Next Article in Journal
Gastro-Intestinal Symptoms in Palliative Care Patients
Previous Article in Journal
Antibody–Drug Conjugates in the Treatment of Genitourinary Cancers: An Updated Review of Data
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Current Oncology
Volume 31
Issue 4
10.3390/curroncol31040173
curroncol-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Impact of the Pandemic on the Quality of Colorectal and Anal Cancer Care, and 2-Year Clinical Outcomes

by
Melanie Powis
1,2,*,
Rinku Sutradhar
1,3,
Simron Singh
1,4,5,
Shabbir Alibhai
1,5,6,
Saidah Hack
2,
Abed Baiad
7,
Kevin Chen
5,
Huaqi Li
5,
Zuhal Mohmand
5 and
Monika K. Krzyzanowska
1,2,3,5,6
1
Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, ON M5S 1A1, Canada
2
Cancer Quality Laboratory (CQuaL), Princess Margaret Cancer Centre, Toronto, ON M5G 1X6, Canada
3
Institute for Clinical Evaluative Sciences (ICES), Toronto, ON M4N 3M5, Canada
4
Division of Medical Oncology and Hematology, Sunnybrook Health Sciences Centre, Toronto, ON M4N 3M5, Canada
5
Department of Medicine, University of Toronto, Toronto, ON M5S 1A1, Canada
6
Department of Medicine, University Health Network, Toronto, ON M5G 2C4, Canada
7
Department of Medicine, McGill University, Montreal, QC H3A 0G4, Canada
*
Author to whom correspondence should be addressed.
Curr. Oncol. 2024, 31(4), 2328-2340; https://doi.org/10.3390/curroncol31040173
Submission received: 27 February 2024 / Revised: 11 April 2024 / Accepted: 17 April 2024 / Published: 19 April 2024
(This article belongs to the Section Gastrointestinal Oncology)
Browse Figures
Review Reports Versions Notes

Abstract

:
We undertook a retrospective study to compare the quality of care delivered to a cohort of newly diagnosed adults with colon, rectal or anal cancer during the early phase of COVID-19 (02/20–12/20) relative to the same period in the year prior (the comparator cohort), and examine the impact of the pandemic on 2-year disease progression and all-cause mortality. We observed poorer performance on a number of quality measures, such as approximately three times as many patients in the COVID-19 cohort experienced 30-day post-surgical readmission (10.5% vs. 3.6%; SD:0.27). Despite these differences, we observed no statistically significant adjusted associations between COVID-19 and time to either all-cause mortality (HR: 0.88, 95% CI: 0.61–1.27, p = 0.50) or disease progression (HR: 1.16, 95% CI: 0.82–1.64, p = 0.41). However, there was a substantial reduction in new patient consults during the early phase of COVID-19 (12.2% decrease), which appeared to disproportionally impact patients who traditionally experience sociodemographic disparities in access to care, given that the COVID-19 cohort skewed younger and there were fewer patients from neighborhoods with the highest Housing and Dwelling, ands Age and Labour Force marginalization quintiles. Future work is needed to understand the more downstream effects of COVID-19 related changes on cancer care to inform planning for future disruptions in care.

1. Introduction

In response to the Coronavirus Disease 2019 (COVID-19) pandemic, cancer care delivery was modified globally in order to reduce strain on healthcare resources and mitigate the risk of spread [1]. Reported changes varied by jurisdiction and included reducing surgical caseloads, delaying and deferring treatments [2], the use of oral over intravenous therapies and undertaking virtual rather than in-person visits [3,4,5,6,7]. In colorectal cancer, the suspension of routine screening has been linked to delays in diagnosis and treatment, with a greater proportion of patients presenting in the emergency department [8]. In England during the early phase of the pandemic, a 63% reduction in referrals, a 92% reduction in colonoscopies, 3500 fewer colorectal cancer diagnoses and a 31% relative reduction in the number of surgeries relative to the year prior were reported [9].
As many aspects of cancer care cannot be deferred without impacting downstream clinical outcomes, this presents challenges moving forward. Following Hurricane Katrina-related disruptions to cancer care in 2005, 10-year mortality was found to be higher amongst survivors diagnosed with colon cancer within six months of the hurricane than case-matched controls from other jurisdictions during the same time period [10]. While it is still too early to examine the impact of the COVID-19 pandemic on longer-term clinical outcomes, a recent study examining outcomes of a cohort of patients diagnosed in 04–06/2020 found that, after adjusting for age, sex, rural residence and stage, patients diagnosed with colorectal cancer during the early phase of the pandemic had an approximately 20% higher risk of mortality (HR: 1.21; 95% CI: 1.05–1.40) than those diagnosed in 2018 [11]. Understanding the complex inter-play between treatment modifications and their implications for overall clinical outcomes is necessary as we emerge from the pandemic, though the majority of the articles published to date have focused on patterns of cancer care [12], while few have examined impacts on the quality of care, which may result in the worsening of clinical outcomes.
We undertook a retrospective, comparative cohort study to examine the impact of the COVID-19 pandemic on the quality of cancer care delivered to patients newly diagnosed with colon, rectal or anal cancer, as well as clinical outcomes (all-cause death and disease progression). The pandemic may have exacerbated existing disparities in access to timely care and colorectal cancer screening, particularly for patients from racialized groups [13], older adults with cancer and those residing in lower income neighbourhoods [14]. As such, we examined associations between patient-level demographic and clinical characteristics and established an overall quality score between the COVID-19 and comparator cohorts.

2. Methods

2.1. Study Overview and Ethics

This study was undertaken at the Princess Margaret Cancer Centre (PM), a large, urban comprehensive cancer centre in Toronto, Canada in a single-payer, universal healthcare system. Approval was received from the University Health Network (#20-5428) and University of Toronto (#00041187) Research Ethics Boards; individual consent was waived, as data were retrospective and the re-identification risk was low. This study’s findings were reported in accordance with the STROBE guidelines.

2.2. Cohort Identification

The cohort was identified from the PM Cancer Registry and consisted of all patients ≥18 years of age, whose first PM consultation for newly diagnosed colon, rectal or anal cancer was between 1 February 2019 and 31 December 2019 (comparator cohort) or 1 February 2020 and 31 December 2020 (COVID-19 cohort). Patients were excluded from the study if they had benign disease. Patients who were undergoing treatment for two synchronous cancers (e.g., prostate and colon cancer) were also excluded, since this would have impacted the trajectory of their disease and choice of treatment, which reduces comparability to standard clinical cases.

2.3. Data Collection

Data were manually abstracted by a team of five trained medical student abstractors into a secure, encrypted Research Electronic Data Capture database (REDCap) hosted at the University Health Network [15,16]. For quality measure evaluation, data were collected for encounters and treatments in the 6 months following the patient’s first consultation at PM. Disease progression was defined as initiating a new treatment regimen, or having a clinical note or imaging scan report identifying new disease. Data on disease progression and mortality were abstracted for the two years following the date of diagnosis.

2.4. Data Linkage

Since limited sociodemographic factors are captured in a patient’s chart, data were linked by full postal code to the Canadian 2016 Census data using the Postal Code Conversion File and Census Analyzer Tool [17] to obtain rural vs. urban residence and neighbourhood gross income quintiles. Additionally, data were linked to the Ontario Marginalization Index to obtain neighbourhood quintiles for each of the four composite measures of marginalization derived from dissemination area-level Census data [18]. Households and Dwellings (previously called Residential Instability) is a composite measure of family and housing instability based on the type and density of housing and family characteristics, such as what proportion of the population is living alone and what proportion of the dwellings are rented vs. owned. Material Resources, previously called Material Deprivation, is a composite measure of poverty, based on income, housing quality, education and family structure, which includes measures such as the proportion of the population without a high school diploma and the unemployment rate. The Age and Labour Force, previously called Dependency, is a composite measure of the proportion of residents without employment income, including those receiving disability benefits and the proportion of residents who are seniors or children. Racialized and Newcomer Populations, formerly called Ethnic Concentration, is a composite measure of the proportion of residents who are recent immigrants, as well as those who self-report belonging to a Racialized Group.

2.5. Quality Measures

Quality measures were identified based on a prior scoping literature review highlighting pandemic-related changes to cancer care [1]. These cancer care changes were mapped to 16 established quality measures that are routinely evaluated in colorectal cancer and represent the best practice (Supplementary File S1) [19,20,21,22]. Eight additional, novel “pandemic-specific measures” were operationalized to capture pandemic-related changes that have been reported in the literature [1] that do not necessarily represent preferred or best-practice care, such as the use of oral vs. IV therapies, or the use of laparoscopy rather than open surgical resection.

2.6. Statistical Analysis

All analyses were carried out in R (version 4.1.2, R Foundation for Statistical Computing; Vienna, Austria). We compared demographic and clinical characteristics of the two cohorts using standardized differences (SDs) rather than p-value since the sample size was small and SDs are not directly dependent on sample size, and this allowed us to compare the size of differences between the two cohorts [23,24,25]. Performance on individual quality measures was calculated for each cohort as the proportion of patients meeting the indicator definition (numerator) out of those who were eligible (denominator), and these were compared using SD. SD > 0.1 was considered indicative of a meaningful difference [26,27].
To examine patient-level differences in the overall quality of care, an overall quality score was generated for each patient as a count of the number of process quality measures for which a patient received measure-concordant care out of those they were eligible for; measures were equally weighted. Univariate Poisson regression models were utilized to examine potential unadjusted associations between patient-level sociodemographic and clinical characteristics and overall quality score by cohort, with the natural logarithm of the number of measures they were eligible for as an offset (range: 5–14 measures); p-values ≤ 0.05 were considered statistically significant.
Plots of cumulative incidence for each outcome (x-axis) by to days since diagnosis (y-axis) were generated and stratified into COVID-19 and comparator groups. Incidence was estimated at two years post-diagnosis and compared using the log-rank and Gray’s tests as appropriate, whereby p < 0.05 was considered significant. Associations between being in the COVID-19 group (vs. the comparator) and time to death, as well as time to progression, with death as a competing risk, were examined using multivariable Cox Proportional Hazards and Fine-Gray regression models, respectively, and these were adjusted for age, disease stage and primary; p < 0.05 was considered significant.

3. Results

3.1. Cohort Description

Relative to the same period in the year prior, there was a 12.2% reduction in new consults during the early phase of the COVID-19 pandemic (COVID-19: 294 patients, comparator: 335; Figure 1). Relative to the comparator, patients in the COVID-19 cohort were younger (mean age: 66.1 vs. 67.5 years; SD: 0.135), and fewer patients resided in neighbourhoods in the highest marginalization quintile of the Household and Dwellings (41.5% vs. 44.8%; SD: 0.113) and Age and Labour Force (15.6% vs. 23.9%; SD: 0.214) categories, or highest socioeconomic status (21.8% vs. 23.6%; SD: 0.117; Table 1). Additionally, fewer patients were treated with surgery during COVID-19 (41.8% vs. 48.7%; SD: 0.143) compared with the year prior.

3.2. Changes to Cancer Care Delivery during COVID-19

A greater proportion in the COVID-19 cohort received treatment with short-course radiotherapy (25 Gy in 5 fractions) for rectal cancer compared to the same period in the year prior (32.6% vs. 11.1%; SD: 0.54; Table 2). Relative to the same period in the year prior, greater proportions of patients in the COVID-19 cohort experienced an interruption in their systemic therapy or radiotherapy (32.4% vs. 22.3%; SD: 0.23) or had their radiotherapy treatment prematurely discontinued (9.4% vs. 1.1%; SD: 0.38). No significant differences were observed in the proportions of patients being treated with oral or single-agent systemic therapy, having the initiation of their treatment deferred or participating in an interventional clinical trial (SD: 0.01–0.09).

3.3. Quality Measure Performance

Relative to the year prior, fewer colon cancer patients (82.4% vs. 90.9%; SD: 0.25; Table 2) and anal cancer patients (65.5% vs. 88.0%; SD: 0.55) received the appropriate oncologist consultations. Fewer patients with rectal (24.7% vs. 33.3%; SD: 0.19) and anal cancers (61.5% vs. 85.7%; SD: 0.57) received the appropriate treatment during COVID-19 compared to the year prior. In the 30 days following surgery, there were three times as many patients with all-cause readmission in the COVID-19 cohort compared to the same period in the year prior (10.5% vs. 3.6%; SD: 0.27). For patients whose first consultation was with a medical oncologist or radiation oncologist, a greater proportion in the COVID-19 cohort received a consultation with their oncologist within two weeks of referral than in the comparator cohort (84.9% vs. 72.4%; SD: 0.31). For patients treated with systemic therapy, the proportion who experienced death within 30 days of treatment was significantly lower in the COVID-19 cohort than in the comparator (1.0% vs. 13.8%; SD: 0.51). A greater proportion of patients were diagnosed with cancer in the emergency department during COVID-19 than in the year prior (30.3% vs. 27.8%; SD: 0.19). Additionally, fewer patients in the COVID-19 cohort had a pathology report in their medical record that confirmed disease (68.0% vs. 74.6%; SD: 0.20).
The mean overall quality performance was lower in the COVID-19 cohort than the comparator (mean proportion (standard deviation): 57.1% (18.7) vs. 60.8% (17.8); SD: 0.20). Relative to patients presenting with stage I disease at diagnosis, patients with stage IV disease had approximately 25% lower overall quality scores in both cohorts (COVID-19-IRR: 0.74, 95% CI: 0.64–0.87; comparator- IRR: 0.76, 95% CI: 0.66–0.88; Supplementary File S2).

3.4. All-Cause Mortality and Disease Progression

Incidence of 2-year mortality (COVID-19: 22.0% [95% CI: 16.6–27], comparator: 24.0% [95% CI: 18.8–28.9]; p = 0.70) and disease progression were similar in both groups (COVID-19: 27.1% [95% CI: 22.0–33.0], comparator: 21% [95% CI: 16.2–26.0], p = 0.20; Figure 2). When adjusted for age, stage and primary, there was no statistically significant association found between being in the COVID-19 group and time to either all-cause death (HR: 0.88, 95% CI: 0.61–1.27, p = 0.50) or disease progression (HR: 1.16, 95% CI: 0.82–1.64, p = 0.41; Table 3).

4. Discussion

Despite numerous existing quality measures, the literature examining the impact of the pandemic on the quality of cancer care to date has been limited, with the majority of articles focused on the provision of a single modality of treatment, such as surgery or radiotherapy [22,28], or on a specific concept of quality care such as the timeliness of care [29] or patient experience [30]. However, cancer treatment is often multi-modal, and in many jurisdictions, care delivery shifted rather than being altogether cancelled; therefore, a view of the “bigger picture” is needed to truly understand potential downstream implications for patients’ treatment trajectories and prognoses. Relative to the same period in the year prior, we found that there were some differences in quality measure performance for patients treated for colon, rectal or anal cancer during the early phase of COVID-19, though not a profound disruption in care, as was predicted at the onset of the pandemic [31].
Similar to other jurisdictions [32], we found that fewer patients received surgery (41.8% vs. 48.7%; SD: 0.143); however, this decrease was much smaller than in other countries, such as Germany [33], Portugal [34], New Zealand [35] or Australia [36], where 14.5–66% reductions in colorectal surgery have been reported. However, these studies either reported on physician survey data, which may be biased by perceptions surrounding the magnitude of changes in surgical volumes, or their analysis approach was different in that they counted procedures completed relative to the year prior rather than the proportion of patients seen who had had surgery.
We found that there was a greater proportion of patients during COVID-19 who experienced treatment interruption (32.4% vs. 22.3%; SD: 0.23), although this difference was smaller than in other jurisdictions (23.4–70%) [37,38,39]. Similarly, we observed an increase in the proportion of patients treated with short-course radiation for rectal cancer during COVID-19 (32.6% vs. 11.1%; SD: 0.54), which is consistent with the literature [32], although this increase was, again, less pronounced [40]. In contrast with the published literature [1,32], we did not observe differences in the proportions of patients being treated with oral or single-agent therapy, having their treatment start deferred or participating in a clinical trial, although there were few available in this context at the time of study (SD: 0.01–0.09). These findings likely reflect the prioritization of non-elective cancer surgeries in our jurisdiction [41] and lower the overall burden of COVID-19 relative to other countries, resulting in fewer issues with the availability of and access to care [42]. Interestingly, we did observe a decrease in the proportion of patients who died within 30 days of systemic therapy treatment during COVID-19 (1.0% vs. 13.8%; SD: 0.51). This may reflect a change in prescribing behavior to avoid low-value care, may reflect treatments that are less likely to have a clinically meaningful effect [43] or may reflect patient preference.
There are several limitations; this study was carried out at a single, urban cancer centre in a large metropolitan area within a universal healthcare system, which may impact the generalizability of the findings to other jurisdictions and healthcare systems. The comparator was chosen to ensure the feasibility of completion of the manual chart abstraction of the data, to minimize the influence of changes in reorganization of care at the institution or changes in standards of treatment and to allow for appropriate follow-up. The proportion of patients with a pathology report in their medical chart pathologically confirming disease prior to the initiation of treatment was low both during COVID-19 (68.0%) and prior to it (74.6%); however, some records from outside institutions are not uploaded in the chart but, instead, are accessed through a central repository (Connecting Ontario), where access for research purposes is restricted. As such, we may undercount the actual proportion of patients with pathologically confirmed disease. We focused on the quality of cancer care delivered in the six months following the first consultation at PM; therefore, the overlap of care for patients seen as new patient consultations at the end of 2019 and the beginning of the pandemic may have biased our findings towards showing fewer meaningful differences, although very few COVID-19-related changes to care have been reported in patients who initiated treatment prior to the onset of the pandemic [44]. Additionally, we were unable to collect data on patient decision making during COVID-19 as part of this study, which may have influenced the observed differences in patterns of care.
We found a small difference in the mean overall quality score of cancer care delivered during the pandemic relative to the comparator (mean proportion [standard deviation]: 57.1% [18.7] vs. 60.8% [17.8]; SD: 0.20). While COVID-19 has been shown to have compounded existing sociodemographic disparities in cancer care, whereby being of older age [15], from a Racialized Group [13,45,46], or residing in a lower income neighbourhood [14] has been associated with poorer access to screening and treatment, we found no association between patient-level demographic or clinical characteristics and the overall quality score. However, we saw small differences in the sociodemographic characteristics of patients seen during the early phase of COVID-19, whereby they were younger and less likely to be from neighborhoods with the highest Housing and Dwelling, and Age and Labour Force marginalization rates; therefore, patients experiencing the most issues with access to care might have had their care deferred. At 2 years post-diagnosis, we did not observe significant adjusted associations between the pandemic and time to either all-cause mortality (HR: 0.88, 95% CI: 0.61–1.27, p = 0.50) or disease progression (HR: 1.16, 95% CI: 0.82–1.64, p = 0.41). However, there were relatively few incidences of death and disease progression in our cohorts, resulting in the instability of the estimates. In spite of this, delays in receipt of cancer treatment following the onset of symptoms is associated with poorer prognosis [47]. As such, future work should revisit the impact of the pandemic on the quality of care and clinical outcomes, with a special focus on sociodemographic disparities in the provision of quality care once more time has elapsed.

5. Conclusions

While there were some differences in quality measure performance during the early phase of the pandemic, this does not appear to have translated into poorer outcomes after 2 years. However, the reduction in the number of new patients relative to the year prior likely reflects delays and deferrals in the screening and diagnosis of new cancers; therefore, impacts on prognosis may be more latent. As findings following Hurricane Katrina demonstrated that deferred and delayed cancer screening and treatment resulted in an increased 10-year mortality risk [10], our analysis should be repeated once more time (and more events) have elapsed.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/curroncol31040173/s1, Supplementary File S1. Quality Measure Definitions. Supplementary File S2. Evaluating potential associations between patient-level sociodemographic and clinical characteristics, and overall quality sore by Poisson regression with score as a count, and the number of measures the patient was eligible for as an offset.

Author Contributions

The authors confirm contributions to the paper as follows: study conceptualization: M.P., R.S., S.S., S.A. and M.K.K.; methodology: M.P. and R.S.; data curation: M.P., S.H., A.B., K.C., H.L. and Z.M.; formal analysis: M.P., R.S., S.S., S.A., S.H. and M.K.K.; writing—original draft preparation: M.P. and M.K.K.; writing—review and editing: all authors. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the Princess Margaret Cancer Centre Foundation and a grant from the Canadian Institute for Health Research (Grant #: 154129).

Institutional Review Board Statement

Approval was received from the University Health Network (#20-5428) and University of Toronto (#00041187) Research Ethics Boards; individual consent was waived.

Informed Consent Statement

Patient consent was waived, as the study was retrospective in nature and the sample size was sufficient enough that the potential re-identification risk was very low.

Data Availability Statement

De-identified data are available upon reasonable, non-commercial request by email to the corresponding author upon execution of a data transfer agreement.

Acknowledgments

The authors would like to acknowledge the contributions of Peter Nakhla in abstracting chart data. This work was presented as a poster at the October 2023 American Society of Clinical Oncology (ASCO) Quality Care Symposium in Boston, MA, USA (October 2023).

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Powis, M.; Milley-Daigle, C.; Hack, S.; Alibhai, S.; Singh, S.; Krzyzanowska, M.K. Impact of the early phase of the COVID pandemic on cancer treatment delivery and the quality of cancer care: A scoping review and conceptual model. Int. J. Qual. Health Care 2021, 33, mzab088. [Google Scholar] [CrossRef] [PubMed]
  2. Walker, M.J.; Wang, J.; Mazuryk, J.; Skinner, S.M.; Meggetto, O.; Ashu, E.; Habbous, S.; Rad, N.N.; Espino-Hernández, G.; Wood, R.; et al. Delivery of Cancer Care in Ontario, Canada, During the First Year of the COVID-19 Pandemic. JAMA Netw Open. 2022, 5, e228855. [Google Scholar] [CrossRef] [PubMed]
  3. Jazieh, A.R.; Akbulut, H.; Curigliano, G.; Rogado, A.; Alsharm, A.A.; Razis, E.D.; Mula-Hussain, L.; Errihani, H.; Khattak, A.; De Guzman, R.B.; et al. Impact of the COVID-19 Pandemic on Cancer Care: A Global Collaborative Study. JCO Glob. Oncol. 2020, 6, 1428–1438. [Google Scholar] [CrossRef] [PubMed]
  4. Tartarone, A.; Lerose, R. COVID-19 and cancer care: What do international guidelines say? Med. Oncol. 2020, 37, 80. [Google Scholar] [CrossRef] [PubMed]
  5. Ueda, M.; Martins, R.; Hendrie, P.C.; McDonnell, T.; Crews, J.R.; Wong, T.L.; McCreery, B.; Jagels, B.; Crane, A.; Byrd, D.R.; et al. Managing Cancer Care During the COVID-19 Pandemic: Agility and Collaboration Toward a Common Goal. J. Natl. Compr. Cancer Netw. 2020, 18, 366–369. [Google Scholar] [CrossRef] [PubMed]
  6. Curigliano, G. The Treatment of Patients With Cancer and Containment of COVID-19: Experiences From Italy. Available online: https://dailynews.ascopubs.org/do/10.1200/ADN.20.200068/full/ (accessed on 14 July 2023).
  7. You, B.; Ravaud, A.; Canivet, A.; Ganem, G.; Giraud, P.; Guimbaud, R.; Kaluzinski, L.; Krakowski, I.; Mayeur, D.; Grellety, T.; et al. The official French guidelines to protect patients with cancer against SARS-CoV-2 infection. Lancet Oncol. 2020, 21, 619–621. [Google Scholar] [CrossRef] [PubMed]
  8. Suárez, J.; Mata, E.; Guerra, A.; Jiménez, G.; Montes, M.; Arias, F.; Ciga, M.A.; Ursúa, E.; Ederra, M.; Arín, B.; et al. Impact of the COVID-19 pandemic during Spain’s state of emergency on the diagnosis of colorectal cancer. J. Surg Oncol. 2021, 123, 32–36. [Google Scholar] [CrossRef] [PubMed]
  9. Morris, E.J.A.; Goldacre, R.; Spata, E.; Mafham, M.; Finan, P.J.; Shelton, J.; Richards, M.; Spencer, K.; Emberson, J.; Hollings, S.; et al. Impact of the COVID-19 pandemic on the detection and management of colorectal cancer in England: A population-based study. Lancet Gastroenterol. Hepatol. 2021, 6, 199–208. [Google Scholar] [CrossRef] [PubMed]
  10. Bell, S.A.; Banerjee, M.; Griggs, J.J.; Iwashyna, T.J.; Davis, M.A. The Effect of Exposure to Disaster on Cancer Survival. J. Gen. Intern. Med. 2020, 35, 380–382. [Google Scholar] [CrossRef]
  11. Heer, E.; Ruan, Y.; Boyne, D.J.; Jarada, T.N.; Heng, D.; Henning, J.-W.; Morris, D.M.; O’sullivan, D.E.; Cheung, W.Y.; Brenner, D.R. Impact of the COVID-19 pandemic on cancer diagnoses, stage and survival in Alberta. Can. Med. Assoc. J. 2023, 195, E804–E812. [Google Scholar] [CrossRef]
  12. Carvalho, A.S.; Fernandes, B.; de Lange, M.; Lingsma, H.; Klazinga, N.; Kringos, D. Changes in the quality of cancer care as assessed through performance indicators during the first wave of the COVID-19 pandemic in 2020: A scoping review. BMC Health Serv. Res. 2022, 22, 786. [Google Scholar] [CrossRef] [PubMed]
  13. Patel, M.I.; Ferguson, J.M.; Castro, E.; Pereira-Estremera, C.D.; Armaiz-Peña, G.N.; Duron, Y.; Hlubocky, F.; Infantado, A.; Nuqui, B.; Julian, D.; et al. Racial and Ethnic Disparities in Cancer Care During the COVID-19 Pandemic. JAMA Netw. Open 2022, 5, e2222009. [Google Scholar] [CrossRef] [PubMed]
  14. Walker, M.J.; Meggetto, O.; Gao, J.; Espino-Hernández, G.; Jembere, N.; Bravo, C.A.; Rey, M.; Aslam, U.; Sheppard, A.J.; Lofters, A.K.; et al. Measuring the impact of the COVID-19 pandemic on organized cancer screening and diagnostic follow-up care in Ontario, Canada: A provincial, population-based study. Prev. Med. 2021, 151, 106586. [Google Scholar] [CrossRef] [PubMed]
  15. Harris, P.A.; Taylor, R.; Thielke, R.; Payne, J.; Gonzalez, N.; Conde, J.G. Research electronic data capture (REDCap)—A metadata-driven methodology and workflow process for providing translational research informatics support. J. Biomed. Inform. 2009, 42, 377–381. [Google Scholar] [CrossRef] [PubMed]
  16. Harris, P.A.; Taylor, R.; Minor, B.L.; Elliott, V.; Fernandez, M.; O’Neal, L.; McLeod, L.; Delacqua, G.; Delacqua, F.; Kirby, J.; et al. The REDCap consortium: Building an international community of software platform partners. J. Biomed. Inform. 2019, 95, 103208. [Google Scholar] [CrossRef]
  17. University of Toronto Libraries. Map and Data Library. Postal Code Conversion Files+. Available online: https://mdl.library.utoronto.ca/collections/numeric-data/census-canada/postal-code-conversion-file (accessed on 1 January 2022).
  18. Ontario Agency for Health Protection and Promotion (Public Health Ontario). 2011 Ontario Marginalization Index: User Guide. Available online: https://www.publichealthontario.ca/-/media/documents/O/2017/on-marg-user-2011.pdf (accessed on 1 November 2022).
  19. American Society for Clinical Oncology. Quality Oncology Practice Initiative. Available online: https://society.asco.org/practice-patients/quality-improvement/quality-programs/qopi/related-measures (accessed on 17 March 2023).
  20. Patwardhan, M.; Fisher, D.A.; Mantyh, C.R.; McCrory, D.C.; Morse, M.A.; Prosnitz, R.G.; Cline, K.; Samsa, G.P. Assessing the quality of colorectal cancer care: Do we have appropriate quality measures? (A systematic review of literature). J. Eval. Clin. Pr. 2007, 13, 831–845. [Google Scholar] [CrossRef] [PubMed]
  21. Keikes, L.; Koopman, M.; Tanis, P.J.; Lemmens, V.E.; Punt, C.J.; van Oijen, M.G. Evaluating the scientific basis of quality indicators in colorectal cancer care: A systematic review. Eur. J. Cancer 2017, 86, 166–177. [Google Scholar] [CrossRef] [PubMed]
  22. COVIDSurg Collaborative. The impact of surgical delay on resectability of colorectal cancer: An international prospective cohort study. Color. Dis. 2022, 24, 708–726. [Google Scholar] [CrossRef] [PubMed]
  23. Austin, P.C. Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples. Stat. Med. 2009, 28, 3083–3107. [Google Scholar] [CrossRef]
  24. Austin, P.C. Using the Standardized Difference to Compare the Prevalence of a Binary Variable Between Two Groups in Ob-servational Research. Commun. Stat.-Simul. Comput. 2009, 38, 1228–1234. [Google Scholar] [CrossRef]
  25. Mamdani, M.; Sykora, K.; Li, P.; Normand, S.L.; Streiner, D.L.; Austin, P.C.; Rochon, P.A.; Anderson, G.M. Reader’s guide to critical appraisal of cohort studies: 2. Assessing potential for confounding. BMJ 2005, 330, 960–962. [Google Scholar] [CrossRef] [PubMed]
  26. Normand, S.L.T.; Landrum, M.B.; Guadagnoli, E.; Ayanian, J.Z.; Ryan, T.J.; Cleary, P.D.; McNeil, B.J. Validating recommendations for coronary angiography following acute myocardial infarction in the elderly: A matched analysis using propensity scores. J. Clin. Epidemiol. 2001, 54, 387–398. [Google Scholar] [CrossRef] [PubMed]
  27. Cohen, J. Statistical Power Analysis for the Behavioural Sciences; Academic Press: Hillsdale, NJ, USA, 1988. [Google Scholar]
  28. Brower, J.V.; Rhodes, S.S.; Remick, J.S.; Russo, A.L.; Dunn, E.F.; Ayala-Peacock, D.N.; Petereit, D.G.; Bradley, K.A.; Taunk, N.K. Effect of COVID-19 on Gynecologic Oncology Care: A Survey of Practicing Gynecologic Radiation Oncologists in the United States. Adv. Radiat. Oncol. 2023, 8, 101188. [Google Scholar] [CrossRef] [PubMed]
  29. Patt, D.; Gordan, L.; Diaz, M.; Okon, T.; Grady, L.; Harmison, M.; Markward, N.; Sullivan, M.; Peng, J.; Zhou, A. Impact of COVID-19 on Cancer Care: How the Pandemic Is Delaying Cancer Diagnosis and Treatment for American Seniors. JCO Clin. Cancer Inform. 2020, 4, 1059–1071. [Google Scholar] [CrossRef] [PubMed]
  30. Treiman, K.; Kranzler, E.C.; Moultrie, R.; Arena, L.; Mack, N.; Fortune, E.; Garcia, R.; Street, R.L. Patients’ Experiences with Cancer Care: Impact of the COVID-19 Pandemic. J. Patient Exp. 2022, 9, 23743735221092567. [Google Scholar] [CrossRef] [PubMed]
  31. Richards, M.; Anderson, M.; Carter, P.; Ebert, B.L.; Mossialos, E. The impact of the COVID-19 pandemic on cancer care. Nat. Rev. Cancer 2020, 1, 565–567. [Google Scholar] [CrossRef] [PubMed]
  32. Mazidimoradi, A.; Hadavandsiri, F.; Momenimovahed, Z.; Salehiniya, H. Impact of the COVID-19 Pandemic on Colorectal Cancer Diagnosis and Treatment: A Systematic Review. J. Gastrointest. Cancer 2023, 54, 171–187. [Google Scholar] [CrossRef] [PubMed]
  33. Brunner, M.; Krautz, C.; Kersting, S.; Weber, G.F.; Stinner, B.; Benz, S.R.; Grützmann, R. Oncological colorectal surgery during the COVID-19 pandemic—A national survey. Br. J. Surg. 2020, 35, 2219–2225. [Google Scholar] [CrossRef]
  34. Brito, M.; Laranjo, A.; Sabino, J.; Oliveira, C.; Mocanu, I.; Fonseca, J. Digestive Oncology in the COVID-19 Pandemic Era. GE-Port. J. Gastroenterol. 2021, 28, 303–310. [Google Scholar] [CrossRef]
  35. Gurney, J.K.; Millar, E.; Dunn, A.; Pirie, R.; Mako, M.; Manderson, J.; Hardie, C.; Jackson, C.G.; North, R.; Ruka, M.; et al. The impact of the COVID-19 pandemic on cancer diagnosis and service access in New Zealand–a country pursuing COVID-19 elimination. Lancet Reg. Health-West. Pac. 2021, 10, 100127. [Google Scholar] [CrossRef]
  36. Lechner, D.; Tschann, P.; Girotti, P.C.N.; Königsrainer, I. Impact of the COVID-19 pandemic on a visceral surgical department in western Austria. Eur. Surg. 2020, 53, 43–47. [Google Scholar] [CrossRef]
  37. Koczkodaj, P.; Sulkowska, U.; Kamiński, M.F.; Didkowska, J. SARS-CoV-2 as a new possible long-lasting determining factor im-pacting cancer death numbers. Based on the example of breast, colorectal and cervical cancer in Poland. Nowotwory 2021, 71, 42–46. [Google Scholar] [CrossRef]
  38. Santoro, G.A.; Grossi, U.; Murad-Regadas, S.; Nunoo-Mensah, J.W.; Mellgren, A.; Di Tanna, G.L.; Gallo, G.; Tsang, C.; Wexner, S.D. DElayed COloRectal cancer care during COVID-19 Pandemic (DECOR-19): Global perspective from an international survey. Surgery 2020, 169, 796–807. [Google Scholar] [CrossRef] [PubMed]
  39. Kamposioras, K.; Saunders, M.; Lim, K.H.J.; Marti, K.; Anderson, D.; Cutting, M.; McCool, D.; Connell, J.; Simpson, L.; Hasan, J.; et al. The Impact of Changes in Service Delivery in Patients With Colorectal Cancer During the Initial Phase of the COVID-19 Pandemic. Clin. Color. Cancer 2020, 20, e120–e128. [Google Scholar] [CrossRef]
  40. Raj Kumar, B.; Pandey, D. An observational study of the demographic and treatment changes in a tertiary colorectal cancer center during the COVID-19 pandemic. J. Surg. Oncol. 2020, 122, 1271–1275. [Google Scholar] [CrossRef]
  41. Fu, R.; Sutradhar, R.; Li, Q.; Hanna, T.P.; Chan, K.K.W.; Irish, J.C.; Coburn, N.; Hallet, J.; Dare, A.; Singh, S.; et al. Timeliness and Modality of Treatment for New Cancer Diagnoses During the COVID-19 Pan-demic in Canada. JAMA Netw. Open. 2023, 6, e2250394. [Google Scholar] [CrossRef] [PubMed]
  42. World Health Organization. Statement on the Second Meeting of the International Health Regulations (2005) Emergency Committee Regarding the Outbreak of Novel Coronavirus (2019-nCoV); World Health Organization: Geneva, Switzerland, 2020; Available online: https://covid19.who.int/ (accessed on 10 October 2023).
  43. Born, K.B.; Levinson, W. Using health care resources wisely during and following the COVID-19 pandemic. Can. J. Health Technol. 2021, 1, 2. [Google Scholar] [CrossRef]
  44. Frey, M.K.; Ellis, A.E.; Zeligs, K.; Chapman-Davis, E.; Thomas, C.; Christos, P.J.; Kolev, V.; Prasad-Hayes, M.; Cohen, S.; Holcomb, K.; et al. Impact of the coronavirus disease 2019 pandemic on the quality of life for women with ovarian cancer. Am. J. Obstet. Gynecol. 2020, 223, 725.e1–725.e9. [Google Scholar] [CrossRef]
  45. Satish, T.; Raghunathan, R.; Prigoff, J.G.; Wright, J.D.; Hillyer, G.A.; Trivedi, M.S.; Kalinsky, K.; Crew, K.D.; Hershman, D.L.; Accordino, M.K. Care Delivery Impact of the COVID-19 Pandemic on Breast Cancer Care. JCO Oncol. Pract. 2021, 17, e1215–e1224. [Google Scholar] [CrossRef]
  46. Bernstein, A.N.; Talwar, R.; Handorf, E.; Syed, K.; Danella, J.; Ginzburg, S.; Belkoff, L.; Reese, A.C.; Tomaszewski, J.; Trabulsi, E.; et al. Assessment of Prostate Cancer Treatment Among Black and White Patients During the COVID-19 Pandemic. JAMA Oncol. 2021, 7, 1467–1473. [Google Scholar] [CrossRef]
  47. Hanna, T.P.; King, W.D.; Thibodeau, S.; Jalink, M.; Paulin, G.A.; Harvey-Jones, E.; O’Sullivan, D.E.; Booth, C.M.; Sullivan, R.; Aggarwal, A. Mortality due to cancer treatment delay: Systematic review and meta-analysis. BMJ 2020, 371, m4087. [Google Scholar] [CrossRef] [PubMed]
Curroncol 31 00173 g001
Figure 1. STROBE diagram.
Figure 1. STROBE diagram.
Curroncol 31 00173 g001
Curroncol 31 00173 g002
Figure 2. Estimated cumulative incidence of death (A) and disease progression with competing risk of death (B) by cohort.
Figure 2. Estimated cumulative incidence of death (A) and disease progression with competing risk of death (B) by cohort.
Curroncol 31 00173 g002
Table 1. Summary of demographic and clinical characteristics by cohort.
Table 1. Summary of demographic and clinical characteristics by cohort.
VariableCOVID-19—2020
(n = 294)		Comparator—2019
(n = 335)		Standardized Difference
AgeMean (SD)66.1 (15.4)67.5 (14.9)0.14
Sex, n (%)Male151 (51.4)174 (51.9)0.01
Female143 (48.6)161 (48.1)
Marital Status, n (%)Married/Common-law Partner175 (59.5)205 (61.2)0.09
Divorced14 (4.8)21 (6.3)
Single49 (16.7)52 (15.5)
Unknown56 (19.0)57 (17.0)
Language, n (%)English as a first language252 (85.7)286 (85.4)0.01
Other42 (14.3)49 (14.6)
Highest Level of Education Completed, n (%)Less than high school3 (1.0)10 (3.0)0.18
High school43 (14.6)39 (11.6)
College diploma/Undergraduate degree24 (8.2)26 (7.8)
Graduate degree11 (3.7)14 (4.2)
Unknown213 (72.4)245 (73.1)
Missing-1
Socioeconomic Status, n (%)1—lowest59 (20.1)70 (20.9)0.12
254 (18.4)50 (14.9)
352 (17.7)61 (18.2)
447 (16.0)58 (17.3)
5—highest64 (21.8)79 (23.6)
Rural16 (5.4)14 (4.2)
Missing2 (0.7)3 (0.9)
ON-MARG-Households and Dwellings1—least marginalized44 (15.0)44 (13.1)0.11
231 (10.5)42 (12.5)
337 (12.6)35 (10.4)
454 (18.4)59 (17.6)
5—most marginalized122 (41.5)150 (44.8)
Missing6 (2.0)5 (1.5)
ON-MARG-Material Resources1—least marginalized81 (27.6)85 (25.4)0.08
262 (21.1)74 (22.1)
347 (16.0)62 (18.5)
453 (18.0)57 (17.0)
5—most marginalized45 (15.3)52 (15.5)
Missing6 (2.0)5 (1.5)
ON-MARG- Age and Labour Force1—least marginalized77 (26.2)83 (24.8)0.21
281 (27.6)80 (23.9)
352 (17.7)57 (17.0)
432 (10.9)30 (9.0)
5—most marginalized46 (15.6)80 (23.9)
Missing6 (2.0)5 (1.5)
ON-MARG- Racialized and Newcomer Populations1—least marginalized26 (8.8)28 (8.4)0.08
226 (8.8)34 (10.1)
354 (18.4)62 (18.5)
484 (28.6)103 (30.7)
5—most marginalized98 (33.3)103 (30.7)
Missing6 (2.0)5 (1.5)
Primary, n (%)Anal29 (9.9)25 (7.5)0.11
Colon170 (57.8)187 (55.8)
Rectal95 (32.3)123 (36.7)
Stage at Diagnosis, n (%)I46 (15.6)53 (15.8)0.16
II50 (17.0)66 (19.7)
III69 (23.5)104 (31.0)
IV98 (33.3)98 (29.3)
Unknown4 (1.4)11 (3.3)
Missing0 (0)3 (0.9)
ECOG Performance Status, n (%)047 (16.0)87 (26.0)0.14
173 (24.8)113 (33.7)
212 (4.1)28 (6.9)
315 (5.1)23 (6.9)
41 (0.3)1 (0.3)
Missing146 (49.7)83 (24.8)
Treatment, n (%) aSurgery123 (41.8)163 (48.7)0.14
Systemic therapy125 (42.5)121 (36.1)0.06
Radiation therapy85 (28.9) 87 (26.0) 0.06
a individual patients could count towards multiple categories; ON-MARG: Ontario Marginalization Index; ECOG: Eastern Cooperative Oncology Group.
Table 2. Pandemic-specific and quality measure performance.
Table 2. Pandemic-specific and quality measure performance.
Measure TypeMeasureCOVID-19 Cohort Performance;
% (Numerator/Denominator)		Comparator Cohort Performance;
% (Numerator/Denominator)		Standardized Difference
Pandemic-specific MeasuresReceipt of neoadjuvant chemotherapy16.3 (8/49)11.8 (8/68)0.13
Laparoscopic resection64.6 (62/96)70.8 (85/120)0.13
Short-course radiotherapy32.6 (15/46)11.1 (6/54)0.54
Oral systemic therapy31.2 (39/125)30.6 (37/121)0.01
Single-agent regimens32.0 (40/125)30.6 (37/121)0.03
Treatment deferral/interruptionDeferral12.1 (26/214)9.5 (24/252)0.09
Interruption32.4 (47/145)22.3 (33/148)0.23
Premature discontinuationSystemic therapy21.6 (27/125)19.8 (24/121)0.04
Radiotherapy9.4 (8/85)1.1 (1/87)0.38
Trial participation2.7 (8/294)1.8 (8/335)0.06
Quality MeasuresReceipt of appropriate oncology consultationColon: surgical oncologist, with or without a consultation with a medical oncologist82.4 (140/170)90.9 (170/187)0.25
Rectum: surgical oncologist AND medical oncologist AND radiation oncologist22.1 (21/95)20.3 (25/123)0.04
Anus: medical oncologist AND radiation oncologist65.5 (19/29)88.0 (22/25)0.55
30-day post-surgical readmission10.5 (11/105)3.6 (5/139)0.27
Unplanned acute care visit19.7 (58/294)23.0 (77/335)0.08
Receipt of appropriate treatmentColon: surgery for stage I–III disease73.6 (67/91)77.6 (83/107)0.09
Rectum: systemic therapy for stage II–IV disease24.7 (18/73)33.3 (31/93)0.19
Anus: concurrent chemotherapy and radiation for stage I–III disease61.5 (16/26)85.7 (18/21)0.57
Positive margins3.3 (3/135)2.2 (4/180)0.03
30-day mortalitySystemic therapy1.0 (1/104)13.8 (15/109)0.51
Surgery1.9 (2/105)0.7 (1/139)0.10
Timely oncologist consultation: within 2 weeks of referral84.9 (73/86)72.4 (63/87)0.31
Upstaging33.7 (98/291)30.6 (98/320)0.07
Timely receipt of treatment: within 60 days of the date of diagnosis58.2 (85/146)55.8 (82/147)0.05
Diagnosed in emergency department30.3 (88/290)27.8 (91/327)0.19
Pathologically confirmed disease68.0 (200/294)74.6 (250/335)0.20
Receipt of treatment for advanced disease67.3 (66/98)70.4 (69/98)0.07
Receipt of a palliative care consultation9.2 (9/98)9.2 (9/98)<0.01
Consent to treatmentSurgery54.3 (57/105)58.3 (81/139)0.08
Systemic therapy30.8 (32/104)27.5 (30/109)0.07
Radiotherapy14.0 (12/86)14.9 (13/87)0.03
Receipt of psychosocial support14.3 (42/294)17.9 (60/335)0.10
Receipt of pain management support0.0 (0/98)1.0 (1/98)0.14
Table 3. Examining adjusted associations between groups (COVID-19 vs. comparator) and time to all-cause death and disease progression using multivariable Cox proportional hazards and Fine-Gray regression models, respectively.
Table 3. Examining adjusted associations between groups (COVID-19 vs. comparator) and time to all-cause death and disease progression using multivariable Cox proportional hazards and Fine-Gray regression models, respectively.
VariableCox Model: All-Cause DeathFine-Gray Model: Disease Progression
HR95% CIp-ValueDisease ProgressionAll-Cause Death
HR95% CIp-ValueHR95% CIp-Value
GroupsComparatorRef--Ref--Ref--
COVID-190.880.61–1.270.501.160.82–1.630.410.740.42–1.280.28
Age5-year increment1.220.81–1.830.301.190.97–1.450.091.130.95–1.350.18
PrimaryColonRef--Ref--Ref--
Rectal0.880.58–1.340.501.140.76–1.700.520.710.38–1.350.30
Anal0.790.34–1.860.602.171.04–5.400.040.440.10–1.950.28
StageIRef--Ref--Ref--
II1.030.36–2.971.001.790.61–5.240.291.280.31–5.330.73
III2.711.13–6.470.032.570.98–6.730.063.020.88–10.40.08
IV7.253.11–16.9<0.0114.15.63–35.40<0.014.381.26–15.30.02
CI: confidence interval; HR: hazard ratio.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Powis, M.; Sutradhar, R.; Singh, S.; Alibhai, S.; Hack, S.; Baiad, A.; Chen, K.; Li, H.; Mohmand, Z.; Krzyzanowska, M.K. The Impact of the Pandemic on the Quality of Colorectal and Anal Cancer Care, and 2-Year Clinical Outcomes. Curr. Oncol. 2024, 31, 2328-2340. https://doi.org/10.3390/curroncol31040173

AMA Style

Powis M, Sutradhar R, Singh S, Alibhai S, Hack S, Baiad A, Chen K, Li H, Mohmand Z, Krzyzanowska MK. The Impact of the Pandemic on the Quality of Colorectal and Anal Cancer Care, and 2-Year Clinical Outcomes. Current Oncology. 2024; 31(4):2328-2340. https://doi.org/10.3390/curroncol31040173

Chicago/Turabian Style

Powis, Melanie, Rinku Sutradhar, Simron Singh, Shabbir Alibhai, Saidah Hack, Abed Baiad, Kevin Chen, Huaqi Li, Zuhal Mohmand, and Monika K. Krzyzanowska. 2024. "The Impact of the Pandemic on the Quality of Colorectal and Anal Cancer Care, and 2-Year Clinical Outcomes" Current Oncology 31, no. 4: 2328-2340. https://doi.org/10.3390/curroncol31040173

Article Metrics

Back to TopTop