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