Abstract
Background and objectives
Following the outbreak of COVID-19, a set of restrictions, health advice, and limitations were put in place to reduce the spread of the virus. These restrictions, together with fear and anxiety of the population, limited people’s access to public services such as health care services. Cancer patients during this era are a significant concern due to being at high risk for COVID-19 infection and also being exposed to delays in their diagnosis, treatment, and follow-ups. Delays in the treatment of cancer could lead to a poorer prognosis. In this study, we attempted to determine the magnitude of delays in chemotherapy and factors associated with delays during the COVID-19 pandemic.
Method
All patients diagnosed with colorectal, lung, gastric cancer, and lymphoma who had chemotherapy at teaching hospitals of Iran University of Medical Sciences (IUMS) between February 20, 2020, and March 20, 2022, were included. Age, gender, cancer type, having metastatic cancer, and date of each chemotherapy session were included for each patient individually. Every session with delays longer than two days was recorded. A three to six-day delay was considered a moderate delay, and a seven-day or longer delay was considered a severe delay in receiving each chemotherapy session. Additionally, each patient’s total number of delays in the entire course was calculated. Logistic regression was used to examine the impact of pandemic waves on delays. On the other hand, Poisson regression was used to evaluate the number of delays in the entire course of chemotherapy.
Results
The research findings indicated an association between the male gender and having metastasis with a higher likelihood of a moderate delay in the treatment regimen. Regarding cancer type, colorectal cancer was associated with higher rates of moderate delays (IRR = 1.88, P < 0.001), but gastric (IRR = 0.75, P = 0.001) and lung cancer (IRR = 0.59, P = 0.002) were associated with reduced rates of severe and moderate delays, respectively. Compared to the COVID-19 pandemic plateau periods, the first (OR = 2.08, P < 0.001), third, and fifth waves of the pandemic were associated with increased delays.
Conclusion
We found an association between the male gender, colorectal cancer, metastatic disease and higher rates of moderate delays. The initial COVID-19 pandemic wave was associated with increased severe delays in the chemotherapy course. According to the findings of this study, male cancer patients and those with metastatic cancer are at risk of poorer prognosis due to lower adherence to treatment. These findings can assist policymakers in developing targeted strategies to lessen the delay rates in the more vulnerable population.
Keywords: Cancer, Chemotherapy, COVID-19, Pandemic, Delay in treatment, SARS-CoV-2
Background
The outbreak of the COVID-19 virus started in late December 2019, and the WHO declared it a pandemic on 11 March 2020 [1]. Respiratory disease caused by COVID-19 had a high transmissibility and mortality. Various limitations, guidelines, and health recommendations, including mask wear and social distancing, were implemented during the pandemic to lower the disease’s prevalence [2]. Limited public transportation, limited working hours, and complete lockdowns in severe circumstances, together with people’s fear of the COVID-19 virus, restricted people’s access to any public services and, on top of that, health care services. On the other hand, the high number of COVID-19 patients and the large burden of the COVID-19 pandemic on hospitals deregulated the routine delivery of healthcare services, which led to poorer overall performance of healthcare systems in different aspects [3, 4].
The severity of COVID-19 infection varies in different populations. Having an underlying illness, in particular cancer, or being immunocompromised is one of the risk factors for higher infection rates and severe COVID-19 respiratory disease [5]. During the pandemic, cancer patients experienced a high degree of anxiety, which may have led to poorer treatment compliance, delay in cancer treatment, and therefore worsening of overall prognosis [6, 7]. Early diagnosis, treatment and regular follow-up after treatment can lead to better overall outcomes and prognosis of cancer [8]. Cancer patients are a major reason for concern due to their underlying disease and the significance of their scheduled treatment plan. Any delay or interruption in cancer treatment would impact the overall prognosis and survival [9]. According to the World Bank, during the COVID-19 pandemic, Iran was classified as a Lower-Middle-Income Country (LMIC) [10]. During the pandemic, low- and middle-income countries faced significant challenges in treating cancer patients due to increased pressure on hospitals, disrupted supply chains, and exacerbated financial issues [11, 12].
Using the findings of this study, healthcare systems can create more effective treatment plans and general preventative measures, especially for high-priority patients who are more likely to have a delay during similar circumstances. In this study, we attempted to determine the magnitude of treatment delay caused by the COVID-19 pandemic in three teaching hospitals in Tehran, Iran, which is an LMIC and the parameters associated with treatment delay.
Method
Study design
This retrospective observational study using universal sampling included all patients undergoing chemotherapy for cancers such as lung, lymphomas, gastric, and colorectal from February 20, 2020, to March 20, 2022, at 3 teaching hospitals of Iran University of Medical Sciences (IUMS) in Tehran, Iran. All patients below 18 and over 80 years old were excluded. Due to inadequate data about the duration of their cycle and incomplete patient information, patients who underwent chemotherapy for two or fewer sessions were also excluded. Data regarding each patient’s cancer type, chemotherapy cycle length, and demographic features (such as age and gender) were gathered using patient records from the hospitals. Metastasis of the underlying cancer to another organ (referred to as “metastatic cancer” in this study) was used as one of the indicators of the disease stage.
COVID-19 waves in Iran
This study included COVID-19 waves in Iran to measure the association of the COVID-19 pandemic with chemotherapy delays among cancer patients. According to the Coronavirus Control Operations Headquarters in Iran, the country experienced six waves of COVID-19 during the pandemic [13] (Table 1). Also, in this study, each scheduled session of chemotherapy was determined in the aspect of being during each wave of COVID-19.
Table 1.
COVID-19 pandemic waves in Iran
| Wave number | Start date | Finish date | Duration (Days) |
|---|---|---|---|
| First wave | 01/03/2020 | 20/04/2020 | 51 |
| Second wave | 04/06/2020 | 26/06/2020 | 23 |
| Third wave | 19/09/2020 | 25/11/2020 | 67 |
| Fourth wave | 31/03/2021 | 29/05/2021 | 60 |
| Fifth wave | 22/06/2021 | 18/12/2021 | 180 |
| Sixth wave | 10/01/2022 | 20/03/2022 | 70 |
Measured delays
Based on chemotherapy cycle length, scheduled chemotherapy session dates were defined. A latency period was determined by calculating the number of days between the actual dates that the patient received chemotherapy and its relative scheduled date; a latency period of two days or less was disregarded, and a latency period of 3 days or more was generally considered as a delay in each chemotherapy session. In this study, 3 to 6 days of delay in each session was considered a moderate delay and a delay of 7 days or more was considered a severe delay. Before the pandemic, median delays of 7 days were common, and any delays longer than that are not recommended and might be associated with lower survival rates [14].
The number of delayed sessions for each patient (moderate and severe separately) was also counted to measure the effect of age, gender, metastasis, and cancer type on the number of times a patient experienced delays in their entire course of chemotherapy.
Analysis
All data was analyzed using STATA version 17 (Stata Corp). To evaluate the effect of age, gender, metastasis, and cancer type on experiencing at least one delay throughout the entire course of chemotherapy (compared to not experiencing any delays in the whole course (a dichotomous outcome)), t-tests and chi squire were used. Also, to evaluate the association of said variables with the quantitative number of delayed sessions for each patient (moderate and severe separately) the Poisson regression model and Incidence Rate Ratio (IRR) were used.
A random-effect multiple logistic regression was performed to evaluate the effect of COVID-19 pandemic waves on the incidence of delay in each session. A chemotherapy session was defined during the COVID-19 waves if the scheduled date of the chemotherapy session was during one of the COVID-19 waves. As a result, if the scheduled date of the chemotherapy session was between two waves, the chemotherapy session was included in the COVID-19 pandemic plateau. For that model, panel data was defined from grouping sessions by their unique patient ID code. Also, age, gender, metastasis, and type of cancer were used as covariates in that model.
Result
After data collection, 670 patients were selected, of which 16 met the exclusion criteria. In this article, 654 patients underwent chemotherapy sessions. Of this total, 246 patients (37.61%) were female. The average age of cancer patients was 57.05 years (SD = 12.73). In this study, 79 patients (12.08%) had metastatic cancer. Regarding cancer type, 260 patients (39.76%) had colorectal cancer, 221 patients (33.79%) had gastric cancer, 54 patients (8.26%) had lung cancer, and 119 patients (18.20%) had lymphoma (Table 2).
Table 2.
Patients characteristics and types of cancers
| Variable | No Delay | Delay1 | Total | P-value |
|---|---|---|---|---|
| Age (mean) | 57.80(SD = 14.76) | 56.97(SD = 12.86) | 57.05(SD = 12.73) | 0.622 |
| Gender: | 0.093 | |||
| Female |
31 (12.60%) |
215 (87.40%) |
246 (37.61%) |
|
| Male |
35 (8.58%) |
373 (91.42%) |
408 (62.39%) |
|
| Metastasis: | 0.114 | |||
| No metastasis |
62 (10.78%) |
513 (89.22%) |
575 (87.92%) |
|
| With Metastasis |
4 (5.06%) |
75 (94.94%) |
79 (12.08%) |
|
| Cancer type: | 0.815 | |||
| Colorectal |
23 (8.85%) |
237 (91.15%) |
260 (39.76%) |
|
| Gastric |
25 (11.31%) |
196 (88.69%) |
221 (33.79%) |
|
| Lung |
5 (9.26%) |
49 (90.74%) |
54 (8.26%) |
|
| Lymphoma |
13 (10.92%) |
106 (89.08%) |
119 (18.20%) |
|
| Total |
66 (10.09%) |
588 (89.91%) |
654 (100%) |
1Encountering at least one delay in entire chemotherapy course;2 Result of T-test;3,4,5Result of Chi-square test
Overall, there were 2407 delayed sessions (53.08%). The median days of delay was 3 days. In this study, 588 patients (89.91%) encountered at least one delay in chemotherapy session during their entire course, while 66 patients (10.09%) did not suffer any delays at all. The average age of patients with at least one delay during their entire course and without a delay wasn’t different. Also, gender, metastasis, and type of cancer didn’t have a significant association with having a delay in the entire course of chemotherapy (Table 2).
Number of delayed sessions for each patient
A Poisson model was used to count the number of moderate and severe delays during patients’ entire chemotherapy course. Being male (IRR = 1.20, P = 0.002) and having metastatic cancer (IRR = 1.20, P = 0.01) were associated with higher rates of moderate delay. In an aspect of cancer type, lymphoma was set as the baseline group. Colorectal cancer had a significant association with higher rates of moderate delay (IRR = 1.88, P < 0.001), and lung cancer had an association with lower rates of moderate delays (IRR = 0.59 P = 0.002) in the entire course of chemotherapy (Table 3). Regarding the number of severe delays, gastric cancer had an association with lower rates of delay when compared to lymphoma as a baseline group. (IRR = 0.75, P = 0.001) (Table 4).
Table 3.
Poisson regression model for number of moderate delays in entire course of Chemotherapy
| Variable | IRR | P-Value | CI95%* |
|---|---|---|---|
| Age | 0.99 | 0.32 | 0.99-1.00 |
| Gender: | |||
| Female | Baseline | ||
| Male | 1.20 | 0.002 | 1.06–1.35 |
| Metastasis: | |||
| Without metastasis | Baseline | ||
| With metastasis | 1.20 | 0.01 | 1.03–1.41 |
| Cancer type: | |||
| Lymphoma | Baseline | ||
| Colorectal | 1.88 | < 0.001 | 1.57–2.26 |
| Gastric | 1.11 | 0.29 | 0.91–1.35 |
| Lung | 0.59 | 0.002 | 0.42–0.83 |
*Confidence interval
Table 4.
Poisson regression model for number of severe delays in entire course of Chemotherapy
| Variable | IRR | P-value | CI95%* |
|---|---|---|---|
| Age | 1.00 | 0.10 | 0.99-1.00 |
| Gender: | |||
| Female | Baseline | ||
| Male | 0.90 | 0.07 | 0.80–1.01 |
| Metastasis: | |||
| Without metastasis | Baseline | ||
| With metastasis | 0.96 | 0.71 | 0.80–1.15 |
| Cancer type: | |||
| Lymphoma | Baseline | ||
| Colorectal | 0.94 | 0.47 | 0.80–1.10 |
| Gastric | 0.75 | 0.001 | 0.63–0.89 |
| Lung | 0.95 | 0.68 | 0.75–1.20 |
*Confidence interval
Waves
In this study, out of 4535 chemotherapy sessions, 2407 sessions (53.08%) were delayed. Moreover, 2545 sessions (56.12%) occurred during 6 waves of the pandemic, and 1990 sessions (43.88%) were not during any wave of the pandemic (Table 5).
Table 5.
Number of delayed sessions in each wave of COVID-19 pandemic
| Wave | No Delay | Delay* | Total |
|---|---|---|---|
| No Wave |
1,002 (50.35%) |
988 (49.65%) |
1,990 (43.88%) |
| First Wave |
55 (33.95%) |
107 (66.05%) |
162 (3.57%) |
| Second Wave |
70 (58.82%) |
49 (41.18%) |
119 (2.62%) |
| Third Wave |
197 (44.47%) |
246 (55.53%) |
443 (9.77%) |
| Fourth Wave |
171 (55.16%) |
139 (44.84%) |
310 (6.84%) |
| Fifth Wave |
474 (40.65%) |
692 (59.35%) |
1,166 (25.71%) |
| Sixth Wave |
159 (46.09%) |
186 (53.91%) |
345 (7.61%) |
| Total |
2,128 (46.92%) |
2,407 (53.08%) |
4,535 (100.00%) |
*Delays beyond two days in each session
A logistic regression model showed a significant association between delay and the first (OR = 2.08, P < 0.001), third (OR = 1.33 P = 0.02), and fifth (OR = 1.61 and P < 0.001) waves of the COVID-19 in Iran. The results remained consistently significant in the first and fifth waves, even in severe delays (Table 6). On the contrary, the fourth wave of COVID-19 was negatively associated with delays (OR = 0.74 and P = 0.04) (Table 7).
Table 6.
Multiple logistic regression analysis of association of pandemic waves and having a severe Delay
| Waves | Odds Ratio* | P-Value | CI95%** |
|---|---|---|---|
| No wave | Baseline | ||
| First Wave | 2.36 | < 0.001 | 1.57–3.55 |
| Second Wave | 0.65 | 0.11 | 0.38–1.10 |
| Third Wave | 1.10 | 0.49 | 0.83–1.45 |
| Fourth Wave | 0.92 | 0.63 | 0.66–1.28 |
| Fifth Wave | 1.27 | 0.02 | 1.03–1.57 |
| Sixth Wave | 1.03 | 0.85 | 0.73–1.44 |
* Adjusted With Age, Gender, Metastasis status and Cancer type. **Confidence interval
Table 7.
Multiple logistic regression analysis of association of pandemic waves and having a Delay
| Waves | Odds Ratio* | P-Value | CI95%** |
|---|---|---|---|
| No wave | Baseline | ||
| First Wave | 2.08 | < 0.001 | 1.40–3.09 |
| Second Wave | 0.66 | 0.06 | 0.43–1.02 |
| Third Wave | 1.33 | 0.02 | 1.04–1.69 |
| Fourth Wave | 0.74 | 0.04 | 0.55–0.99 |
| Fifth Wave | 1.61 | < 0.001 | 1.33–1.95 |
| Sixth Wave | 1.24 | 0.14 | 0.93–1.66 |
*Adjusted With Age, Gender, Metastasis status and Cancer type. **Confidence interval
Discussion
This study found a significant association between gender and moderate delays in the course of chemotherapy. Similar findings regarding male patients experiencing more delays in cancer treatment were also noted before the pandemic [15]. Although the exact cause requires further studies, this might be due to the larger social support females receive, which decreases patient delay [16]. Also, historically, men have consistently underused healthcare services and have generally shown less interest in health compared to women [17, 18].
Age was not associated with a moderate or severe delay during chemotherapy, which is consistent with previous literature [15, 19]. Metastatic cancer was associated with higher rates of moderate delays in an entire course of chemotherapy. The exact cause of this increase needs further study. However, it might be due to a longer hospitalization, for which patients encountered difficulties receiving the treatment in a timely manner. Similar observations were also noted in other literature [20].
Colorectal cancer was associated with higher rates of moderate delays compared to other types of cancer. The same association between GI tract cancer and higher rates of delay was observed in similar studies [20]. On the other hand, lung cancer was associated with a decreased rate of moderate delays and gastric cancer was associated with a reduced rate of severe delays in the course of chemotherapy. The exact cause of these findings requires further studies. However, in the case of lung cancer, which is the most lethal cancer, the cause of stricter adherence to chemotherapy may be due to the fact that the fear of these patients from their disease was higher than the fear of the COVID-19 pandemic [21].
To our knowledge, this is the first study that analyzed the effect of the COVID-19 pandemic waves on the treatment of cancer patients. The initial wave of the COVID-19 pandemic was significantly linked to increased delays, including severe delays. This finding has been caused by the high rates of fear and anxiety among the population at first, as well as the nearly complete lockdown and quarantine that were imposed during the early stages of the pandemic [22, 23]. The fifth pandemic wave was also associated with increased delays(beyond two days in each session ). It can be due to the prolongation of the fifth wave in Iran and the higher number of chemotherapy sessions during this wave, the exact cause for higher delay during this wave requires further studies.
Overall, a reducing trend was observed in the number of delays during the pandemic, specifically in the last six months of this study. This reducing trend can be explained by the discovery of vaccines, less restriction throughout the pandemic, and decreased overall fear of the disease over time [22](Fig. 1).
Fig. 1.
Monthly Average of number of delays in entire course of chemotherapy
Managing cancer during a crisis like the COVID-19 pandemic in lower-middle-income countries (LMIC) poses a complex challenge. It involves protecting patients from COVID-19 while ensuring the continuity of cancer treatment with limited resources. Healthcare-related services such as chemotherapy, radiotherapy, and life-saving interventions experienced more severe shortages in these countries compared to high-income countries (HIC) [11]. During the pandemic, previous treatment challenges in LMIC are exacerbated by disrupted global supply chains and financial constraints [24]. These elements require identifying vulnerable patients and preparedness to prioritize such patients, creating a stepwise approach for better delivery of health services to cancer patients in these regions [12].
The study’s strengths include its duration, sample size, and consideration of pandemic waves, which can highlight the pandemic’s impact on healthcare services. However, there are limitations to this study. First, the entire study took place during the COVID-19 pandemic. Further studies should include a comparison with the pre and post-pandemic periods. Second, the exact cause of these delays is unknown and can be studied in the future.
Delays between treatment options( such as surgery and chemotherapy), assessing vaccinations and the effects of policies implemented during this period on the continuity of chemotherapy and assessing the impact of these delays on outcomes and the survival of patients can also be future topics for further studies.
Conclusion
This study revealed a significant correlation between gender and moderate delays in chemotherapy, with males experiencing more delays. However, age did not show a similar association. Having metastatic disease and colorectal cancer were linked with increased moderate delays, while lung cancer was associated with fewer delays. The COVID-19 pandemic’s initial wave significantly increased delays, with a reducing trend observed over time, possibly due to vaccine discovery and reduced fear of the disease. Exploring the exact causes of these delays, the impact of vaccinations, implemented policies, and telemedicine on chemotherapy continuity, as well as the effects of these delays on patient outcomes and survival, could provide a more comprehensive understanding of the pandemic’s impact on cancer patients.
Acknowledgements
The Authors would like to appreciate to the Vice-Chancellor of Research and Technology at Iran University of Medical Sciences for Financial supports of this study. We appreciate “Quillbot” which has been used to improve readability of the text.
Abbreviations
- IUMS
Iran University of Medical sciences
- CI
Confidence interval
- IRR
Incidence Rate Ratio
- LMIC
Lower-middle-income countries
- HIC
High-income countries
Author contributions
A.TB. and M.R. designed the study and its topic. P.F., K.A. collected the data and conducted data analysis.M.R., D.H, SAY.A. participated in data analysis and drafting manuscript. M.N., A.TB. and P.F. provided expert opinions regarding data analysis, critical revision of the study and supervised the project. All authors take full responsibility for their contributions to this study. Also, all authors reviewed and approved the final manuscript.
Funding
This work was supported by Iran University of Medical Sciences (Grant number: 22177).
Data availability
Data of this study is available upon reasonable request from corresponding author.
Declarations
Ethics approval and consent to participate
This study was approved by the Research Ethics Committee of the Iran University of Medical Sciences, Tehran, Iran (IR.IUMS.REC.1400.1201). In this study, the need for informed consent was waived by the Research Ethics Committee of the Iran University of Medical Sciences, Tehran, Iran.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
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Data Availability Statement
Data of this study is available upon reasonable request from corresponding author.