PURPOSE

We aimed to identify if there is an association between the severity of cervical cancer at diagnosis and the pattern of recurrence.

METHODS

We conducted a retrospective study of recurrent cervical cancers diagnosed between 2016 and 2018. We characterized the cases according to histology, size, FIGO stage (according to 2009 and 2018 FIGO classifications) and nodal involvement at diagnosis, symptoms at the time of recurrence, interval between the end of treatment and recurrence, imaging methods used, and location of the recurrence. Statistical analysis was performed between histology, size, FIGO stage and nodal involvement at diagnosis and time to recurrence and type of recurrence (locoregional versus lymph node, distant or multiple site involvement).

RESULTS

We included 48 patients with recurrent cervical cancer. At diagnosis, mean tumor size was 5 cm and 83% of the patients had squamous cell carcinoma. The FIGO stage changed in 43.8% of patients between the 2009 and the 2018 classifications. A mean of 26 months elapsed between the end of treatment and recurrence. Recurrence was symptomatic in 64.6% of patients. Imaging identified recurrence in 97.9% of patients. The most frequent recurrence sites were locoregional and lymph node metastases. We found a statistically significant association between 2009 FIGO stage and time to recurrence (P = 0.030) and lymph node involvement at diagnosis and type of recurrence (P = 0.022). As expected patients with more advanced disease recurred sooner, though this was only observed for the 2009 FIGO classification. Absence of lymph nodes at initial diagnosis was associated with locoregional recurrence, while presence of lymph node involvement was associated with lymph node, distant or multiple site involvement of recurrence. No other significant associations were found.

CONCLUSION

In our cohort of recurrent cervical cancer, we found an association between patients without lymph node metastases at initial diagnosis and locoregional recurrence. Further studies are needed in order to evaluate whether this association has predictive value.