| Literature DB >> 35015334 |
Jennifer M Davies1, Alice Spencer1, Sian Macdonald1, Lucy Dobson1, Emily Haydock2, Holly Burton2, Georgios Angelopoulos2, Pierre Martin-Hirsch2, Nick J Wood2, Amudha Thangavelu3, Richard Hutson3, Sarika Munot3, Marina Flynn4, Michael Smith5, Bridget DeCruze5, Eva Myriokefalitaki5, Katelijn Sap5, Brett Winter-Roach5, Robert Macdonald1, Richard J Edmondson6,7.
Abstract
OBJECTIVE: To review the effect of the COVID-19 pandemic on the diagnosis of cervical cancer and model the impact on workload over the next 3 years.Entities:
Keywords: cervical cancer; chemotherapy; diagnosis; gynaecological cancer; palliative care; radiation therapy; surgery
Mesh:
Year: 2022 PMID: 35015334 PMCID: PMC9303941 DOI: 10.1111/1471-0528.17098
Source DB: PubMed Journal: BJOG ISSN: 1470-0328 Impact factor: 7.331
Patient characteristics
|
Pre‐COVID
|
COVID
| Total |
| |
|---|---|---|---|---|
| Overall numbers | 233 | 173 | 406 | 0.003 |
| Treating hospital | ||||
| A | 63 (27) | 35 (20) | 98 | 0.06 |
| B | 12 (5) | 11 (6) | 23 | |
| C | 68 (29) | 51 (29) | 119 | |
| D | 21 (9) | 21 (12) | 42 | |
| E | 50 (21) | 43 (25) | 93 | |
| F | 20 (9) | 12 (7) | 32 | |
| Total | 233 | 173 | ||
| Stage at diagnosis | ||||
| 1a1 | 53 (23) | 40 (23) | 93 | 0.04 |
| 1a2‐1b2 | 51 (22) | 37 (21) | 88 | |
| 1b3 | 5 (2) | 2 (1) | 7 | |
| 2 | 42 (18) | 16 (9) | 58 | |
| 3 | 31 (13) | 36 (21) | 67 | |
| 4 | 26 (11) | 21 (12) | 47 | |
| Not documented | 25 (11) | 21 (12) | 46 | |
| Total | 233 | 173 | 406 | |
| Histology | ||||
| SCC | 162 (70%) | 115 (66) | 277 | 0.7 |
| Adenocarcinoma | 50 (21%) | 34 (20) | 84 | |
| Neuroendocrine | 1 (0.4%) | 2(1) | 3 | |
| Undifferentiated | 1 (0.4%) | 0 (0) | 1 | |
| Small cell Ca | 1 (0.4%) | 0 (0) | 1 | |
| Adenosquamous | 0 (0%) | 8 (5) | 8 | |
| Not documented | 18 (8%) | 14 (8) | 32 | |
| Total | 233 | 173 | 406 | |
| Symptoms | ||||
| Pain/Bleeding | 78 (33) | 69 (40) | 147 | 0.5 |
| Abnormal smear | 60 (26) | 43 (25) | 103 | |
| Unknown | 95 (41) | 61 (35) | 156 | |
| Total | 233 | 173 | 406 | |
| Mode of presentation | ||||
| GP | 63 (27) | 54 (31) | 117 | 0.04 |
| Colposcopy/abnormal smear | 60 (26) | 49 (28) | 109 | |
| A + E | 15 (6) | 10 (6) | 25 | |
| Other | 30 (13) | 24 (14) | 54 | |
| Unknown | 65 (28) | 36 (21) | 101 | |
| Total | 233 | 173 | ||
| Time of symptoms to diagnosis | ||||
| Median | 21.5 | 19 | 0.7 | |
| Range | 1‐474 | 1‐668 | ||
Chi‐square.
Paired t‐test.
Chi‐square comparing early stage versus late stage.
Mann–Whitney U‐ test.
Confusion matrix showing cases categorised by stage
| Pre‐COVID ( | COVID ( | |
|---|---|---|
| ≤1B2 (surgery) | 104 | 77 |
| 1B2/2/3 (curative RT) | 78 | 73 |
| 4 (palliative RT/chemo) | 26 | 21 |
FIGURE 1Forecasts of likely impact of COVID on extra cases of cervical cancer with no increased treatment capacity. Number of cases for each forecast represents numbers expected in addition to normal background diagnostic rates. Forecasts have been generated for a 3‐year period to reflect the normal cycle of cervical screening. (A) Model of ‘hidden’ cases showing effect of 273 additional cases. (B) Model of ‘excess’ cases showing effect of 630 additional cases presenting over a 3‐year period. (C) Summation of (A) and (B) to show likely increase in cases over three periods if no additional treatment capacity is provided
FIGURE 2Projections of the effect of increasing treatment capacity on increased numbers of cervical cancer cases presenting as result of COVID pandemic. The projection generated in Figure 1C was used as a baseline representing the additional cases expected as a result of the pandemic. The effects of increasing by one, two or three cases per month per cancer alliance in England are estimated in (A), (B) and (C), respectively, showing that increasing capacity by three cases per month per cancer alliance, would eradicate the extra low stage disease within 7 months with minimal impact on rates of regional and distant disease