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Journal of Clinical Oncology, Vol 25, No 4 (February 1), 2007: pp. 384-389 © 2007 American Society of Clinical Oncology. DOI: 10.1200/JCO.2006.07.7800 Multi-Institutional Reciprocal Validation Study of Computed Tomography Predictors of Suboptimal Primary Cytoreduction in Patients With Advanced Ovarian Cancer
From the University of California Los Angeles (UCLA) Medical Center; Olive View-UCLA Medical Center; Cedars-Sinai Medical Center; Kaiser Permanente Sunset Medical Center, Los Angeles, CA; Johns Hopkins Medical Institutions, Baltimore, MD; and the Mayo Clinic, Rochester, MN Address reprint requests to Christine H. Holschneider, MD, Olive View-UCLA Medical Center, Department of Obstetrics and Gynecology, 14445 Olive View Dr, Rm 2B-163, Sylmar, CA 91342; e-mail: CHolschneider{at}ladhs.org
Purpose: Identify features on preoperative computed tomography (CT) scans to predict suboptimal primary cytoreduction in patients treated for advanced ovarian cancer in institution A. Reciprocally cross validate the predictors identified with those from two previously published cohorts from institutions B and C. Patients and Methods: Preoperative CT scans from patients with stage III/IV epithelial ovarian cancer who underwent primary cytoreduction in institution A between 1999 and 2005 were retrospectively reviewed by radiologists blinded to surgical outcome. Fourteen criteria were assessed. Crossvalidation was performed by applying predictive model A to the patients from cohorts B and C, and reciprocally applying predictive models B and C to cohort A.
Results: Sixty-five patients from institution A were included. The rate of optimal cytoreduction ( Conclusion: The high accuracy rates of CT predictors of suboptimal cytoreduction in the original cohorts could not be confirmed in the cross validation. Preoperative CT predictors should be used with caution when deciding between surgical cytoreduction and neoadjuvant chemotherapy.
Ovarian cancer remains the leading cause of mortality from a gynecologic malignancy in the United States with 16,210 deaths annually.1 The majority of cases are advanced stage (stage III/IV) at the time of diagnosis. Current front-line therapy consists of cytoreductive surgery and platinum-based chemotherapy.
Optimal primary cytoreduction has been demonstrated for the past 30 years to be a highly significant predictor of outcome in patients with advanced ovarian cancer. A recent meta-analysis of maximal cytoreduction and survival in 81 published patient cohorts demonstrated that cohorts in which there was a high proportion of maximal cytoreduction (> 75%) had a 50% increase in median survival compared with those with a less than 25% maximal cytoreduction rate (33.9 v 22.7 months).2 A higher response rate to chemotherapy and improved survival in patients with optimal cytoreduction, defined by residual disease For women with advanced ovarian cancer, rates of optimal primary cytoreduction vary widely from 25% to more than 90%.6 GOG data have demonstrated that women whose tumors cannot be cytoreduced to smaller than 2 cm residual disease do not derive any significant survival benefit from primary cytoreductive surgery.7 Thus, patients who undergo suboptimal primary cytoreduction may incur significant surgical morbidity without associated gain in survival. This has prompted investigations into neoadjuvant chemotherapy. Several trials have demonstrated decreased operative morbidity8 and improved maximal tumor debulking rates at interval cytoreduction after neoadjuvant chemotherapy.9-15 To date, there are no published randomized trials that compare survival in patients who receive neoadjuvant chemotherapy with interval cytoreduction versus those who undergo primary cytoreduction followed by chemotherapy. A European Organisation for Research and Treatment of Cancer trial is currently underway, which addresses this question.16 An extensive review of retrospective and nonrandomized prospective studies of neoadjuvant chemotherapy versus primary cytoreduction suggests improved median survival with neoadjuvant chemotherapy over that observed in patients who underwent suboptimal primary cytoreduction (26 months v 20 months).6 However, in the literature available to date, survival of patients treated with neoadjuvant chemotherapy appears inferior to that observed after optimal primary cytoreduction (26 months v 51 months).6 Thus, the accurate pretreatment identification of patients whose disease is not optimally cytoreducible at primary surgery becomes one of the most critical issues surrounding neoadjuvant chemotherapy for ovarian cancer. Investigators have attempted to identify specific preoperative predictors of suboptimal cytoreduction. A number of studies have demonstrated an association between the preoperative CA-125 level and the inability to achieve optimal cytoreduction, yet the overall accuracy rates at predicting surgical outcome (ie, optimal v suboptimal cytoreduction) were only 50% to 78% with most studies using a CA-125 cut off value of 500 U/mL.17-23 The two series with high optimal cytoreduction rates (> 70%) found preoperative CA-125 levels completely lacking as predictors of surgical outcome.20-22 Five small studies have been published to date,22,24-27 which have attempted to identify specific radiological predictors of suboptimal cytoreduction on preoperative computed tomography (CT) scans. For example, Bristow et al26 created a model including 13 radiographic features and performance status to calculate predictive index scores with a 93% accuracy rate for optimal versus suboptimal primary debulking. Dowdy and colleagues22 found only diffuse peritoneal thickening to be an independent predictor of suboptimal surgical cytoreduction. Interpretation of these studies published to date is limited due to their retrospective nature, the highly variable rates of optimal cytoreduction (33% to 80%), the fact that most2,24,25,27 included patients with both early and advanced stage disease, and the quite different combination of CT predictors that correlated with suboptimal cytoreduction in each of the study cohorts; the latter calling into question the applicability of identified CT predictors to other patient populations. We therefore undertook the current study with the following two objectives: to identify radiologic features on preoperative CT scans that predict suboptimal primary cytoreduction in a specific cohort of patients with advanced stage (III/IV) ovarian cancer treated at University of California, Los Angeles (Los Angeles, CA) and associated teaching institutions, where the surgical practice is characterized by a strong commitment to optimal primary cytoreduction (cohort A); and to reciprocally cross validate the CT predictors identified in cohort A with those from two previously published cohorts of patient with stage III/IV ovarian cancer who underwent primary cytoreduction at Johns Hopkins Medical Institute26 (Baltimore, MD; cohort B) or the Mayo Clinic22 (Rochester, MN; cohort C).
Objective 1 Institutional review board approval of the study protocol was obtained from all participating institutions. Patients who underwent primary surgery for stage III and stage IV epithelial ovarian cancer between 1999 and 2005 at one of four teaching institutions affiliated with the University of California, Los Angeles Gynecologic Oncology training program (patient cohort A) were identified through pathology databases and institutional tumor registries. Only patients who had preoperative CT scans performed within 4 weeks before primary cytoreductive surgery and whose CT films were available for review were included in the study.
CT scanning protocols varied given the inclusion of four different institutions. In general, all images were obtained using 5 mm to 10 mm collimation through the abdomen and pelvis with PO and IV contrast unless the latter was medically contraindicated. Patients whose preoperative CT scans had been performed at outlying institutions were not eligible for this study given the large variation in the imaging techniques used and the fact that images had generally been returned to the originating institution. CT scans performed at the study institutions were systematically re-reviewed by study radiologists who were blinded to surgical outcomes. Fourteen radiologic criteria were chosen from pertinent positive predictors gathered from previous studies22,26 and supplemented with potential predictors from clinical experience. These criteria included large volume ascites, pleural effusion, diffuse peritoneal thickening, omental caking, omental extension to spleen or stomach, suprarenal lymph nodes larger than 1 cm, infrarenal or inguinal lymph nodes larger than 2 cm, and tumor implants larger than 2 cm on small and large bowel mesentery, peritoneum, diaphragm, liver, or porta hepatis. Large volume ascites was defined as the presence of ascites on two thirds of abdominopelvic CT scan cuts. Diffuse peritoneal thickening was defined as peritoneal thickening to
Demographic data, surgical findings, and pathologic data were retrospectively obtained from the medical record. All surgeries were performed by one of 12 gynecologic oncologists at one of the four study institutions. Optimal cytoreduction was defined as Univariate comparisons of the percentage of patients who underwent suboptimal cytoreduction were carried out using Fisher's exact tests for each of the 14 potential radiologic predictors. The Wilcoxon rank sum test was used to compare median age, albumin, ASA status, and CA-125 levels between patients with optimal versus suboptimal cytoreduction. The Kruskal-Wallis test was used to study the association between increasing ASA classification and the proportion of patients with suboptimally cytoreduced ovarian cancer. Simultaneous multivariate assessment of all 14 radiologic and four clinical variables was carried out using backward stepwise logistic regression with a liberal P < .15 variable retention criterion and a model predictive of suboptimal cytoreduction was developed (predictive model A). Sensitivity, specificity, and accuracy of the model were calculated based on receiver operating curve analysis. Stratification of the data by surgeon and/or procedures performed would have been desirable since optimal cytoreduction depends in part on the surgeon's practice, philosophy, and skill set. However, in this study, the number of patients per surgeon and/or per radical surgical technique was too small to allow for a stratified analysis. In order to safeguard against statistical overfitting, we performed a leave one out (statistical) cross validation. In short, an observation was left out of the data set, the process of identifying (variable selection) and fitting the model was performed on all the remaining data, and then the fitted model was used to predict the probability of a suboptimal cytoreduction for the observation left out. These steps were repeated for each observation in the data set, a receiver operating curve curve was formed, and resultant sensitivity, specificity, and accuracy reported.
Objective 2
Sixty-five consecutive patients from institution A met study inclusion criteria. Demographic and clinical data are described in Table 1. Eighty-eight percent of patients had International Federation of Gynecology and Obstetrics staging system (FIGO) stage III disease while 12% of patients had FIGO stage IV disease. Fifty-one patients (78%) were optimally cytoreduced to  1 cm residual disease at the time of primary surgery.
There were no statistically significant differences between the median age (optimal: 62 years; range, 33 to 82 years; suboptimal: 56 years; range, 34 to 87 years; P = .92), ASA status (optimal: 2; range, 2 to 4; suboptimal: 3; range, 2 to 4; P = .12), serum albumin (optimal: 3.5 g/dL; range, 2.2 to 4.7 g/dL; suboptimal, 3.4 g/dL; range, 2.7 to 4.0 g/dL; P = .62) and CA-125 levels (optimal: 860 U/mL; range, 15 to 7,960 U/mL; suboptimal: 780 U/mL; range, 105 to 2,866 U/mL); P = .42) of individuals who were optimally cytoreduced when compared with those who were suboptimally debulked. An association was noted between the ASA classification and the proportion of patients who underwent suboptimal cytoreduction, but this did not reach statistical significance: 13% of patients with an ASA classification of 2 underwent suboptimal cytoreduction, this increased to 25% with an ASA class of 3 and to 40% with an ASA classification of 4 (P = .12). Table 2 presents the percentage of patients who underwent suboptimal debulking for each of the 14 preoperative CT variables. Diaphragmatic disease larger than 2 cm (P < .02) and large bowel mesentery implants larger than 2 cm (P < .02) were the only statistically significant univariate predictors of suboptimal cytoreduction. Forty-seven percent of women who were positive for diaphragm disease and 50% of those with disease of the large bowel mesentery on preoperative CT scan were suboptimally debulked.
All 14 radiologic and four clinical criteria were candidates for predicting suboptimal debulking in the backward multivariate logistic analysis. Of these 18 potential predictors, the logistic regression identified only diaphragm disease (risk ratio [RR], 5.69; P = .01) and large bowel mesentery implants (RR, 6.07; P = .011) as significant predictors of suboptimal cytoreduction. While ASA status and omental extension to stomach and spleen demonstrated borderline significance on univariate analysis, they lost any trend toward significance on multivariate analysis. Using a model where only the presence of both diaphragm disease and large bowel mesentery implants is considered predictive of suboptimal cytoreduction (predictive model A), the nominal sensitivity was 79%, the specificity was 75%, and the accuracy was 77% in patient cohort A. These nominal sensitivity, specificity, and accuracy rates were confirmed by a leave one out statistical validation. In this analysis, both diaphragm disease and large bowel mesentery implants continued to be the only significant predictors. Across the 65 runs the mean sensitivity for suboptimal cytoreduction was 78.6% (95% CI, 56.6% to 100%), the mean specificity was 74.5% (95% CI, 62.5 to 86.5%), and the mean accuracy was 76.5% (95% CI, 51.5% to 100%). Those patients with no disease on the diaphragm or large bowel mesentery had the lowest rates of suboptimal cytoreduction (7%), patients with one, but not both risk factors had intermediate rates of suboptimal cytoreduction (42% to 44%), whereas those with both diaphragm and large bowel mesentery implants on preoperative CT had the highest rates of suboptimal cytoreduction (67%). Thus, patients with both CT predictors were 9.11 times more likely to be suboptimally debulked than those with neither predictor (Table 3).
In order to study the applicability of our thus identified CT predictors of suboptimal cytoreduction to other patient cohorts, we applied predictive model A to patient cohorts B and C (Table 4). The resultant sensitivity of predictive model A fell to 15% and 72%, specificity to 32% and 56%, and accuracy to 34% and 64% when applied to patient cohorts B and C, respectively. For reciprocal cross validation, we applied the CT predictors previously identified in patient cohorts B (predictive model B) and C (predictive model C) to the present patient cohort A (Table 5). When CT predictor models B and C were applied to patient cohort A, the original accuracy rates of 93% and 79% fell to 74% and 48%, respectively. The CT predictors identified in three additional studies in the literature were not used as primary outcome measure for cross validation as the original study cohorts included early-stage ovarian cancer.23,24,26 However, when the predictors from these three studies were applied to cohort A for comparison purposes, a similar loss in accuracy was observed from 79% to 88% in the original cohorts to 51% to 62% in cohort A. In other words, 64% to 86% of patients in cohort A predicted to undergo suboptimal cytoreduction using any of the five published models were actually optimally cytoreduced.
Our current study identifies diaphragm disease and large bowel mesentery implants as being the only statistically significant predictors of suboptimal cytoreduction. Despite this statistical significance, the clinical relevance of this finding remains questionable because approximately half of our own patients whose preoperative CT scans were positive for either of these predictors actually underwent optimal cytoreduction at the time of primary surgery. Even when applying our multivariate model, which required the presence of both, diaphragm disease and disease of the large bowel mesentery on the preoperative CT scan in order to be predictive of suboptimal cytoreduction, there was still a 33% false positive rate. Despite optimizing our model, one of every three patients predicted to undergo suboptimal tumor debulking could actually be left with minimal residual disease after operation with therapeutic intent. If we had followed our CT predictor model, each of these patients would have been deprived of the potential survival advantage associated with optimal primary cytoreductive surgery. As becomes evident from the review of all published CT predictor data to date, each of the retrospective studies,22,24-27 including our own, identified a different set of predictors of cytoreductive surgery outcome, raising the question as to their applicability to patient cohorts other than the one they were developed in. The lack of generalizability of any of the CT predictive models identified to date is illustrated by our cross validation studies. Reciprocal accuracy rates in the validation cohorts were poor across all models and cohorts studied. Most importantly, there was an unacceptable overprediction of suboptimal cytoreduction in the reciprocal cross validation scenarios of 64% to 86%. Which is to say that 64% to 86% of those patients predicted in the cross validation cohorts to undergo suboptimal cytoreduction using any of the published prediction models actually underwent optimal primary tumor cytoreduction, leaving the patient with minimal residual disease. This high rate of overcall of suboptimal cytoreduction by CT predictors becomes particularly concerning in light of the well-documented survival advantage associated with intraperitoneal chemotherapy in patients with optimally cytoreduced cancer,5,28,29 especially when juxtaposed to data from a recent meta-analysis of neoadjuvant chemotherapy which suggests a 4.1-month reduction in survival for each cycle of chemotherapy given before surgical tumor debulking.30 One of the principle difficulties in the development of any reliable predictive model of surgical outcome for patients with advanced ovarian cancer is the challenge of factoring in the significant impact of each individual surgeon's philosophy, effort, and ability to utilize advanced surgical techniques to achieve maximal cytoreduction.31 Subset analysis of the suboptimally debulked patients by individual surgeon was not possible in our study due to the low number of patients with suboptimal cytoreduction for each of the 12 surgeons in institution cluster A. However, an overall optimal cytoreduction rate of 78% in patient cohort A is an attestation to the surgical practice at University of California, Los Angeles and affiliated teaching institutions that is characterized by a strong commitment to optimal primary cytoreduction and the inclusion of advanced surgical techniques in the surgeon's armamentarium to achieve resection of the tumor. In summary, identification of risk factors for suboptimal cytoreduction in small retrospective populations such as ours and all previously published cohorts, are not reproducible in alternate populations. Until prospective, randomized trials have demonstrated that neoadjuvant chemotherapy followed by interval cytoreduction is equivalent in terms of survival outcomes to primary optimal cytoreduction followed by chemotherapy, extreme caution should be used when applying preoperative imaging predictors to decide between primary surgical exploration and neoadjuvant chemotherapy in the medically fit patient. Only the patient who is the most unlikely to undergo optimal cytoreduction should be offered neoadjuvant chemotherapy, unless her medical condition renders her unsuitable for primary surgery. Ultimately, only a multi-institutional prospective trial would answer the question of whether or not an accurate and reproducible preoperative model using CT or other imaging modalities could be developed for the prediction of surgical outcome. Such a model would have to take into consideration the impact of variable surgical practices and the surgeon's philosophical commitment to aggressive tumor debulking and skills in advanced cytoreductive surgical techniques.
The authors indicated no potential conflicts of interest.
Conception and design: Allison E. Axtell, Margaret H. Lee, Christine H. Holschneider Administrative support: Allison E. Axtell, Christine H. Holschneider Provision of study materials or patients: Robert E. Bristow, Sean C. Dowdy, William A. Cliby, Scott Lentz, Andrew J. Li, Beth Y. Karlan, Christine H. Holschneider Collection and assembly of data: Allison E. Axtell, Margaret H. Lee, Steven Raman, John P. Weaver, Mojan Gabbay, Michael Ngo, Ilana Cass, Christine H. Holschneider Data analysis and interpretation: Allison E. Axtell, Robert E. Bristow, Sean C. Dowdy, William A. Cliby, Steven Raman, John P. Weaver, Scott Lentz, Ilana Cass, Andrew J. Li, Beth Y. Karlan, Christine H. Holschneider Manuscript writing: Allison E. Axtell, Robert E. Bristow, Sean C. Dowdy, William A. Cliby, Christine H. Holschneider Final approval of manuscript: Allison E. Axtell, Margaret H. Lee, Robert E. Bristow, Sean C. Dowdy, William A. Cliby, Steven Raman, John P. Weaver, Mojan Gabbay, Michael Ngo, Scott Lentz, Ilana Cass, Andrew J. Li, Beth Y. Karlan, Christine H. Holschneider
We thank Jeffrey Gornbein, PhD, Department of Biostatistics, David Geffen School of Medicine at University of California, Los Angeles, for assistance with the statistical analysis.
Presented in part during plenary presentations at the 34th Annual Meeting of the Western Association of Gynecologic Oncologists, Santa Fe, NM, June 15-18, 2005; and at the 37th Annual Meeting of the Society of Gynecologic Oncologists, Palm Springs, CA, March 22-26, 2006. Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.
1. American Cancer Society. Cancer Facts & Figures 2005. http://www.cancer.org/downloads/STT/CAFF2005f4PWSecured.pdf 2. Bristow RE, Tomacruz RS, Armstrong DK, et al: Survival effect of maximal cytoreductive surgery for advanced ovarian carcinoma during the platinum era: A meta-analysis. J Clin Oncol 20:1248-1259, 2002 3. McGuire WP, Hoskins WJ, Brady MF, et al: Cyclophosphamide and cisplatin compared with paclitaxel and cisplatin in patients with stage III and stage IV ovarian cancer. N Engl J Med 334:1-6, 1996 4. Ozols RF, Bundy BN, Greer BE, et al: Phase III trial of carboplatin and paclitaxel compared with cisplatin and paclitaxel in patients with optimally resected stage III ovarian cancer: A Gynecologic Oncology Group study. J Clin Oncol 27:3194-3200, 2003 5. Armstrong DK, Bundy B, Wenzel L, et al: Intraperitoneal cisplatin and paclitaxel in ovarian cancer. N Engl J Med 354:34-43, 2006 6. Holschneider CH, Berek JS: Cytoreductive surgery: Principles and rationale, in Bristow RE, Karlan BY, Montz FJ (eds): Surgery for Ovarian Cancer: Principles and Practice. Lancaster, United Kingdom, The Parthenon Publishing Group, 2005, pp 141-143 7. Hoskins WJ, McGuire WP, Brady MF, et al: The effect of diameter of largest residual disease on survival after primary cytoreductive surgery in patients with suboptimal residual epithelial ovarian carcinoma. Am J Obstet Gynecol 170:974-979, 1994[Medline] 8. Schwartz PE, Rutherford TJ, Chambers JT, et al: Neoadjuvant chemotherapy for advanced ovarian cancer: Long term survival. Gynecol Oncol 72:93-99, 1999[CrossRef][Medline] 9. Kayikciog F, Rose MF, Boran N, et al: Neoadjuvant chemotherapy or primary surgery in advanced epithelial ovarian cancer. Int J Gynecol Cancer 11:466-470, 2001[CrossRef][Medline] 10. 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Kuhn W, Rutke S, Spathe K, et al: Neoadjuvant chemotherapy followed by tumor debulking prolongs survival for patients with poor prognosis in International Federation of Gynecology and Obstetrics stage IIIC ovarian carcinoma. Cancer 92:2585-2591, 2001[CrossRef][Medline] 15. Vergote I, DeWever I, Tjalma W, et al: Neoadjuvant chemotherapy or primary debulking surgery in advanced ovarian carcinoma: A retrospective analysis of 285 patients. Gynecol Oncol 71:431-436, 1998[CrossRef][Medline] 16. European Organization for Research and Treatment of Cancer: Randomized phase III study comparing upfront debulking surgery versus neo-adjuvant chemotherapy in patients with stage IIIc or IV epithelial ovarian cancer (EORTC protocol 55971). http://www.eortc.be/protoc/Details.asp?Protocol=55971 17. Chi DS, Venkatraman ES, Masson V, et al: The ability of preoperative serum CA-125 to predict optimal primary tumor cytoreduction in stage III epithelial ovarian carcinoma. Gynecol Oncol 77:227-231, 2000[CrossRef][Medline] 18. Gemer O, Segal S, Kopmar A, et al: Preoperative CA-125 level as a predictor of non-optimal cytoreduction of advanced epithelial ovarian cancer. Acta Obstet Gynecol Scand 80:583-585, 2001[CrossRef][Medline] 19. Saygili U, Guclu S, Uslu T, et al: Can serum CA-125 levels predict the optimal primary cytoreduction in patients with advanced ovarian carcinoma? Gynecol Oncol 86:57-61, 2002[CrossRef][Medline] 20. Cooper BC, Sood AK, Davis CS, et al: Preoperative CA-125 levels: An independent prognostic factor for epithelial ovarian cancer. Obstet Gynecol 100:59-64, 2002 21. Memarzadeh S, Lee SB, Berek JS, et al: CA-125 levels are a weak predictor of optimal cytoreductive surgery in patients with advanced epithelial ovarian cancer. Int J Gynecol Cancer 13:120-124, 2003[CrossRef][Medline] 22. Dowdy SC, Mullany SA, Brandt KR, et al: The utility of computed tomography scans in predicting suboptimal cytoreductive surgery in women with advanced ovarian carcinoma. Cancer 101:346-352, 2004[CrossRef][Medline] 23. Brockbank EL, Ind TE, Barton DP, et al: Preoperative predictors of suboptimal primary surgical cytoreduction in women with clinical evidence of advanced primary epithelial ovarian cancer. Int J Gynecol Cancer 14:42-50, 2004[CrossRef][Medline] 24. Nelson BE, Rosenfield AT, Schwartz PE: Preoperative abdominopelvic computed tomographic prediction of optimal cytoreduction in epithelial ovarian carcinoma. J Clin Oncol 11:166-172, 1993[Abstract] 25. Meyer JI, Kennedy AW, Friedman R, et al: Ovarian carcinoma: Value of CT in predicting success of debulking surgery. Am J Roentgenol 165:875-878, 1995 26. Bristow RE, Duska LR, Lambrou NC, et al: A model for predicting surgical outcome in patients with advanced ovarian carcinoma using computed tomography. Cancer 89:1532-1540, 2000[CrossRef][Medline] 27. Qayyum A, Coakley FV, Westphalan AC, et al: Role of CT and MRI imaging in predicting optimal cytoreduction of newly diagnosed primary epithelial ovarian cancer. Gynecol Oncol 96:301-306, 2005[CrossRef][Medline] 28. Alberts DS, Liu PY, Hannigan EV, et al: Intraperitoneal cisplatin plus intravenous cyclophosphamide versus intravenous cisplatin plus intravenous cyclophosphamide for stage III ovarian cancer. N Engl J Med 335:1950-1955, 1996 29. Markman M, Bundy BN, Alberts DS, et al: Phase III trial of standard-dose intravenous cisplatin plus paclitaxel versus moderately high-dose carboplatin followed by intravenous paclitaxel and intraperitoneal cisplatin in small-volume stage III ovarian carcinoma: An intergroup study of the Gynecologic Oncology Group, Southwestern Oncology Group, and Eastern Cooperative Oncology Group. J Clin Oncol 19:1001-1007, 2001 30. Bristow RE, Chi DS: Platinum-based neoadjuvant chemotherapy and interval cytoreduction for advanced ovarian cancer: A meta-analysis. Gynecol Oncol 103:1070-1076, 2006[CrossRef][Medline] 31. Aletti GD, Gostout BS, Podratz KC, et al: Ovarian cancer surgical resectability: Relative impact of disease, patient status, and surgeon. Gynecol Oncol 100:33-37, 2006[CrossRef][Medline] Submitted June 7, 2006; accepted November 17, 2006. This article has been cited by other articles:
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Copyright © 2007 by the American Society of Clinical Oncology, Online ISSN: 1527-7755. Print ISSN: 0732-183X
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ABSTRACT
INTRODUCTION
4 mm involving at least two of the five following areas: lateral colic gutters, lateral conal fascia, anterior abdominal wall, diaphragm, and pelvic peritoneal reflections, as described by Dowdy.
