Ovarian cancer is the sixth most common cancer and the seventh cause of death from cancer in women worldwide. Incidence rates are highest in developed countries, being the second most common and the most lethal gynecological malignancy in the United States and with a relatively frequent incidence in South America (7.7 per 100,000).1–3
The overall poor prognosis can be explained by the fact that 63% to 75% of the patients present at an advanced stage, defined as International Federation of Gynecologists and Obstetricians (FIGO) stage III or IV. Patients who present at an advanced stage have a 5-year survival rate of approximately 25% compared with an 80% to 90% survival in patients with early-stage ovarian cancer.4,5 Treatment, based on optimal cytoreduction surgery to <1 cm residual disease plus the administration of paclitaxel and platinum-based chemotherapy, is regarded as the “gold standard” in advanced-stage ovarian cancer.2,5–9
Cancer patients are immunosuppressed as a result of their disease and the use of cytotoxic treatment. On the contrary, surgery itself creates profound metabolic, neuroendocrine, inflammatory, and immunological stress.10,11 Natural killer cell activity plays a critical role in determining outcome after potentially curative surgery.11 Regional anesthesia, including epidural and spinal anesthesia, not only provides pain relief sparing the use of opioids but also attenuates surgery-induced activation of the sympathetic nervous and neuroendocrine systems, reducing perioperative immunosuppression.12–15 Mixed evidence has been published relating the use of regional anesthesia during oncologic surgery to a decrease in time to cancer recurrence and an improvement on cancer-related survival.15–21 Our objective was to determine whether the use of epidural anesthesia, in addition to general analgesia during and/or after surgical resection of advanced ovarian cancer, has an impact on time to recurrence and overall survival.
This study was approved by the ethics committee of the School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile. Patients were identified from a prospective clinical registry maintained by the Division of Gynecologic Oncology under care of J. Brañes, MD. The anesthesia records of all de novo FIGO stage IIIC (peritoneal metastases beyond pelvis of >2 cm or lymph node metastases) and IV (distant metastases to the liver or outside the peritoneal cavity) cases undergoing surgery for ovarian cancer between January 2000 and March 2011 were reviewed. We selected FIGO stage IIIC and IV patients due to the similar clinical prognosis reported in the literature compared with patients with early-stage ovarian cancer.22
From the database, we extracted patients’ demographic characteristics and cancer-related factors that consistently have shown to play a role in survival2,6,23,24: preoperative carcinoantigen 125 levels, FIGO staging, tumor cell type, chemotherapy received, and the quality of cytoreduction. Optimal cytoreduction is defined as residual tumor lesions ≤1 cm in maximum diameter,2 ideally with no gross residual disease.25 Anesthesia technique, ASA physical status, estimated intraoperative blood loss, blood products usage, and surgical duration data were extracted from the patients’ anesthesia records. Follow-up assessments were conducted at 3-month intervals for the first 2 years, followed by assessments every 6 months for 3 years, and then annually. Cancer recurrence was determined by clinical symptoms at follow-up or spontaneous consult. Recurrence was confirmed by a carcinoantigen 125 more than 2 times the documented nadir value or from a computerized tomography scan showing evidence of disease.
All patients included in this study were scheduled for exploratory laparotomy and received general anesthesia for the surgical procedure. The technique used in every case was inhaled anesthesia plus IV fentanyl dosed according to hemodynamic and clinical variables as determined by the attending anesthesiologist. Muscle relaxation was achieved with a nondepolarizing drug guided by clinical need. Among patients who received an epidural anesthetic, the catheter was inserted at the T10 to L1 level, and intermittent bolus doses of a mixture of local anesthetics (bupivacaine 0.1%–0.5%) with or without fentanyl were administered during surgery, if permitted by the clinical status. The decision to place an epidural catheter was made by the attending anesthesiologist, taking into consideration the preference and clinical status of the patient. Contraindications to catheter placement were patient refusal, coagulation disorders, and anatomical abnormalities limiting epidural placement.
All patients received 30 mg ketorolac IV every 8 hours for postoperative analgesia, unless contraindicated. For patients receiving epidural catheters, a mixture of local anesthetics and opioids was delivered via patient-controlled epidural analgesia. Those without an epidural catheter received opioid-based IV analgesia with morphine by IV patient-controlled analgesia or continuous infusions of tramadol with morphine as rescue analgesic. Postoperative IV and epidural analgesia were managed by the acute pain service of the Department of Anesthesiology. All epidural catheters remained in place for at least 48 hours, and the infusion was adjusted to achieve visual analog scale scores <4 on a scale ranging from 0 = no pain to 10 = worst pain ever experienced.
Differences in baseline characteristics between patients who received epidural anesthesia and/or analgesia (EA) and those who did not receive EA (group no EA) were evaluated using χ2 test or Fisher exact test for inference on the proportions and Wilcoxon rank sum test for continuous variables. Time to recurrence and overall survival were calculated from the date of the surgery to recurrence or death due to cancer, respectively. Those patients who did not experience the event of interest before March 5, 2012, or those lost to follow-up were classified as censored observations.
Since propensity score (PS) estimates are less biased than regression estimates when the number of adjustment factors is large relative to the number of events, we used the former technique to control for differences in baseline characteristics. PS is the conditional probability of receiving an exposure (e.g., receiving EA) given a set of measured covariates.26 To estimate the PS, a logistic regression model was used in which treatment status (EA versus no EA) was regressed on the baseline (pretreatment) characteristics listed in Table 1, with the respective P values pre- and post-PS match. In our study, all patients were scheduled for exploratory laparotomy; however, optimal cytoreduction (R0) was not a guaranteed result. Since R0 is a well-known predictor of survival in advanced ovarian cancer, and also could have been related to the probability of receiving an epidural (e.g., if a surgeon predicted that the likelihood of achieving R0 is high during the preoperative setting, it would be more likely that the surgeon requested an epidural), we also included this variable to estimate the PS. Moreover, trying to control for changes in surgical techniques during the study period, the variable “surgeon” was also included.
Chemotherapy was given concomitant to or after surgery and is thus independent of the exposure status (receiving EA) but closely related to the survival outcome. Therefore, the variable was not included in the estimation of the PS. Instead, we conducted a secondary analysis adjusting for chemotherapy.
PS analysis was implemented in 2 ways to control for confounding27:
- PS matching: We performed the matching using a one-to-one nearest neighbor caliper matching with replacement with a caliper size of 0.2 standard deviations (R library “MatchIT”).28 Balances in the distribution of baseline covariates were assessed by estimating absolute standardized differences of the covariates between the 2 groups before and after matching27,29 and using the method suggested by Hansen and Bowers30 (R library “RItools”). As the PS-matched sample does not consist of independent observations, we used a marginal survival model with robust standard errors.31
- PS weighting: We weighted the entire sample by the inverse probability of the treatment weights derived from the PS. If a subject had a higher probability of being in a group, it was considered overrepresented and therefore was assigned a lower weight. Conversely, if the subject had a smaller probability, it was considered as underrepresented and was assigned a higher weight.29,32 We then fit a weighted Cox proportional hazards model using an indicator variable representing EA status as the sole predictor.
Kaplan–Meier survival curves were estimated for time to recurrence and time to death due to cancer. We performed logrank and stratified logrank tests for the matched pairs data.33
Finally, a new model was created using a more liberal approach. A stepwise logistic regression with P ≤ 0.15 as cutoff for selecting variables was used to reestimate a less stringent second PS model. Using this scenario, the variables surgical duration and optimal cytoreduction were used for the calculation, instead of those presented in Table 1. We then weighted the entire sample by the inverse probability of the treatment weights derived from this new PS. The analyses were performed using STATA/SE v.10.1 (StataCorp LP, College Station, TX) and R v. 2.11.1 (http://www.R-project.org, The R Project for Statistical Computing, Vienna, Austria).
The medical records of 89 patients with de novo diagnosis of ovarian cancer that met inclusion criteria and underwent surgery between January 2000 and March 2011 were reviewed. Nine patients were excluded from the analysis due to incomplete documentation of the anesthesia technique. The median follow-up time was 4.9 (interquartile range: 2.5–9.8) years.
Among the 80 patients studied, 39 had an epidural catheter placed. In 2 patients, the epidural catheter was never used; in one case, the catheter was intravascular, and in the other, the anesthesiologist in charge decided not to use the catheter because the patient was too unstable. To avoid misclassification bias, these 2 latter cases were included in the group without EA in the analysis (Fig. 1). Of the 37 patients remaining in the EA group, 30 received epidural anesthesia as part of a balanced anesthetic technique as well as postoperatively for pain control, while the 7 remaining patients received epidural analgesia only during the postoperative period.
The baseline characteristics of the study cohort are listed in Table 1. Patients who received EA were more likely to have a longer surgery (P = 0.04), tended to have more optimal cytoreduction (P = 0.05), and received paclitaxel plus platinum-based chemotherapy more often (P = 0.06). Except for the use of chemotherapy, which was not included in the PS model, all covariates were well balanced between groups after adjusting for PS (Table 1). We were able to match 35 patients from the EA group with 20 patients from the no EA group.
Time to Recurrence
The left panel of Figure 2 displays the unadjusted Kaplan–Meier curves for time to recurrence of ovarian cancer in the EA and no EA groups. The median time to recurrence was 1.6 and 0.9 years for the EA and no EA group, respectively (P = 0.02). After PS matching, the median time to recurrence was 1.6 and 1.4 years for the EA and no EA group, respectively, as displayed in the right panel of Figure 2 (P = 0.30). Similarly, PS weighting did not demonstrate an improved recurrence time with the use of EA (Fig. not shown).
Using a Cox proportional hazards model in the PS-matched sample, the estimated hazard ratio for EA exposure (0.72; 95% confidence interval [CI], 0.40–1.33) did not change substantially after adjusting for chemotherapy (0.73; 95% CI, 0.40–1.31). Similar results were obtained using PS weighting (full and with 2 covariates, Table 2).
In this sample, all deaths were attributed to cancer. The left panel of Figure 3 shows the unadjusted Kaplan–Meier survival curves for the EA and no EA groups. The median survival time was 3.3 and 1.9 years for the EA and no EA group, respectively (P = 0.01). After PS matching, the median survival time was 3.3 and 2.7 years for the EA and no EA group, respectively (right panel Fig. 3, P = 0.37). Similarly, PS weighting did not demonstrate an improved survival with the use of EA (Fig. not shown).
Using a Cox proportional hazards model, the estimated hazard ratio (0.74; 95% CI, 0.36–1.49) in the PS-matched sample did not change substantially after adjusting for chemotherapy. Similar results were obtained using PS weighting (full and with 2 covariates, Table 2).
The role of EA in patients with cancer remains uncertain. Despite the lack of conclusive evidence from randomized trials, in 2006 there was an initial enthusiasm in the medical community when Exadaktylos et al.19 and subsequently Biki et al.16 published their findings that described a benefit on cancer recurrence, metastasis, and biochemical progression in patients after receiving regional anesthesia for cancer surgery (breast and prostate, respectively). The proposed mechanism was a sparing effect in opioid usage, which in acute and chronic use would inhibit components of the cellular and humoral immune function including natural killer cell activity. These effects seemed biologically plausible; however, the retrospective nature of the studies rendered these findings speculative rather than conclusive. Further retrospective reports have suggested similar results of clinical progression in cancer. In studying patients with colon cancer, Christopherson et al.17 concluded that epidural supplementation was associated with enhanced survival among patients without metastases before 1.46 years, having no effect on survival of patients with metastases. Alternatively, Wuethrich et al.21 found only a marginal benefit and reported a reduced risk of clinical cancer progression, with no effect on biochemical recurrence-free survival, cancer-specific survival, or overall survival.
After PS matching and weighting, we were unable to find significant differences in time to recurrence and overall survival between the EA and no EA groups using a prospective database of patients with FIGO stage IIIC and IV ovarian cancer undergoing surgery in our institution. Our findings suggest that EA may offer no survival benefit.
We found only 2 previous reports that investigated the potential association between EA (versus general anesthesia alone) and cancer recurrence time or cancer-specific survival in patients with ovarian cancer. Our study investigated a Latin American population in which optimal cytoreduction was possible in 62% of patients with FIGO stage IIIC and 50% reduction in FIGO stage IV patients; these results are similar to those expected from a gynecologic oncology surgeon.2 Anesthesia techniques are constantly evolving, and special attention is given to all factors linked with cancer recurrence and progression, including the avoidance of intraoperative hypotension, hypothermia, hyperglycemia, and blood products use.13,34 In our institution, control over these factors has been adopted incrementally. As a result, neither group in the current study was systematically affected.
Using a multivariable Cox analysis, Lin et al.20 studied patients with ovarian serous adenocarcinoma undergoing surgery and reported a significant increase in the hazard of subsequent death by 21.4% (P = 0.04) in patients receiving general anesthesia compared with those receiving EA. However, Lin et al.20 excluded a large number of patients from analysis due to inadequate documentation of baseline clinical covariates and/or loss to follow-up (35% of the epidural group and 49% of the general anesthesia group), instead of correctly using imputation techniques35 or right censoring.36 Furthermore, 40% of the cohort analyzed were patients with FIGO stage I (disease confined to the ovaries) and FIGO stage II (metastatic disease confined to the pelvis); these tumors have a drastically different clinical course compared with the more advanced stages.37,38 Even after controlling for FIGO stage, the number of patients excluded from the analysis might have resulted in selection bias.
In a second study, de Oliveira et al.18 investigated the association between intraoperative regional neuraxial anesthesia and time to ovarian cancer recurrence. The authors reported that patients receiving intraoperative epidural anesthesia and postoperative analgesia had a longer time to recurrence than those receiving only postoperative epidural analgesia or no epidural group. Furthermore, acknowledging the importance of FIGO staging, they performed a post hoc analysis including only FIGO stage III patients (58% of the sample). Unable to find a significant difference in time to recurrence between the postoperative epidural analgesia and the intra/postoperative group or the no epidural group, they reported an increase in the mean time to tumor recurrence between the intra/postoperative epidural group (n = 16) and general anesthesia without epidural group (n = 74, P = 0.02—unadjusted for multiple comparisons). Kaplan–Meier estimates of the survival functions are widely used in many clinical studies. In a randomized trial, patients are randomly assigned to different groups with no systematic difference between covariate factors. However, in a nonrandomized clinical trial or an observational study, the treatment assignment may be biased due to some confounding variables; hence, the unadjusted Kaplan–Meier estimator may be inappropriate.32,39–41 As in the de Oliveira et al.18 study, our unadjusted estimator was statistically significant (P = 0.02, left panel of (Fig. 1). The estimator becomes insignificant after PS matching and PS weighting.
One of the strengths of the present report is that all patients had advanced disease, FIGO stage IIIC or IV. Ovarian cancer is a heterogeneous disease composed of different types of tumors with widely differing clinicopathologic features and behavior. Epithelial ovarian cancer is not a single disease, but it is composed of a diverse group of tumors that can be classified based on distinctive morphologic and molecular genetic features. Recently, Kurman and Shih42 grouped together ovarian cancer in type I and II, proposing a unifying theory. Type I is the less aggressive type of ovarian cancer that is usually detected early. Type II is an aggressive and advanced disease, which includes conventional high-grade serous carcinoma, undifferentiated carcinoma, and malignant mixed mesodermal tumors (carcinosarcoma). Accordingly, our sample comprises patients with type II. Survival and recurrence prognosis for these groups are dissimilar. Consequently, type II patients may demonstrate a lesser response to conventional treatment, while interventions that might have some benefits, such as analgesic techniques, may not be demonstrated. Despite the above classification, cytoreductive surgery followed by platinum-based chemotherapy remains the cornerstone of treatment.
Simulation studies have shown that PS estimates are less biased than regression estimates when the number of adjustment factors is large relative to the number of events.43 In addition, since a regression model requires the assumption of linearity in the covariates, the regression adjustment might not account for all confounding factors.44 Numerous retrospective analyses have demonstrated that residual disease status at completion of attempted primary cytoreduction is a strong predictor of survival.23 Since optimal cytoreduction is related to the likelihood of receiving EA, we included that variable in the PS analysis in an attempt to isolate the effect of the neuraxial technique. On the contrary, chemotherapy based on paclitaxel combined with carboplatin is a favored regimen for treating epithelial cell ovarian cancer, being superior to the previous scheme of cisplatin–cyclophosphamide, and demonstrating better overall survival with less toxic reactions.45 Since chemotherapy is independent of epidural status, it does not contribute any information to the PS; therefore, we opted not to include it as a variable in the calculation of the PS and instead conducted a secondary analysis adjusted for chemotherapy status.
Our results suggest that prognosis in advanced cancer disease might not be primarily governed by factors such as immune modulation, cytokine, and influence of other mediators. In advanced stages of cancer, today the best option in controlling progression remains surgery and chemotherapy.2,6 Anesthesia and analgesia techniques are important, but they do not appear to have a significant impact on cancer prognosis in this population.
Several limitations regarding our study are worth noting. Because of the nonrandomized nature of the study, the indication for EA was influenced by patients’ and physicians’ preferences, baseline characteristics, and practice patterns. Consequently, differences in outcomes among patients who did and did not receive an epidural may be explained by confounding. Also, the epidural technique was not homogenous (bupivacaine concentration varied between 0.1% and 0.5% and was administered with or without an opioid), and the information regarding the amount of postoperative morphine given was not available in all medical records. We attempted to address this issue by implementing a PS analysis to balance the treatment groups and controlling for all measured covariates including clinical and tumor characteristics linked to the patients’ prognosis and those related to the likelihood of receiving an epidural. Finally, since we only studied patients with advanced ovarian cancer, this study cannot exclude the potential benefit from neuraxial technique in patients with less advanced disease.
In conclusion, we found no benefit in overall survival or time to recurrence in patients with advanced stages (FIGO IIIC and IV) of ovarian cancer after the use of EA during and/or after debulking surgery. Optimal cytoreduction and platinum-based chemotherapy are still the strongest prognostic factors at this stage of the disease.
Name: Hector J. Lacassie, MD.
Contribution: This author helped design and conduct the study and write the manuscript.
Attestation: Hector J. Lacassie has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
Name: Jaime Cartagena, MD.
Contribution: This author helped design and conduct the study.
Attestation: Jaime Cartagena has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
Name: Jorge Brañes, MD.
Contribution: This author helped design and conduct the study.
Attestation: Jorge Brañes has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
Name: Melissa Assel, MSc.
Contribution: This author helped analyze the data and write the manuscript.
Attestation: Melissa Assel has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
Name: Ghislaine C. Echevarría, MD, MSc.
Contribution: This author helped design and conduct the study, analyze the data, and write the manuscript.
Attestation: Ghislaine C. Echevarría has seen the original study data, reviewed the analysis of the data, approved the final manuscript, and is the archival author.
This manuscript was handled by: Sorin J. Brull, MD, FCARCSI (Hon).
1. Parkin DM, Bray F, Ferlay J, Pisani P. Global cancer statistics, 2002. CA Cancer J Clin. 2005;55:74–108
2. Zivanovic O, Aldini A, Carlson JW, Chi DS. Advanced cytoreductive surgery: American perspective. Gynecol Oncol. 2009;114:S3–9
3. Jemal A, Siegel R, Ward E, Hao Y, Xu J, Murray T, Thun MJ. Cancer statistics, 2008. CA Cancer J Clin. 2008;58:71–96
4. Colombo N, Van Gorp T, Parma G, Amant F, Gatta G, Sessa C, Vergote I. Ovarian cancer. Crit Rev Oncol Hematol. 2006;60:159–79
5. Mould T. An overview of current diagnosis and treatment in ovarian cancer. Int J Gynecol Cancer. 2012;22(Suppl 1):S2–4
6. Vergote I, Tropé CG, Amant F, Kristensen GB, Ehlen T, Johnson N, Verheijen RH, van der Burg ME, Lacave AJ, Panici PB, Kenter GG, Casado A, Mendiola C, Coens C, Verleye L, Stuart GC, Pecorelli S, Reed NSEuropean Organization for Research and Treatment of Cancer-Gynaecological Cancer Group; NCIC Clinical Trials Group. . Neoadjuvant chemotherapy or primary surgery in stage IIIC or IV ovarian cancer. N Engl J Med. 2010;363:943–53
7. Elattar A, Bryant A, Winter-Roach BA, Hatem M, Naik R. Optimal primary surgical treatment for advanced epithelial ovarian cancer. Cochrane Database Syst Rev. 2011;8:CD007565
8. McGuire WP, Hoskins WJ, Brady MF, Kucera PR, Partridge EE, Look KY, Clarke-Pearson DL, Davidson M. Cyclophosphamide and cisplatin compared with paclitaxel and cisplatin in patients with stage III and stage IV ovarian cancer. N Engl J Med. 1996;334:1–6
9. Piccart MJ, Bertelsen K, James K, Cassidy J, Mangioni C, Simonsen E, Stuart G, Kaye S, Vergote I, Blom R, Grimshaw R, Atkinson RJ, Swenerton KD, Trope C, Nardi M, Kaern J, Tumolo S, Timmers P, Roy JA, Lhoas F, Lindvall B, Bacon M, Birt A, Andersen JE, Zee B, Paul J, Baron B, Pecorelli S. Randomized intergroup trial of cisplatin-paclitaxel versus cisplatin-cyclophosphamide in women with advanced epithelial ovarian cancer: three-year results. J Natl Cancer Inst. 2000;92:699–708
10. Gottschalk A, Sharma S, Ford J, Durieux ME, Tiouririne M. Review article: the role of the perioperative period in recurrence after cancer surgery. Anesth Analg. 2010;110:1636–43
11. Snyder GL, Greenberg S. Effect of anaesthetic technique and other perioperative factors on cancer recurrence. Br J Anaesth. 2010;105:106–15
12. Kurosawa S, Fukuda T. Management of late complications after allogeneic hematopoietic stem cell transplantation. Rinsho Ketsueki. 2013;54:167–76
13. Kurosawa S, Kato M. Anesthetics, immune cells, and immune responses. J Anesth. 2008;22:263–77
14. Kutza J, Gratz I, Afshar M, Murasko DM. The effects of general anesthesia and surgery on basal and interferon stimulated natural killer cell activity of humans. Anesth Analg. 1997;85:918–23
15. Schlagenhauff B, Ellwanger U, Breuninger H, Stroebel W, Rassner G, Garbe C. Prognostic impact of the type of anaesthesia used during the excision of primary cutaneous melanoma. Melanoma Res. 2000;10:165–9
16. Biki B, Mascha E, Moriarty DC, Fitzpatrick JM, Sessler DI, Buggy DJ. Anesthetic technique for radical prostatectomy surgery affects cancer recurrence: a retrospective analysis. Anesthesiology. 2008;109:180–7
17. Christopherson R, James KE, Tableman M, Marshall P, Johnson FE. Long-term survival after colon cancer surgery: a variation associated with choice of anesthesia. Anesth Analg. 2008;107:325–32
18. de Oliveira GS Jr, Ahmad S, Schink JC, Singh DK, Fitzgerald PC, McCarthy RJ. Intraoperative neuraxial anesthesia but not postoperative neuraxial analgesia is associated with increased relapse-free survival in ovarian cancer patients after primary cytoreductive surgery. Reg Anesth Pain Med. 2011;36:271–7
19. Exadaktylos AK, Buggy DJ, Moriarty DC, Mascha E, Sessler DI. Can anesthetic technique for primary breast cancer surgery affect recurrence or metastasis? Anesthesiology. 2006;105:660–4
20. Lin L, Liu C, Tan H, Ouyang H, Zhang Y, Zeng W. Anaesthetic technique may affect prognosis for ovarian serous adenocarcinoma: a retrospective analysis. Br J Anaesth. 2011;106:814–22
21. Wuethrich PY, Hsu Schmitz SF, Kessler TM, Thalmann GN, Studer UE, Stueber F, Burkhard FC. Potential influence of the anesthetic technique used during open radical prostatectomy on prostate cancer-related outcome: a retrospective study. Anesthesiology. 2010;113:570–6
22. Heintz AP, Odicino F, Maisonneuve P, Quinn MA, Benedet JL, Creasman WT, Ngan HY, Pecorelli S, Beller U. Carcinoma of the ovary. FIGO 26th
Annual Report on the Results of Treatment in Gynecological Cancer. Int J Gynaecol Obstet. 2006;95(Suppl 1):S161–92
23. Bristow RE, Montz FJ, Lagasse LD, Leuchter RS, Karlan BY. Survival impact of surgical cytoreduction in stage IV epithelial ovarian cancer. Gynecol Oncol. 1999;72:278–87
24. Cornelis S, Van Calster B, Amant F, Leunen K, van der Zee AG, Vergote I. Role of neoadjuvant chemotherapy in the management of stage IIIC-IV ovarian cancer: survey results from the members of the European Society of Gynecological Oncology. Int J Gynecol Cancer. 2012;22:407–16
25. Chi DS, Eisenhauer EL, Lang J, Huh J, Haddad L, Abu-Rustum NR, Sonoda Y, Levine DA, Hensley M, Barakat RR. What is the optimal goal of primary cytoreductive surgery for bulky stage IIIC epithelial ovarian carcinoma (EOC)? Gynecol Oncol. 2006;103:559–64
26. Rosenbaum PR, Rubin DB.. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983;70:41–55
27. Austin PC. A tutorial and case study in propensity score analysis: an application to estimating the effect of in-hospital smoking cessation counseling on mortality. Multivariate Behav Res. 2011;46:119–51
28. Rosenbaum PR Design of Observational Studies. 2010 New York, NY Springer
29. Austin PC. An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res. 2011;46:399–424
30. Hansen BB, Bowers J.. Covariate balance in simple, stratified and clustered comparative studies. Statist Sci. 2008;23:219–36
31. Lin DY, Wei LJ.. The Robust inference for the Cox proportional hazards model. J Amer Statist Assoc. 1989;84:1074–8
32. Xie J, Liu C. Adjusted Kaplan-Meier estimator and log-rank test with inverse probability of treatment weighting for survival data. Stat Med. 2005;24:3089–110
33. Klein JP, Moeschberger ML. Survival Analysis: Techniques for Censored and Truncated Data. 20032nd ed New York, NY Springer
34. Moslemi-Kebria M, El-Nashar SA, Aletti GD, Cliby WA. Intraoperative hypothermia during cytoreductive surgery for ovarian cancer and perioperative morbidity. Obstet Gynecol. 2012;119:590–6
35. Allison P Missing Data (Quantitative Applications in the Social Sciences). 2001 Thousand Oaks, CA Sage
36. Hosmer DW, Lemeshow S, May S Applied Survival Analysis: Regression Modeling of Time-to-Event Data. 20082nd ed Hoboken, NJ Wiley-Interscience
37. Engel J, Eckel R, Schubert-Fritschle G, Kerr J, Kuhn W, Diebold J, Kimmig R, Rehbock J, Hölzel D. Moderate progress for ovarian cancer in the last 20 years: prolongation of survival, but no improvement in the cure rate. Eur J Cancer. 2002;38:2435–45
38. Winter-Roach BA, Kitchener HC, Lawrie TA. Adjuvant (post-surgery) chemotherapy for early stage epithelial ovarian cancer. Cochrane Database Syst Rev. 2012;3:CD004706
39. Nieto FJ, Coresh J. Adjusting survival curves for confounders: a review and a new method. Am J Epidemiol. 1996;143:1059–68
40. Sugihara M. Survival analysis using inverse probability of treatment weighted methods based on the generalized propensity score. Pharm Stat. 2010;9:21–34
41. Galimberti S, Sasieni P, Valsecchi MG. A weighted Kaplan-Meier estimator for matched data with application to the comparison of chemotherapy and bone-marrow transplant in leukaemia. Stat Med. 2002;21:3847–64
42. Kurman RJ, Shih IeM. The origin and pathogenesis of epithelial ovarian cancer: a proposed unifying theory. Am J Surg Pathol. 2010;34:433–43
43. Cepeda MS, Boston R, Farrar JT, Strom BL. Comparison of logistic regression versus propensity score when the number of events is low and there are multiple confounders. Am J Epidemiol. 2003;158:280–7
44. Torche F, Costa-Ribeiro C.. Parental wealth and children’s outcomes over the life-course in Brazil: a propensity score matching analysis. RSSM. 2012;30:79–96
45. Bookman MA, Greer BE, Ozols RF. Optimal therapy of advanced ovarian cancer: carboplatin and paclitaxel vs. cisplatin and paclitaxel (GOG 158) and an update on GOG0 182-ICON5. Int J Gynecol Cancer. 2003;13:735–40