnosed in each period. The significant mortality hazards that persist after adjustment for various prognosis indicators may reflect residual or uncontrolled differences in the survival of patients diagnosed in the two periods. This may be due to the fact that the marked decrease in the absolute number of cancer cases is likely to translate into a larger proportion of cases with a worse prognosis in 2020, even within each apparently homogeneous stratum. To overcome this, we also used a PSRA approach to consider several variables that have been described to differ between patients diagnosed with cancer before and after COVID- 19, 32 and probably contributed for the observed differences in mortality. Nevertheless, after the inclusion of the PSRA, patients with Stage III cancer and those undergoing surgical treatment or radiotherapy were found to have a significantly higher mortality, while patients who did not receive any treatment had a lower mortality hazards. Apart from that, the available clinical information from each case does not allow us to disentangle the contribution of potential delays in access to care, which are likely to have occurred in at least a subset of the cases included here, or the contribution to the change in the case-mix of patients. Treatment disruptions and modifications have been reported as a result of the pandemic, which may have also impacted the prognosis of these patients. In Canada, over half of patients with lung cancer receiving treatment between March and May 2020 underwent at least one change in their cancer treatment plan. 38 In the United States of America, nearly half of patients with breast cancer encountered treatment delays. 39 A study using data from the Public Health England National Cancer Registration Service also found that modest delays in surgery for cancer will impact patient survival. 40 In the current study, infection, as well as more likely to present a COVID-19 phenotype characterized by more severe disease and increased risk of death, although with differences according to cancer type. 41 In our study, the number of patients who had a SARS-CoV-2 infection diagnosis was relatively small (nine confirmed), and therefore the occurrence of COVID-19 among the few patients in our cohorts could not meaningfully account for the nearly 50% higher death hazard in patients diagnosed in 2020. Furthermore, most of the deaths observed in our study were due to cancer, and there were only three deaths among the patients with a confirmed COVID-19 diagnosis. The current study compared two cohorts of patients diagnosed with cancer over a 4-month period before and after COVID-19 to evaluate the impact of the pandemic on short-term mortality. We also included a comparison between patients diagnosed in February, periods without COVID-19 cases in Portugal, 2 and this "negative control" supports the validity of our findings. We opted to exclude patients who received a first treatment outside IPO-Porto from our analyses, to ensure the completeness of data collected as well as the comparability between the two periods, since there is a usual lag between the incidence of cancer cases and their registration. Cancer cases diagnosed in 2019 and treated elsewhere are more likely to have potentially received additional care at IPO-Porto until the present than those diagnosed in 2020, and as such included in the cancer registry. We have previously analyzed two interrupted time series to compare the variation in the number of incident cancer cases diagnosed before COVID-19 and after, as well as the comparison of data from the month of February, and found that the observed decrease in the number of cancer cases after 2 March 2020 was unlikely to be due to delayed registration. 32 Additionally, the collection of data for the current study occurred between 1 May and 31 August 2020 to ensure that clinical and treatment information was as complete as possible, and vital status was obtained through manual linkage with the National Health Service database, which is continuously updated. We had few missing data overall, with the exception of cause of death, which was only used to describe the cause of death and not included in further analyses. Therefore, although the current study was implemented quickly in response to the COVID-19 pandemic, we believe that there are no significant differences in the completeness of data, or that this would affect the results of the present study in a meaningful manner. Detailed patient-level data were obtained, which allowed us to understand the impact of the COVID-19 pandemic on the short-term mortality of patients with cancer. However, uncontrolled differences in the prognosis of patients diagnosed in the two periods may contribute for some of the differences observed. To partially overcome this, we also conducted a PSRA analysis and some hazards remained statistically significant. Additionally, a more comprehensive assessment of the potential effects of the pandemic on cancer survival will require a longer follow-up, and a continued monitoring of the survival among patients diagnosed over the next months. This may include patients whose diagnosis or access to treatment may have been delayed, possibly to a different extent as the pandemic evolves. Our study includes data from a single-center located in Northern Portugal, which may impair the generalizability of our results to other settings. Nonetheless, IPO-Porto is one of the largest cancer-dedicated hospitals in Portugal, receiving patients from any part of the country, with different sociodemographic backgrounds and our study includes patients presenting a large spectrum of cancer sites. The results presented here describe the impact of the COVID-19 outbreak on the short-term mortality of patients with cancer at an oncology center in Northern Portugal. The higher overall mortality observed should be cautiously interpreted due not only to the differing case-mix of patients diagnosed with cancer during the COVID-19 pandemic, but also the impact of government, health-care services and patient responses. The first months of the COVID-19 pandemic led to changes in the timely diagnosis, treatment and follow-up of cancer cases, which will inevitably impact the prognosis of patients with cancer. Additionally, considering the backlog of cancer cases likely presenting with late, nonoperable disease needing assessment along with the expected volume of new cancer cases and the ongoing reallocation of resources, health-care systems will require a strategic prioritization of patients to mitigate deaths attributable to the COVID-19 pandemic. The authors declared no potential conflicts of interest. The data that supports the findings of this study are available from the corresponding author upon reasonable request. 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