Funding:
This research was supported by the projects from the National Natural Science Foundation of China (No. 82172993).
Abstract
Objective The COVID-19 pandemic has had a significant impact on oncogynecologic patients worldwide, particularly with respect to delayed diagnosis and treatment. During the COVID-19 pandemic, few studies have examined the impact of delayed surgery on survival in early-stage cervical cancer patients. The purpose of this study was to determine the effect of delayed surgical time on survival in patients with early cervical cancer.
Design A retrospective cohort study.
Setting A single general hospital in Shaanxi, Northwest China.
Population A total of 1207women with early cervical cancer were recruited between April 2013 and December 2018 in Mainland China and followed up until 29 Feb 2022.
Methods This retrospective cohort study was conducted in a comprehensive tertiary hospital in Shaanxi, Xi’an, China. We used a Cox proportional hazard model with delay time in weeks as a categorical variable to analyse the effect of surgical delay time on survival. The research was approved by the Medical Ethics Committee of the Xijing Hospital of Fourth Military Medical University.
Main Outcome Measures The 5-year overall and disease-free survival were used as the primary outcome measures.
Results A total of 800 participants were included in the final cohort. In the multivariate Cox regression analysis (median follow-up, 58 months), patients in the long delay time group had DFS (5-year rates, 91.5% versus 90.9%, HR 0.99, 95% CI 0.62~1.59,P =0.98) and OS (5-year rates of 92.9% versus 90.8%, HR 0.68, 95% CI 0.42~1.10, P =0.11) similar to those in the short delay time group.
Conclusions Our findings indicate that a 12-week delay in surgery is not associated with long-term survival in women with early-stage cervical cancer.
Keywords Cervical cancer; Delayed surgery; Cohort study; Wait time; COVID-19
1. Introduction
Since 2020, the coronavirus disease 2019 (COVID-19) pandemic has radically affected the world1, 6. Health care systems have been strained by the pandemic, leading to unprecedented challenges regarding timely oncologic care. Globally, the COVID-19 pandemic has impacted cancer patients in many ways, according to a number of studies13, 16.Multiple studies have demonstrated that COVID-19 has resulted in delayed cancer care2, 3, 14.
A recent high-quality meta-analysis concluded that cancer treatment delay is associated with increased mortality in various malignancies4. Several studies have shown that a short wait time does not affect the prognosis of patients with early cervical cancer7-12, but data from mainland China are still lacking. Similar to all other countries, China is struggling to combat the COVID-19 pandemic. Social distancing and community quarantine seem to be the best ways to overcome the COVID-19 pandemic. However, these measures prevent some cancer patients with clinical symptoms from reaching hospitals. To determine whether the delay from the onset of clinical symptoms to surgical treatment affects the prognosis of patients, we examined the association between delayed surgery and outcomes for women with early cervical cancer.
Associations between surgical delay time, defined as the time interval from clinical symptom onset to radical hysterectomy, and oncologic outcomes, including surgical-pathological factors (pathological parametrical invasion, lymphovascular space invasion and nodal metastasis) and mortality, were examined.
2. Methods
2.1 Data collection
This was a retrospective observational cohort study of patients undergoing Da Vinci robot-assisted radical hysterectomy in the Department of Gynaecologic Oncology at a tertiary care centre between January 2013 and December 2018. All robot-assisted radical hysterectomies were performed by senior gynaecologic oncologist surgeons. The study was approved by the Medical Ethics Committee of Xijing Hospital.
2.2 Study design
A total of 1207 patients who had undergone surgical treatment for early cervical cancer were selected for the study. Four patients had other malignancies, while 64 patients had incomplete medical records or follow-up data. A total of 151patients were excluded because they had preoperative radiotherapy and/or chemotherapy, and 20 were excluded because they did not undergo pelvic lymphadenectomy (stage IA1). A total of 168 patients without delayed time information or with no typical clinical symptoms were also excluded from the study (Fig. 1).
An electronic database was used to collect patient characteristics and accessible clinical data. Patient characteristics included age at diagnosis, gravidity, parity, and typical clinical symptoms, such as increased vaginal secretion, contact bleeding, and irregular vaginal bleeding. Tumour characteristics included histological type, clinical stage reclassification according to FIGO 2018 classification, pathological characteristics, and presence of pelvic or para-aortic lymph node metastases. Adjuvant treatments included postoperative radiotherapy, chemotherapy, chemoradiotherapy or follow-up.
2.3 Study definitions
Surgical delay time was defined as the time interval between the onset of typical clinical symptoms and surgical treatment by theDavinci robot assisted with radical hysterectomy. This cohort of patients was divided into two groups according to the wait time between the onset of typical clinical symptoms and surgery: shorter wait time (<12 weeks) versus longer wait time (≥12 weeks). The median wait time in our data was used as the cut-off. The time interval between surgical therapy for cervical cancer and the first recurrence or death from cervical cancer was characterized as disease-free survival (DFS). The time interval between surgical treatment for cervical cancer and death from any cause was defined as overall survival (OS).
All patients were enrolled in follow-up programs after surgery.
2.4 Statistical methods
Data were expressed as the mean and standard deviation (SD) when normally distributed or the median and interquartile range (IQR) when skewed.
The collected variables were analysed for significant differences between the two groups. Demographics and patient characteristics were compared in the two groups using the Wilcoxon rank-sum test for continuous variables and the χ2 test for categorical variables.
Survival curves were assessed by the Kaplan–Meier method. Differences between the groups were assessed by the log-rank test. A Cox proportional hazards regression model was used to estimate the effect of wait time on survival outcomes, adjusted for factors known to be associated with survival, expressed as hazard ratios (HR) and 95% confidence intervals (CI). All survival analyses were censored at the last follow-up date.
Data were analysed from February to April 2022. All statistical analyses were considered statistically significant with a two-sided P<0.05.
SPSS (version 25.0, Armonk, NY, USA) and R version 3.5.3 (Wiener, Australia) were used for analysis. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines were used to outline the results of this observational cohort study.
2.5 Sensitivity analyses
In addition to the above analysis, a series of sensitivity analyses were performed, including the cases with tumour sizes >4 cm. See Supplementary Materials for further details of these sensitivity analyses.
3. Results