| Literature DB >> 35328186 |
Angela Santoro1, Antonio Travaglino1, Frediano Inzani1, Patrizia Straccia1, Damiano Arciuolo1, Michele Valente1, Nicoletta D'Alessandris1, Giulia Scaglione1, Giuseppe Angelico1, Alessia Piermattei1, Federica Cianfrini1, Antonio Raffone2, Gian Franco Zannoni1,3.
Abstract
BACKGROUND: chemotherapy response score (CRS) is widely used to assess the response of ovarian high-grade serous carcinoma (HGSC) to chemotherapy and is based on pathological examination of omental specimens. We aimed to assess the prognostic value of CRS assessed on the uterine adnexa.Entities:
Keywords: CRS; chemotherapy; high grade serous carcinoma; ovarian cancer; prognosis
Year: 2022 PMID: 35328186 PMCID: PMC8946962 DOI: 10.3390/diagnostics12030633
Source DB: PubMed Journal: Diagnostics (Basel) ISSN: 2075-4418
Characteristics of the included studies.
| Study | Country | Sample Size | Period of Enrollment |
|---|---|---|---|
| Bohm 2015 | UK (test cohort) | 62 (test cohort) | 2009–2014 |
| Lee 2017 | Korea | 110 | 2006–2014 |
| Ditzel 2018 | Massachusetts (USA) | 68 (59 adnexal) | 2005–2012 |
| Michaan 2018 | Korea | 132 | 2009–2014 |
| Santoro 2019 | Italy | 161 | 2014–2017 |
| Lawson 2020 | Texas (USA) | 158 | 2013–2018 |
Figure 1Forest plot of the hazard ratio (HR) for progression-free survival in ovarian high-grade serous carcinoma (adnexal CRS1 vs. CRS2-3).
Figure 2Funnel plot of standard error by logHR for the analysis of adnexal CRS. The vertical line with the diamond sign at the bottom indicates the logarithm of the HR for progression-free survival. The symmetry of the funnel plot indicates that there is no significant risk of publication bias.
Figure 3Forest plot of the hazard ratio (HR) for progression-free survival in ovarian high-grade serous carcinoma (omental CRS1 vs. CRS2-3).
Figure 4Funnel plot of standard error by logHR for the analysis of omental CRS. The vertical line with the diamond sign at the bottom indicates the logarithm of the HR for progression-free survival. The symmetry of the funnel plot indicates that there is no significant risk of publication bias.