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Original research
Characterization of pre-operative anemia in patients undergoing surgery by a gynecologic oncologist and association with post-operative complications
  1. Olivia W Foley,
  2. Brenda Vega,
  3. Dario Roque,
  4. Emily Hinchcliff,
  5. Jenna Marcus,
  6. Edward J Tanner and
  7. Emma L Barber
  1. Obstetrics and Gynecology, Division of Gynecologic Oncology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
  1. Correspondence to Dr Olivia W Foley, Department Obstetrics and Gynecology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA; olivia.foley{at}nm.org

Abstract

Objective Anemia is prevalent in patients with gynecologic cancers and is associated with increased peri-operative morbidity. We aimed to characterize risk factors for pre-operative anemia and describe outcomes among patients undergoing surgery by a gynecologic oncologist to identify potential areas for impactful intervention.

Methods We analyzed major surgical cases performed by a gynecologic oncologist in the National Surgical Quality Improvement Program (NSQIP) database from 2014 to 2019. Anemia was defined as hematocrit <36%. Demographic characteristics and peri-operative variables for patients with and without anemia were compared using bivariable tests. Odds of peri-operative complications in patients stratified by pre-operative anemia were calculated using logistic regression models.

Results Among 60 017 patients undergoing surgery by a gynecologic oncologist, 23.1% had pre-operative anemia. Women with ovarian cancer had the highest rate of pre-operative anemia at 39.7%. Patients with advanced-stage cancer had a higher risk of anemia than early-stage disease (42.0% vs 16.3%, p≤0.001). In a logistic regression model adjusting for potential demographic, cancer-related, and surgical confounders, patients with pre-operative anemia had increased odds of infectious complications (odds ratio (OR) 1.16, 95% CI 1.07 to 1.26), thromboembolic complications (OR 1.39, 95% CI 1.15 to 1.68), and blood transfusion (OR 5.78, 95% CI 5.34 to 6.26).

Conclusions There is a high rate of anemia in patients undergoing surgery by a gynecologic oncologist, particularly those with ovarian cancer and/or advanced malignancy. Pre-operative anemia is associated with increased odds of peri-operative complications. Interventions designed to screen for and treat anemia in this population have the potential for significant impact on surgical outcomes.

  • Ovarian Cancer
  • Preoperative Care
  • Surgery
  • Postoperative complications

Data availability statement

Data may be obtained from a third party and are not publicly available. Data were obtained from the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database. These data are available to NSQIP-participating institutions.

https://doi.org/10.1136/ijgc-2023-004539

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    What is already known on this topic

    • Pre-operative anemia has been shown to be associated with poorer surgical outcomes for general surgery and benign gynecology patients.

    What this study adds

    • Patients undergoing surgery by a gynecologic oncologist have high rates of anemia, particularly those with ovarian cancer and/or advanced disease. Pre-operative anemia is associated with infectious and thromboembolic complications in this specific population.

    How this study might affect research, practice or policy

    • These results inform future research to determine if screening for and treating pre-operative anemia for patients seeing a gynecologic oncologist improves peri-operative outcomes.

    Introduction

    Anemia is widespread among patients with solid malignancies and affects 20–90% of patients with gynecologic cancers, depending on the population and phase of treatment.1–4 In the pre-operative setting, anemia has been shown to be associated with higher rates of morbidity and mortality for those undergoing major surgery.5 6 Treating anemia with peri-operative blood transfusion is associated with additional risks and does not mitigate the negative effects of anemia.7–10 For this reason, the Enhanced Recovery After Surgery (ERAS) Society has identified screening and alternative treatments for pre-operative anemia, such as iron replacement, as important targets of future efforts to optimize patient outcomes.11

    In obstetrics and gynecology, previously published studies including large numbers of patients from national databases have similarly demonstrated an association between pre-operative anemia and increased composite morbidity/mortality scores in mixed populations of patients.12–14 Compared with the gynecologic surgery population as a whole, patients receiving care from a gynecologic oncologist are likely to have poorer performance status and unique risk factors such as receipt of neoadjuvant chemotherapy.15 Pre-operative anemia in gynecologic oncology patients has been shown to be associated with surgical site infection,16 but a more comprehensive evaluation of the relationship between pre-operative anemia and morbidity in this population has not previously been performed. Using a national surgical database, we aimed to identify the patients undergoing surgery by a gynecologic oncologist who are most at risk for pre-operative anemia as well as the peri-operative complications associated with anemia. We hypothesize that the rates of infectious and thromboembolic complications are higher among patients going to the operating room with anemia based on previous data demonstrating a link between these complications and anemia in other populations.17 18 Gynecologic oncologists may consider the results of this study when developing guidelines designed to improve peri-operative outcomes.

    We hypothesize that patients with ovarian cancer are at highest risk for pre-operative anemia because of advanced age, medical comorbidities, and receipt of neoadjuvant chemotherapy for some. We analyze this subpopulation of patients and report the rate of pre-operative anemia and peri-operative complications. These patients may have more to gain from interventions designed to treat anemia, particularly those undergoing neoadjuvant chemotherapy with a longer time interval between diagnosis and surgery.

    Methods

    Study Design and Participants

    This retrospective cohort study was performed using the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database. The database collects patient demographics, peri-operative variables, and 30-day post-operative outcomes data for patients undergoing major surgical procedures at hospitals across the US. This information is collected by trained clinical reviewers at each institution and audited to ensure interrater reliability.19 The linked hysterectomy-specific and gynecology participant use files from 2014 to 2019 were used for this study. Our cohort included patients with “gynecologic oncologist” listed under gynecology or hysterectomy subspecialist. All patients with surgery performed by a gynecologic oncologist, including those with benign pathology, were included to reflect the entire clinical practice of the subspecialty.15 20 21 Patients were excluded from the analysis if there was no hematocrit value available within the 30 days before surgery. This study was reviewed by the Institutional Review Board at Northwestern University and declared exempt from formal review as a secondary analysis of a deidentified dataset. In accordance with the Journal’s guidelines, we will provide our data for independent analysis by the Editorial Team for the purposes of additional data analysis or for the reproducibility of this study in other centers if such is requested.

    Variables

    The primary exposure in this study was pre-operative anemia, defined as hematocrit lower than 36% in the 30 days prior to surgery. This was used to approximate the WHO definition of anemia that is based on hemoglobin (<12 g/dL) because hemoglobin value is not available in the NSQIP database.22 For patients with multiple laboratory draws leading up to surgery, the hematocrit value taken closest to the day of surgery was used. We compared demographic characteristics among patients with and without pre-operative anemia including age, body mass index (BMI), race, and ethnicity. Race was categorized as White, Black, Asian, or None of the above, which included Native Hawaiian, Pacific Islander, American Indian, or Alaska Native. These groups were combined under the heading ‘None of the above’ due to small sample size. Baseline health characteristics were also compared including history of hypertension requiring medication, chronic obstructive pulmonary disease (COPD), diabetes, smoking history, and American Society of Anesthesiologists (ASA) class. Missing data for any of these characteristics was classified in a separate category. In the subset of patients in the cohort with a malignancy, we identified the cancer site from the combined participant use file and determined whether the patient had advanced or local disease. Advanced disease was defined by stage IIIA-IVB uterine cancer, stage IIIA-IVB cervical cancer, or stage IIA-IVB ovarian cancer; all other patients with cancer were characterized as having local or early-stage disease. Receipt of neoadjuvant chemotherapy was not reported because of the high proportion of missing data. Surgical variables examined included mode of surgery as determined by Current Procedural Terminology (CPT) codes, operative time, and total relative value units (RVUs), which was used as a surrogate for surgical complexity.23

    The two primary outcome measures were odds of infectious complications and thromboembolic complications. Patients were identified as having had an infectious complication if they had one or more of the following complications: superficial wound infection, deep wound infection, organ space infection, pneumonia, urinary tract infection, sepsis, or septic shock. Thromboembolic complication similarly was a composite that included pulmonary embolism, deep vein thrombosis (DVT)/thrombophlebitis, or stroke. Secondary outcomes included any blood transfusion (administered intra-operatively or within 72 hours after surgery), length of hospital stay >4 days, rate of readmission within 30 days, and individual infectious/thromboembolic complications. The number of units of blood transfused was not available in the surgical dataset during this study period, so transfusion was considered a binary variable.

    Statistical Methods

    Chi-squared analyses were used to compare categorical variables between the two groups, and Wilcoxon rank sum tests were used to compare continuous variables. Associations between pre-operative anemia and primary and secondary outcomes were described using raw data compared with chi-squared analyses, as well as individual univariate logistic regression models for each outcome of interest. Covariates controlled for in the logistic regression models included age, BMI, race, ethnicity, ASA class, hypertension requiring medication, diabetes, smoking status, local malignancy versus advanced malignancy versus benign pathology, mode of surgery, and surgical RVUs. All variables were categorical except for surgical RVUs, which was included as a continuous variable. Operative time and cancer site were not included in the models to avoid collinearity with mode of surgery, surgical RVUs, and local/advanced/benign pathology. Patients with missing values for the covariates of interest were excluded from the logistic regression analyses. Patients with ovarian cancer were analyzed as a subpopulation using unadjusted logistic regression models as well as adjusted regression analyses for each outcome of interest, with the same covariates as described above. All analyses were performed using STATA 17.0.

    Results

    We identified 66 446 patients from the surgical database who had surgery by a gynecologic oncologist. Some 6429 patients were excluded due to lack of available hematocrit data in the 30 days prior to surgery, with 60 017 patients included in the final analysis (Figure 1). There were 13 881 patients with anemia as defined as hematocrit <36%, representing 23.1% of the study population. Among patients with anemia, 10 233 (73.6%) had mild anemia (hematocrit 30–36%), 3269 (23.6%) had moderate anemia (hematocrit 24–30%), and 389 (2.8%) had severe anemia (hematocrit <24%).

    Figure 1
    Figure 1

    Cohort study enrollment diagram.

    Patient characteristics are described in Table 1. Black race, ASA class III+, hypertension requiring medication, and diabetes were associated with a higher likelihood of pre-operative anemia. As regards cancer-related variables, patients with ovarian cancer had the highest rate of pre-operative anemia at 39.7% compared with rates of 18–21% for uterine cancer, cervical cancer, and benign pathology. Some 42% of those with advanced-stage disease had pre-operative anemia compared with only 16.3% with local disease. Patients going into the operating room with pre-operative anemia were more likely to have a laparotomy and had on average longer operative times (169.6 min vs 151.5 min, p<0.001) and more complex procedures as estimated by total RVUs (33.4 vs 27.7, p<0.001).

    View this table:
    Table 1

    Association between patient and surgical characteristics and pre-operative anemia

    The unadjusted rates of primary and secondary outcomes stratified by pre-operative anemia are described in Table 2. Patients with pre-operative anemia had higher rates of infectious complication (9.9% vs 6.3%, p<0.001), thromboembolic complication (2.0% vs 0.9%, p<0.001), peri-operative blood transfusion (25.9% vs 3.6%, p<0.001), length of stay >4 days (28.0% vs 8.8%, p<0.001), and readmission within 30 days (7.7% vs 4.3%, p<0.001) compared with patients without anemia. The unadjusted and adjusted odds ratios (ORs) of primary and secondary outcomes from the logistic regression models are reported in Table 3. In the adjusted model, patients with anemia had an OR of 1.16 (95% CI 1.07 to 1.26) for any infectious complication and 1.39 (95% CI 1.15 to 1.68) for any thromboembolic complication. For the secondary outcomes, pre-operative anemia was associated with increased odds of blood transfusion (OR 5.78, 95% CI 5.34 to 6.26), length of stay >4 days (OR 2.15, 95% CI 2.01 to 2.31), and readmission within 30 days of surgery (OR 1.30, 95% CI 1.18 to 1.42).

    View this table:
    Table 2

    Unadjusted rates of infectious complications, thromboembolic complications, blood transfusion, length of stay >4 days, and 30-day readmission in anemic versus non-anemic patients

    View this table:
    Table 3

    Unadjusted and adjusted odds ratios of peri-operative complications in patients with anemia compared with those without anemia from logistic regression models

    The 9833 patients with ovarian cancer were analyzed separately. The unadjusted and adjusted ORs of primary and secondary outcomes from logistic regression models are shown in Table 4. In the adjusted models, there was no statistically significant difference identified in infectious or thromboembolic complications or 30-day readmissions in patients with or without pre-operative anemia. However, the odds of peri-operative blood transfusion were significantly higher for patients with anemia (OR 4.32, 95% CI 3.80 to 4.92), as was the odds of length of stay >4 days (OR 1.48, 95% CI 1.32 to 1.66). In this population, the rate of blood transfusion was 41.8% for patients going into the operating room with anemia compared with 12.6% of those without anemia.

    View this table:
    Table 4

    Unadjusted and adjusted odds ratios of peri-operative complications for patients with ovarian cancer and anemia compared with those without anemia from logistic regression models

    Discussion

    Summary of Main Results

    Our results demonstrate that patients undergoing surgery by a gynecologic oncologist have a high rate of pre-operative anemia (23.1% in this large national cohort). Some 35.4% of patients undergoing open abdominal surgery had anemia. The most notable demographic difference in the anemic and non-anemic populations was race; Black race was associated with a significantly higher rate of pre-operative anemia compared with other racial groups. In a logistic regression model controlling for relevant demographic, cancer-related, and surgical characteristics, anemia was associated with higher odds of infectious and thromboembolic complications. There was also a significant increase in the odds of intra-operative blood transfusion for patients going into the operating room with anemia even when controlling for patient characteristics, surgical approach, and complexity, suggesting an independent effect that is not just driven by selection bias. Pre-operative anemia was associated with a higher rate of hospital length of stay >4 days and 30-day readmissions, both variables relevant to patients as well as hospital systems looking to improve on trackable outcome metrics. Patients in this study with ovarian cancer had significantly higher rates of pre-operative anemia when compared with other gynecologic malignancies or benign pathology. When controlling for demographic and operative characteristics, anemic ovarian cancer patients had over four times the odds of requiring peri-operative blood transfusion.

    Results in the Context of Published Literature

    The high rate of pre-operative anemia in this large national database population is similar to that published in previous institution-specific studies.1 24 25 Increased risk of anemia among Black patients in this cohort is consistent with published data demonstrating that Black American women are more likely to be anemic when compared with other racial groups.26 The reasons for this effect are incompletely understood, and further research is needed to clarify the role of structural racism in this finding, identify potential barriers in access to treatment for anemia on the basis of race, and develop processes to address this health inequity.27

    Prior studies from the general surgery and gynecology literature have demonstrated poorer surgical outcomes for patients with pre-operative anemia5 6 12–14 16; we identify a similar effect in a population of patients taken care of by gynecologic oncologists. The higher rates of blood transfusion in patients with pre-operative anemia in this cohort represents a clinically relevant finding given the independent association between blood transfusion and peri-operative morbidity and mortality in this population.7 10 In the ovarian cancer subpopulation, we hypothesize that neoadjuvant chemotherapy is one of the primary drivers of pre-operative anemia and intra-operative transfusions based on previous studies demonstrating high rates of anemia and blood transfusion for patients undergoing interval cytoreduction.10 28 29 However, the database used is missing complete data regarding receipt of pre-operative chemotherapy, limiting our ability to make conclusive statements about the role of neoadjuvant chemotherapy.

    Strengths and Weaknesses

    The major strength of this study is the large sample size with high-quality peri-operative laboratory and complication data available. There are some relevant factors that are not collected consistently by NSQIP and therefore not included in this study, such as receipt of neoadjuvant chemotherapy and complications >30 days after surgery. Although blood loss is relevant to this study, estimated blood loss has been shown to be unreliable and inaccurate with wide variations based on the estimator, so we do not view the lack of data regarding this variable as a significant limitation.30 Around 10% of the patient population was excluded due to lack of 30-day pre-operative laboratory values. Patients without pre-operative laboratory values may be less likely to have anemia, perhaps causing overestimation of anemia rates. In addition, we included patients who received a blood transfusion in the pre-operative period. Pre-operative transfusion may improve the hematocrit value listed in the database prior to surgery but comes with the complications associated with transfusion. This would lead to overestimation of complications in the non-anemic cohort and weaken the association between anemia and peri-operative complications, so it does not threaten the study’s conclusions. Finally, far outliers with high blood transfusion requirements were not excluded from our analysis due to lack of data available in the NSQIP database regarding number of units transfused. These outliers, more likely to fall in the pre-operative anemia cohort, may have high rates of morbidity that could pull up the overall rates of complications. However, we suspect that the number of significant outliers requiring four or more units of blood is low and does not diminish our study’s conclusions.

    Implications for Practice and Future Research

    The risks of complications associated with both pre-operative anemia and blood transfusion suggest the need for alternative interventions to treat pre-operative anemia. Iron deficiency is one of the most common causes of anemia in this population; rates have been shown to be as high as 43% in patients with solid tumors.31 Iron deficiency is modifiable with oral or intravenous iron supplementation. Intravenous formulations deliver dosages more quickly, providing rapid availability for erythropoiesis.32 Based on the available data, international surgical guidelines recommend treatment of iron deficiency anemia in the pre-operative setting.33 The ERAS Society has published on the importance of evaluation and treatment of pre-operative anemia but has recommended further research to clarify the role of iron supplementation and the populations that may benefit.11 Vitamin B12 and folate deficiencies are less common but similarly targetable nutritional deficiencies that should be considered as part of the treatment for pre-operative anemia.1

    Gynecologic oncology patients, and particularly advanced ovarian cancer patients, may have more to gain from active management of pre-operative anemia than the general abdominal surgery population. Intravenous iron administration appears to improve hemoglobin levels for anemic patients but takes time.32 34 Patients receiving neoadjuvant chemotherapy may have 2–3 months between diagnosis and surgery, giving them time to benefit from correction of nutritional deficiencies.29 Many patients undergoing surgery by a gynecologic oncologist will need adjuvant treatment, and stakes are high to avoid peri-operative complications and maintain post-operative hemoglobin levels when compared to other surgical patients. For patients with ovarian cancer, delay in the initiation of adjuvant chemotherapy beyond 37 days after surgery has been associated with decreased survival.35 36 While data supporting iron supplementation for all anemic preoperative patients is mixed, the results of our study and the unique needs of this patient population suggest that any opportunity to improve perioperative anemia should be considered.

    Conclusions

    Previous work has demonstrated an increased risk of peri-operative morbidity in patients with anemia undergoing major abdominal surgery or benign gynecologic procedures.5 12–14 This study adds to the literature by evaluating a national cohort of patients from gynecologic oncology practices as a separate population. These patients have distinct demographic characteristics and risk factors for both anemia and peri-operative complications. Approaches to screening and treatment for anemia should be specific to their needs.

    Data availability statement

    Data may be obtained from a third party and are not publicly available. Data were obtained from the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database. These data are available to NSQIP-participating institutions.

    Ethics statements

    Patient consent for publication

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    Footnotes

    • Contributors OF contributed to the conceptualization of the work, methodology, formal data analysis, data curation, writing of the original draft, and is the guarantor. BV contributed to project administration and data curation as well as review and editing of the manuscript. DR, EH, HM, and ET contributed to the acquisition of data and review and editing of the manuscript. EB contributed to the conceptualization of the work, formal analysis, supervision, and review and editing of the manuscript. All authors are in agreement with its submission for publication to IJGC.

    • Funding This study was funded by GOG Foundation and National Institute on Aging (1P30AG059988-01a1)

    • Competing interests ELB received career development funds from the GOG Foundation and the National Institute on Aging (NIA) (1P30AG059988-01a1).

    • Provenance and peer review Not commissioned; externally peer reviewed.