Ultrasound and Clinical Preoperative Characteristics for Discrimination Between Ovarian Metastatic Colorectal Cancer and Primary Ovarian Cancer: A Case-Control Study
Status PubMed-not-MEDLINE Language English Country Switzerland Media electronic
Document type Journal Article
PubMed
31805677
PubMed Central
PMC6963303
DOI
10.3390/diagnostics9040210
PII: diagnostics9040210
Knihovny.cz E-resources
- Keywords
- cancer, colon, metastasic, model, neoplasm, ovary, risk prediction, ultrasound,
- Publication type
- Journal Article MeSH
The aim of this study was to describe the clinical and sonographic features of ovarian metastases originating from colorectal cancer (mCRC), and to discriminate mCRC from primary ovarian cancer (OC). We conducted a multi-institutional, retrospective study of consecutive patients with ovarian mCRC who had undergone ultrasound examination using the International Ovarian Tumor Analysis (IOTA) terminology, with the addition of evaluating signs of necrosis and abdominal staging. A control group included patients with primary OC. Clinical and ultrasound data, subjective assessment (SA), and an assessment of different neoplasias in the adnexa (ADNEX) model were evaluated. Fisher's exact and Student's t-tests, the area under the receiver-operating characteristic curve (AUC), and classification and regression trees (CART) were used to conduct statistical analyses. In total, 162 patients (81 with OC and 81 with ovarian mCRC) were included. None of the patients with OC had undergone chemotherapy for CRC in the past, compared with 40% of patients with ovarian mCRC (p < 0.001). The ovarian mCRC tumors were significantly larger, a necrosis sign was more frequently present, and tumors had an irregular wall or were fixed less frequently; ascites, omental cake, and carcinomatosis were less common in mCRC than in primary OC. In a subgroup of patients with ovarian mCRC who had not undergone treatment for CRC in anamnesis, tumors were larger, and had fewer papillations and more locules compared with primary OC. The highest AUC for the discrimination of ovarian mCRC from primary OC was for CART (0.768), followed by SA (0.735) and ADNEX calculated with CA-125 (0.680). Ovarian mCRC and primary OC can be distinguished based on patient anamnesis, ultrasound pattern recognition, a proposed decision tree model, and an ADNEX model with CA-125 levels.
Department of Gynecologic Oncology Gdynia Oncology Center Pomeranian Hospitals Gdynia 81519 Poland
Department of Obstetrics and Gynecology Centre of Postgraduate Medical Education 01809 Warsaw Poland
Department of Obstetrics and Gynecology Clínica Universidad de Navarra Pamplona 31008 Spain
Department of Oncological Surgery Gdynia Oncology Centre Gdynia 81519 Poland
Division of Propedeutics of Oncology Medical University of Gdańsk Gdańsk 80210 Poland
See more in PubMed
GLOBOCAN Colorectal cancer. Estimated incidence, mortality and prevalence worldwide in 2012. [(accessed on 29 August 2018)]; Available online: http://globocan.iarc.fr/Pages/fact_sheets_cancer.aspx?cancer=colorectal.
Network N.C.C. Nccn Clinical Practice Guidelines in Oncology, Colon Cancer. National Comprehensive Cancer Network; Jenkintown, PA, USA: 2018. Version 3.2018. PubMed
Van Cutsem E., Cervantes A., Adam R., Sobrero A., Van Krieken J.H., Aderka D., Aranda Aguilar E., Bardelli A., Benson A., Bodoky G., et al. Esmo consensus guidelines for the management of patients with metastatic colorectal cancer. Ann. Oncol. 2016;27:1386–1422. doi: 10.1093/annonc/mdw235. PubMed DOI
Mori Y., Nyuya A., Yasui K., Toshima T., Kawai T., Taniguchi F., Kimura K., Inada R., Nishizaki M., Haraga J., et al. Clinical outcomes of women with ovarian metastases of colorectal cancer treated with oophorectomy with respect to their somatic mutation profiles. Oncotarget. 2018;9:16477–16488. doi: 10.18632/oncotarget.24735. PubMed DOI PMC
Sekine K., Hamaguchi T., Shoji H., Takashima A., Honma Y., Iwasa S., Kato K., Takahashi K., Kato T., Kanemitsu Y., et al. Retrospective analyses of systemic chemotherapy and cytoreductive surgery for patients with ovarian metastases from colorectal cancer: A single-center experience. Oncology. 2018;95:220–228. doi: 10.1159/000489665. PubMed DOI
Kuijpers A.M., Mehta A.M., Aalbers A.G., van Driel W.J., Boot H., Verwaal V.J. Treatment of ovarian metastases of colorectal and appendiceal carcinoma in the era of cytoreductive surgery and hyperthermic intraperitoneal chemotherapy. Eur. J. Surg. Oncol. 2014;40:937–942. doi: 10.1016/j.ejso.2014.02.238. PubMed DOI
Zikan M., Fischerova D., Pinkavova I., Dundr P., Cibula D. Ultrasonographic appearance of metastatic non-gynecological pelvic tumors. Ultrasound Obstet. Gynecol. 2012;39:215–225. doi: 10.1002/uog.10068. PubMed DOI
Testa A.C., Ferrandina G., Timmerman D., Savelli L., Ludovisi M., Van Holsbeke C., Malaggese M., Scambia G., Valentin L. Imaging in gynecological disease (1): Ultrasound features of metastases in the ovaries differ depending on the origin of the primary tumor. Ultrasound Obstet. Gynecol. 2007;29:505–511. doi: 10.1002/uog.4020. PubMed DOI
Guerriero S., Alcazar J.L., Pascual M.A., Ajossa S., Olartecoechea B., Hereter L. Preoperative diagnosis of metastatic ovarian cancer is related to origin of primary tumor. Ultrasound Obstet. Gynecol. 2012;39:581–586. doi: 10.1002/uog.10120. PubMed DOI
Epstein E., Van Calster B., Timmerman D., Nikman S. Subjective ultrasound assessment, the adnex model and ultrasound-guided tru-cut biopsy to differentiate disseminated primary ovarian cancer from metastatic non-ovarian cancer. Ultrasound Obstet. Gynecol. 2016;47:110–116. doi: 10.1002/uog.14892. PubMed DOI
Moro F., Pasciuto T., Djokovic D., Di Legge A., Granato V., Moruzzi M.C., Mancari R., Annoni G.F., Fischerova D., Franchi D., et al. Role of ca125/cea ratio and ultrasound parameters in identifying metastases to the ovaries in patients with multilocular and multilocular-solid ovarian masses. Ultrasound Obstet. Gynecol. 2018;53:116–123. doi: 10.1002/uog.19174. PubMed DOI
Timmerman D., Valentin L., Bourne T.H., Collins W.P., Verrelst H., Vergote I. International Ovarian Tumor Analysis, G. Terms, definitions and measurements to describe the sonographic features of adnexal tumors: A consensus opinion from the international ovarian tumor analysis (iota) group. Ultrasound Obstet. Gynecol. 2000;16:500–505. doi: 10.1046/j.1469-0705.2000.00287.x. PubMed DOI
Testa A.C., Ludovisi M., Mascilini F., Di Legge A., Malaggese M., Fagotti A., Fanfani F., Salerno M.G., Ercoli A., Scambia G., et al. Ultrasound evaluation of intra-abdominal sites of disease to predict likelihood of suboptimal cytoreduction in advanced ovarian cancer: A prospective study. Ultrasound Obstet. Gynecol. 2012;39:99–105. doi: 10.1002/uog.10100. PubMed DOI
Van Calster B., Van Hoorde K., Valentin L., Testa A.C., Fischerova D., Van Holsbeke C., Savelli L., Franchi D., Epstein E., Kaijser J., et al. Evaluating the risk of ovarian cancer before surgery using the adnex model to differentiate between benign, borderline, early and advanced stage invasive, and secondary metastatic tumours: Prospective multicentre diagnostic study. BMJ. 2014;349:g5920. doi: 10.1136/bmj.g5920. PubMed DOI PMC
Van Calster B., Vergouwe Y., Looman C.W., Van Belle V., Timmerman D., Steyerberg E.W. Assessing the discriminative ability of risk models for more than two outcome categories. Eur. J. Epidemiol. 2012;27:761–770. doi: 10.1007/s10654-012-9733-3. PubMed DOI
Van Calster B., Van Hoorde K., Froyman W., Kaijser J., Wynants L., Landolfo C., Anthoulakis C., Vergote I., Bourne T., Timmerman D. Practical guidance for applying the adnex model from the iota group to discriminate between different subtypes of adnexal tumors. Facts Views Vis. Obgyn. 2015;7:32–41. PubMed PMC
Breiman L., Friedman J., Stone C., Olshen R. Classification and Regression Trees. 1st ed. Chapman and Hall/CRC; New York, NJ, USA: 1984.
Quinlan J.R. Induction of decision trees. Mach. Learn. 1986;1:81–106. doi: 10.1007/BF00116251. DOI
Hastie T., Tibshirani R., Friedman J. The Elements of Statistical Learning. 2 ed. Springer; New York, NY, USA: 2009.
Chang L.Y., Wang H.W. Analysis of traffic injury severity: An application of non-parametric classification tree techniques. Accid. Anal. Prev. 2006;38:1019–1027. doi: 10.1016/j.aap.2006.04.009. PubMed DOI
Stanimirowa I., Daszykowski M., Walczak B. Metody uczenia z nadzorem—Kalibracja, dyskryminacja i klasyfikacja [methods of learning with supervision—Calibration, discrimination and classification] In: Zuba D., Parczewski A., editors. Chemometria w Analityce. Wydawnictwo Instytut Ekspertyz Sądowych; Kraków, Poland: 2008. pp. 34–36.
Ranganathan P., Pramesh C.S., Buyse M. Common pitfalls in statistical analysis: Clinical versus statistical significance. Perspect. Clin. Res. 2015;6:169–170. doi: 10.4103/2229-3485.159943. PubMed DOI PMC
Steyerberg E. Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating. 1st ed. Springer; New York, NY, USA: 2009.
Team R. Rstudio: Integrated Development for R. RStudio Inc.; Boston, MA, USA: 2015. [(accessed on 19 April 2019)]. 1.1.463. Available online: http://www.Rstudio.Com/
Team R.C. A language and Environment for Statistical Computing. R Foundation for Statistical Computing; Vienna, Austria: 2018. [(accessed on 19 April 2019)]. Available online: https://www.R-project.Org./
Lunardon N., Menardi G., Torelli N. Rose: A package for binary imbalanced learning. R J. 2014;6:79–89. doi: 10.32614/RJ-2014-008. DOI
Therneau T., Atkinson B. [(accessed on 19 April 2019)];Rpart: Recursive Partitioning and Regression Trees. R Package Version 4.1-13. 2018 Available online: https://cran.R-project.Org./package=rpart.
Bossuyt P.M., Reitsma J.B., Bruns D.E., Gatsonis C.A., Glasziou P.P., Irwig L., Lijmer J.G., Moher D., Rennie D., de Vet H.C., et al. Stard 2015: An updated list of essential items for reporting diagnostic accuracy studies. Radiology. 2015;277:826–832. doi: 10.1148/radiol.2015151516. PubMed DOI
Ledermann J.A., Raja F.A., Fotopoulou C., Gonzalez-Martin A., Colombo N., Sessa C., Group E.G.W. Newly diagnosed and relapsed epithelial ovarian carcinoma: Esmo clinical practice guidelines for diagnosis, treatment and follow-up. Ann. Oncol. 2013;24:vi24–vi32. doi: 10.1093/annonc/mdt333. PubMed DOI