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Impact of hospital volume on surgical management and outcomes for early-stage cervical cancer
YGYNO-977862; No. of pages: 6; 4C: Gynecologic Oncology xxx (xxxx) xxx
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Impact of hospital volume on surgical management and outcomes for early-stage cervical cancer Emeline M. Aviki a, Ling Chen c, Kimberly Dessources a, Mario M. Leitao Jr. a,b, Jason D. Wright c,d,e,⁎ a
Gynecology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA Joan & Sanford I. Weill Medical College of Cornell University, New York, NY, USA Department of Obstetrics and Gynecology, Columbia University College of Physicians and Surgeons, New York, NY, USA d Herbert Irving Comprehensive Cancer Center, Columbia University College of Physicians and Surgeons, New York, NY, USA e New York Presbyterian Hospital, New York, NY, USA b c
H I G H L I G H T S • Higher hospital procedural volume is associated with higher rates of indicated radical hysterectomy. • Higher hospital volume is associated with higher rates of indicated lymph node assessment. • Hospital volume is not associated with differences in mortality.
a r t i c l e
i n f o
Article history: Received 30 December 2019 Received in revised form 14 February 2020 Accepted 17 February 2020 Available online xxxx
a b s t r a c t Objective. To determine whether process and outcome measures varied for patients with early-stage cervical cancer based on hospital surgical volume. Methods. Using the National Cancer Database, we identified women with stages IA2 – IB1 cervical cancer (2011 −2013). Annual hospital volume was calculated using number of hysterectomies performed in the prior year and grouped into patient level-quartiles. Centers in the highest quartile of volume were defined as HVCs; those in the lowest quartile, as LVCs. Demographics, type/mode of hysterectomy, lymph node assessment, NCCN-compliant surgery (radical hysterectomy (RH) with LND), and survival outcomes were compared across quartiles of hospital volume. Cox Proportional Hazards model was performed to determine impact of volume on mortality. Results. We identified 3469 women treated at 598 different hospitals. RH was more likely at HVCs versus LVCs (68.9% vs. 59.6%, p b 0.001). LND was more likely at HVCs versus LVCs (96.1% vs 87.3%, p b 0.001). Patients treated at HVCs were 11.4% more likely to receive guideline-compliant surgery compared to LVCs (67.8% vs. 56.4%, p b 0.001). There was no difference in 5-year survival, 90-day survival, all-cause mortality across volume quartiles. Thirty-day mortality was significantly lower at HVCs (0 deaths in 880 patients) versus LVCs (1 in 1058 (0.1%, p = 0.02)). Age ≥ 80, Medicaid and Medicare insurance, Hispanic race, and poorly differentiated histology were independent predictors of mortality. Hospital volume was not found to be an independent predictor of mortality (p = 0.95). Conclusions. HVCs demonstrated higher rates of NCCN-recommended surgery for early-stage cervical cancer. There was no association between hospital volume and survival. © 2020 Published by Elsevier Inc.
1. Introduction There will be an estimated 13,170 new cases of cervical cancer diagnosed in 2019 [1]. For women with International Federation of Gynecology and Obstetrics (FIGO) 2009 Stage IA2 and 1B1 disease, which ⁎ Corresponding author at: Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Columbia University College of Physicians and Surgeons, 630 West 168th Street, New York, NY 10032, USA. E-mail address: [email protected] (J.D. Wright).
includes tumors that are b4 cm and confined to the cervix, the 5-year survival rate is 92% [1]. The recommended surgical treatment for Stage IA2 and IB1 disease includes radical hysterectomy (or radical trachelectomy in cases where fertility preservation is desired) with pelvic lymph node sampling [2]. An acceptable alternative to surgery is pelvic external beam radiotherapy with brachytherapy [2]. Radical hysterectomy is a complex surgical procedure that involves removal of the uterus, cervix, upper part of the vagina, and parametrial tissue. In a recent multicenter retrospective study, Matsui et al., reported that patients with Stage IB1 - IIA cervical cancer who underwent
https://doi.org/10.1016/j.ygyno.2020.02.029 0090-8258/© 2020 Published by Elsevier Inc.
Please cite this article as: E.M. Aviki, L. Chen, K. Dessources, et al., Impact of hospital volume on surgical management and outcomes for early-stage cervical cancer, Gynecologic Oncology, https://doi.org/10.1016/j.ygyno.2020.02.029
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E.M. Aviki et al. / Gynecologic Oncology xxx (xxxx) xxx
radical hysterectomy and received treatment at higher volume centers had decreased rates of local recurrence and all-cause mortality [3]. Additional studies involving women with locally advanced cervical cancer have demonstrated improvements in guideline compliance and survival when care is delivered at high volume centers (HVCs) [4–6]. Robin et al. reported improved guideline compliance at HVCs and a corresponding survival benefit when guidelines were followed [4]. Wright et al. evaluated patients who were treated with radiation therapy and found that rates of guideline adherence were higher at HVCs, but that hospital volume did not affect survival [5]. Lastly, Richard et al. studied patients with stage IIB – IIIB cervical cancer who received radiation therapy and found that treatment at HVCs was independently associated with better adherence to guidelines and improved survival [6]. For women with early-stage cervical cancer, it remains unclear how often guideline recommended care is delivered and whether hospital volume affects guideline compliance and survival outcomes. In this analysis, we explore surgical treatment patterns in women diagnosed with early-stage cervical cancer, and whether hospital volume affects surgical guideline compliance and survival outcomes. 2. Materials and methods 2.1. Data source and patient selection The National Cancer Data Base (NCDB) is a nationwide hospital registry of cancer patients sponsored by the American Cancer Society and the American College of Surgeons [7]. The NCDB gathers information on approximately 70% of all new invasive cancer diagnoses from N1500 Commission on Cancer-affiliated hospitals within the United States. Data captured include hospital factors, patient demographics, disease stage, first course of treatment, and overall survival (OS). This study was deemed to be non-human subjects research and approved by the Columbia University Institutional Review Board. We queried the NCDB for all patients diagnosed with cervical cancer from 2010 to 2013 (n = 38,545). We included all women with Stage IA2 and IB1 cervical cancer, with squamous cell, adenocarcinoma, or adenosquamous histologies, who underwent radical or simple hysterectomy for their initial treatment (n = 5263). We excluded all patients with an unknown surgical modality (n = 453), patients for whom this was not a first or only cancer diagnosis (n = 209), those without a microscopic confirmation of cancer (n = 6), and those who received chemotherapy or radiotherapy prior to surgery (n = 48). The original cohort included 4547 patients from 661 hospitals.
Table 1 Patient-level quartiles of prior year volume. Volume category
Number of patients (N = 3469)
Annual cervical cancer hysterectomy volume
Low Medium-Low Medium-High High
1058 519 1012 880
0–1 2 3–5 6–20
≥80 years), race (white, black, Hispanic, other, unknown), year of diagnosis (2011, 2012, 2013), insurance status (uninsured, private, Medicaid, Medicare, other/unknown), and income (b$38,000, $38,000– $47,999, $48,000–$62,999, ≥$63,000, unknown) were evaluated. Location was classified as metropolitan, urban, or rural, determined by matching zip codes to rural-urban continuum codes from the United States Department of Agriculture Economic Research Service. Comorbidity status was described using the Deyo classification of the Charlson Comorbitidy score (0, 1, ≥2) [8]. Facility type was based on classification by the American College of Surgeons Commission on Cancer Accreditation program as a community cancer program, comprehensive community cancer program, academic/research program, or integrated network cancer center [5]. The region of the treating facility was classified as Northeast, Midwest, South, or West. Tumor characteristics included stage based on American Joint Committee on Cancer (AJCC) clinical stage, FIGO stage, or AJCC pathologic stage (IA2 or IB1), histology (squamous, adenocarcinoma, or adenosquamous), and grade (well, moderate, poorly differentiated, or unknown). Surgical modality was classified as intent-totreat and reported as minimally invasive surgery (MIS) or open. 2.4. Defining outcomes and process measures The primary process measure evaluated was National Comprehensive Cancer Network (NCCN) guideline-compliant surgical management. NCCN guideline compliance was defined as a radical hysterectomy with lymph node assessment. The secondary outcome of interest was 30-day mortality, 90-day mortality, and OS, reported as all-cause mortality, which includes death from cancer and other causes. 2.5. Statistical analysis
Hospital volume was computed using the number of simple and radical hysterectomies (Codes: 50, 51, 52, 53, 54, 60, 61, 62) performed at a given hospital in the previous year on patients with suspected, confirmed, or occult Stage IA2 or IB1 cervical cancer (C53.0 – C53.9). Hospital volume was analyzed as a categorical variable and divided into patient-level volume quartiles. Based on patient-level quartiles from procedures performed in the previous year, low volume was defined as an annual volume of ≤1, medium-low as a volume of 2, mediumhigh as a volume of 3–5, and high as a volume of 6–20 cases in the prior year (Table 1). As seen in Table 1, the volume of patients in each quartile are not evenly distributed as they are based on volume from the previous year. Sensitivity analyses were performed using volume as a continuous variable. The final analytical cohort excluded patients from 2010 due to the absence of surgical modality, leaving a total of 3469 patients for the analysis.
We sought to examine the effect of hospital volume on NCCN guideline-compliant surgical management and OS. An unadjusted analysis was performed to compare demographics and outcomes of interest across volume quartiles using X2 test. The results of these tests were described in the text to highlight a comparison of differences between centers in the highest quartile of volume (HVCs) and centers in the lowest quartile of volume (LVCs). However, all statistical tests were conducted across volume quartiles. OS was compared across volume quartiles using the Kaplan-Meir method and compared using the Log-rank test. Thirty-day and 90-day mortality were compared across volume quartiles using X2 test. A marginal multivariable Cox Proportional Hazards model was used to determine factors associated with all-cause mortality, accounting for hospital-level clustering. Results from the Cox Proportional Hazards models are reported as hazards ratios (HRs) with 95% confidence intervals (CIs). A sensitivity analysis comparing the effect of volume as a continuous variable was performed using a similar model. All hypothesis tests were two-sided. A p-value of b0.05 was considered statistically significant. Analyses were conducted using SAS version 9.4 (SAS institute Inc., Cary, NC).
2.3. Data collection
3. Results
For the 3469 patients included in the analysis, demographic characteristics including age at diagnosis (b40, 40–49, 50–59, 60–69, 70–79,
We identified 3469 women treated at 598 different hospitals, including 1058 (30.5%) at LVCs, 519 (15.0%) at medium-low volume
2.2. Defining hospital volume
Please cite this article as: E.M. Aviki, L. Chen, K. Dessources, et al., Impact of hospital volume on surgical management and outcomes for early-stage cervical cancer, Gynecologic Oncology, https://doi.org/10.1016/j.ygyno.2020.02.029
E.M. Aviki et al. / Gynecologic Oncology xxx (xxxx) xxx
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Table 2 Characteristics stratified by hospital volume quartiles. Characteristics
Number of patients Number of hospitals Age of diagnosis b40 40–49 50–59 60–69 70–79 N/=80 Race White Black Hispanic Other Unknown Year of diagnosis 2011 2012 2013 Insurance Uninsured Private Medicaid Medicare Other government/unknown Median household income b$38,000 $38,000–$47,999 $48,000–$62,999 $63,000+ Unknown Patient's residence area Metropolitan Urban Rural Unknown Comorbidity score 0 1 N/=2 Facility type Community cancer Comprehensive community ca Academic/research Integrated network cancer Facility location Northeast Midwest South West Stage 1A2 1B1 Histology Squamous cell Adenocarcinoma Adenosquamous Grade Well Moderate Poorly Unknown Hysterectomy type Simple Radical Route of surgery Open Minimally invasive Lymphadenectomy No Yes a
Low
Medium low
Medium high
High
p-Value
N
%
N
%
N
%
N
%
1058
(30.5)
519
(15.0)
1012
(29.2)
880
(25.4)
323 349 214 199 41 12
(30.5) (33.0) (20.2) (11.2) (3.9) (1.1)
174 153 106 66 15
(33.5) (29.5) (20.4) (12.7) (2.9)
(34.4) (33.6) (18.6) (8.6) (3.8)
a
(33.8) (30.7) (20.7) (11.0) (2.9) (1.0)
303 296 164 76 33
a
342 311 209 111 29 10
a
a
723 112 149 54 20
(68.3) (10.6) (14.1) (5.1) (1.9)
351 59 70 36
(67.6) (11.4) (13.5) (6.9)
642 113 176 75
(63.4) (11.2) (17.4) (7.4)
602 100 123 50
(68.4) (11.4) (14.0) (5.7)
a
a
a
a
a
a
353 366 339
(33.4) (34.6) (32.0)
182 186 151
(35.1) (35.8) (29.1)
332 295 385
(32.8) (29.2) (38.0)
293 320 267
(33.3) (36.4) (30.3)
59 611 225 124 39
(5.6) (57.8) (21.3) (11.7) (3.7)
36 303 111 55 14
(6.9) (58.4) (21.4) (10.6) (2.7)
86 566 199 126 35
(8.5) (55.9) (19.7) (12.5) (3.5)
86 509 155 90 40
(9.8) (57.8) (17.6) (10.2) (4.5)
176 258 308 315
(16.6) (24.4) (29.1) (29.8)
88 114 150 164
(17.0) (22.0) (28.9) (31.6)
220 268 245 278
(21.7) (26.5) (24.2) (27.5)
177 213 243 244
(20.1) (24.2) (27.6) (27.7)
a
a
a
a
a
a
a
a
899 121 17 21
(85.0) (11.4) (1.6) (2.0)
432 61 16 10
(83.2) (11.8) (3.1) (1.9)
836 135 14 27
(82.6) (13.3) (1.4) (2.7)
694 141
(78.9) (16.0)
a
a
37
(4.2)
910 120 28
(86.0) (11.3) (2.6)
445 62 12
(85.7) (11.9) (2.3)
891 105 16
(88.0) (10.4) (1.6)
766 93 21
(87.0) (10.6) (2.4)
78 488 356 136
(7.4) (46.1) (33.6) (12.9)
17 192 211 99
(3.3) (37.0) (40.7) (19.1)
14 341 513 144
(1.4) (33.7) (50.7) (14.2)
a
a
193 626 61
(21.9) (71.1) (6.9)
200 289 356 213
(18.9) (27.3) (33.6) (20.1)
114 102 183 120
(22.0) (19.7) (35.3) (23.1)
161 196 440 215
(15.9) (19.4) (43.5) (21.2)
108 221 396 155
(12.3) (25.1) (45.0) (17.6)
190 868
(18.0) (82.0)
78 441
(15.0) (85.0)
102 910
(10.1) (89.9)
106 774
(12.0) (88.0)
634 376 48
(59.9) (35.5) (4.5)
312 176 31
(60.1) (33.9) (6.0)
595 360 57
(58.8) (35.6) (5.6)
502 325 53
(57.0) (36.9) (6.0)
203 482 279 94
(19.2) (45.6) (26.4) (8.9)
103 228 142 46
(19.8) (43.9) (27.4) (8.9)
153 437 324 98
(15.1) (43.2) (32.0) (9.7)
129 436 221 94
(14.7) (49.5) (25.1) (10.7)
427 631
(40.4) (59.6)
178 341
(34.3) (65.7)
347 665
(34.3) (65.7)
274 606
(31.1) (68.9)
429 629
(40.5) (59.5)
217 302
(41.8) (58.2)
432 580
(42.7) (57.3)
392 488
(44.5) (55.5)
134 924
(12.7) (87.3)
39 480
(7.5) (92.5)
62 950
(6.1) (93.9)
34 846
(3.9) (96.1)
0.47
0.01
0.001
0.03
0.02
b0.001
0.65
b0.001
b0.001
b0.001
0.66
0.002
b0.001
0.35
b0.001
Fewer than 10 patients.
Please cite this article as: E.M. Aviki, L. Chen, K. Dessources, et al., Impact of hospital volume on surgical management and outcomes for early-stage cervical cancer, Gynecologic Oncology, https://doi.org/10.1016/j.ygyno.2020.02.029
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E.M. Aviki et al. / Gynecologic Oncology xxx (xxxx) xxx
Table 3 Comparing NCCN guideline compliance across quartiles of volume. Characteristics
Low N
NCCN guideline compliance No Yes
%
Medium low
Medium high
High
N
N
N
%
%
p-Value % b0.001
461 (43.6) 191 (36.8) 363 (35.9) 283 (32.2) 597 (56.4) 328 (63.2) 649 (64.1) 597 (67.8)
*NCCN compliance was defined as having radical hysterectomy and lymph node dissection.
centers, 1012 (29.2%) at medium-high volume centers, and 880 (25.4%) at HVCs (Table 1). Most patients had stage 1B1 disease (86.3%), underwent radical hysterectomy (64.7%), and received MIS (57.6%). Additionally, most patients were white (66.8%), had private insurance (57.3%), and lived in metropolitan areas (82.5%). Hospital volume was found to be associated with race, year of diagnosis, insurance type, median household income, patient's residence area, facility type, facility location, stage, grade, hysterectomy type, and lymphadenectomy (Table 2). Uninsured patients comprised a larger proportion of patients at HVCs (9.8% vs 5.6%) and Medicaid patients comprised a larger proportion of patients at LVCs (21.3% vs. 17.6%) (p = 0.03). Patients residing in zip codes with a median household income b$38,000 were more likely to receive care at HVCs (20.1% vs. 16.6%) (p = 0.02). Patients living in metropolitan areas were more likely to receive care at LVCs (85.0% vs 78.9%) and those living in urban areas were more likely to receive care at HVCs (16.0% vs 11.4%)
(p b 0.001). HVCs were more frequently described as academic/research facilities (71.1%) whereas LVCs were more frequently described as comprehensive community cancer centers (46.1%) (p b 0.001). Women in the Northeast were more likely to receive care at low- or medium-low volume centers (53.9%) and those in the South were more likely to receive care at high- or medium-high volume centers (60.8%) (p b 0.001). Patients with Stage IA2 disease were more likely to receive care at LVCs (39.9%) while patients with Stage IB1 disease were more likely to receive care at medium-high and HVCs (30.4%) (p b 0.001). The majority of patients across quartiles of hospital volume underwent radical hysterectomy; performance of radical hysterectomy was 59.6% at LVCs-, 65.7% at medium-low, 65.7% at medium-high and 68.9% at HVCs (p b 0.001). Volume was not found to be associated with whether the procedure was done via an open or minimally invasive approach, with 59.5% of women at LVCs undergoing MIS compared to 55.5% at HVCs (p = 0.35). Lymph node assessment was more likely to occur at HVCs compared to LVCs (96.1% vs 87.3%, p b 0.001). We then examined NCCN guideline compliance defined as both radical hysterectomy and lymph node assessment across volume quartiles. In this analysis, patients at HVCs were significantly more likely to receive NCCN guideline-compliant surgical management compared to patients seen at LVCs (Table 3). Patients treated at HVCs were 11.4% more likely to receive NCCN-compliant surgical management compared to patients treated at LVCs (67.8% vs 56.4%, p b 0.001). In the initial unadjusted survival analysis, 5-year survival, 30-day mortality, and 90-day mortality were compared across volume quartiles (Table 4). There was no difference in 5-year survival across volume quartiles (Fig. 1). Thirty-day mortality was significantly lower at HVCs,
Table 4 Comparing survival outcomes across quartiles of volume. Survival characteristics
Low N
All 5-Year survival 95% CI 30-Day mortality 90-Day mortality a
%
1058
1 2
Medium low
Medium high
N
N
%
519 91.8 (89.4–93.8) 0.1 0.2
0 0
High %
1012 92.2 (89.1–94.4) 0.0 0.0
2 3
N
p-Value %
880 89.5 (86.3–91.9) 0.2 0.3
0 1
90.2 (86.9–92.8) 0.0 0.1
0.97 0.02a 0.09a
Chi-Square test performed in lieu of Fisher's Exact test.
Fig. 1. Overall survival expressed as months from diagnosis grouped by hospital volume quartiles. p = 0.97 by log rank test (n = 3469).
Please cite this article as: E.M. Aviki, L. Chen, K. Dessources, et al., Impact of hospital volume on surgical management and outcomes for early-stage cervical cancer, Gynecologic Oncology, https://doi.org/10.1016/j.ygyno.2020.02.029
E.M. Aviki et al. / Gynecologic Oncology xxx (xxxx) xxx
with 0 deaths in 880 patients at HVCs compared to 1 death in 1058 patients (0.1%) at LVCs (p = 0.02). There was no difference in 90-day mortality across volume quartiles (p = 0.09). In the adjusted survival model, hospital volume as a categorical variable was not an independent predictor of mortality (Table 5). A Table 5 Multivariable Cox Proportional Hazards model of mortality controlling for quartiles of volume. Characteristics
Adjusted hazards ratio
Number of patients Number of hospitals Age of diagnosis b40 40–49 50–59 60–69 70–79 N/=80 Race White Black Hispanic Other Unknown Year of diagnosis 2011 2012 2013 Insurance Private Medicaid Medicare Other government/unknown Uninsured Median household income b$38,000 $38,000–$47,999 $48,000–$62,999 $63,000+ Unknown Comorbidity score 0 1 N/=2 Facility type Academic/Research Community cancer Comprehensive community ca Integrated network cancer Stage 1A2 1B1 Histology Squamous cell Adenocarcinoma Adenosquamous Grade Well Moderate Poorly Unknown Hysterectomy type Simple Radical Route of surgery Open Minimally invasive Lymphadenectomy No Yes Prior year volume, quartiles Low High Medium high Medium low
3469 598
a
p-Value b 0.05.
Referent 0.83 (0.55–1.24) 1.31 (0.88–1.95) 1.20 (0.75–1.92) 1.45 (0.69–3.06) 5.90 (2.61–13.33)a Referent 1.02 (0.67–1.56) 0.38 (0.23–0.64)a 0.88 (0.46–1.71) 0.62 (0.08–4.51) Referent 1.01 (0.74–1.38) 0.91 (0.63–1.31) Referent 1.47 (1.02–2.10)a 1.85 (1.21–2.81)a 1.34 (0.66–2.73) 1.07 (0.57–2.02) Referent 0.92 (0.60–1.40) 0.93 (0.63–1.38) 0.70 (0.44–1.10) 1.83 (0.19–17.12) Referent 1.06 (0.72–1.57) 0.46 (0.14–1.52) Referent 1.83 (0.84–3.95) 1.36 (0.99–1.86) 1.10 (0.67–1.82) 0.54 (0.28–1.03) Referent Referent 0.71 (0.49–1.03) 1.39 (0.81–2.40) Referent 1.07 (0.63–1.83) 2.36 (1.34–4.16)a 0.80 (0.38–1.70) Referent 0.97 (0.72–1.30) Referent 1.27 (0.97–1.67) Referent 1.18 (0.65–2.16) Referent 1.07 (0.70–1.64) 0.99 (0.70–1.40) 1.03 (0.67–1.60)
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sensitivity analysis was performed using volume as a continuous variable, and results were unchanged (Supplementary Table S1). In the Cox Proportional Hazards model, age ≥ 80, Medicaid and Medicare insurance, and having a poorly differentiated cervical cancer were independent predictors of increased mortality, and Hispanic race was an independent predictor of decreased mortality. 4. Discussion These findings suggest that patients with early-stage cervical cancer are more likely to receive guideline-recommended surgery and less likely to die within 30 days of surgery when treated at HVCs. However, treatment at HVCs does not appear to influence 90-day or all-cause mortality. This is one of the first analyses to specifically investigate the relationship between volume and outcomes in patients surgically treated for Stage IA2 and IB1 cervical cancer. Several previously published reports have examined the association between volume and outcomes in different populations of patients with cervical cancer. An early perspective database study of 1500 women who underwent radical hysterectomy for cervical cancer, surgeon volume was found to influence rates of postoperative medical complications, length of stay, and transfusion requirements. While surgeon volume had a strong impact on outcomes, hospital volume did not appear to have an independent effect on outcomes [9]. In a recent study of 5964Japanese women with FIGO stage IB1 - IIB cervical cancer treated with radical hysterectomy, the authors demonstrated lower rates of local recurrence and lower rates of all-cause mortality when patients were treated at HVCs [3]. In our cohort of patients with IA2 and IB1 cervical cancer, we did not find any differences in all-cause mortality across hospital volume settings. However, there are notable differences between our study and the Japanese study which might explain this. First, in our analysis and the perspective database study, the highestvolume hospital cohort included far lower-volume hospitals than those in the highest-volume cohort in the Japanese study [3,9]. For example, the perspective database study defined high volume as hospitals with an average annual volume of N7, and we defined high volume as hospitals with a prior year volume of between 6 and 20; whereas the Japanese study defined high volume as hospitals with an average annual volume of ≥21. This may indicate that, unlike the Japanese cohort, very few centers in the U.S. are truly high-volume enough to demonstrate mortality differences. Second, we included all patients with IA2 and IB1 cervical cancer who underwent hysterectomy, regardless of the type of hysterectomy performed. Extrafascial (simple) hysterectomy is technically less complex and carries lower risk of surgical complications; therefore, in our cohort volume would be less likely to affect mortality. Additionally, we did not include patients with FIGO Stage IB2 – IIB disease who might require an even more technically complex surgery for complete tumor removal and are often treated with radiation in lieu of surgery. By only evaluating radical hysterectomy across volume settings and by including higher-risk patients, differences in immediate surgical outcomes and longer-term oncologic outcomes may be more profound and therefore show a mortality difference. By including all surgically treated patients in our analysis, we were able to demonstrate higher rates of guideline-compliant surgery in patients treated at HVCs. In our analysis, 62.6% of patients received guideline-compliant surgery, a figure that increased to 67.8% at centers in the highest quartile of volume. This finding raises the question of whether performing simple hysterectomy in patients with Stage IA2 and IB1 cervical cancer results in higher rates of local recurrence. We were unable to evaluate rates of local recurrence due to limitations of the NCDB dataset. A recent study used the NCDB to evaluate survival differences associated with use of simple compared to radical hysterectomy in patients with IA2 and IB1 (2 cm or less). The authors found no survival difference between simple and radical hysterectomy for patients with Stage IA2 cancers. However, in patients with stage IB1 (2 cm or less) disease, simple hysterectomy was associated with a 55% increased risk of death compared to radical hysterectomy [10].
Please cite this article as: E.M. Aviki, L. Chen, K. Dessources, et al., Impact of hospital volume on surgical management and outcomes for early-stage cervical cancer, Gynecologic Oncology, https://doi.org/10.1016/j.ygyno.2020.02.029
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Though there are few studies evaluating volume-outcomes in patients with early-stage cervical cancer, several studies have evaluated the association between volume and outcomes in patients with locally advanced cervical cancer [4,8,9]. A prior NCDB study of 15,194 women with locally advanced cervical cancer showed improved guidelinecompliant treatment using chemotherapy, external beam radiotherapy, and brachytherapy at higher-volume centers [4]. In this patient cohort, 44.3% received guideline-compliant treatment and guidelinecompliance was associated with improved survival. However, the impact of volume on survival outcomes was not evaluated [4]. An NCDB study of 20,766 women with stage IIB-IVA cervical cancer examined factors associated with survival and found that while hospital volume did not affect survival, adherence to treatment guidelines, and the specific hospital in which patients received care, impacted survival [5]. In fact, the specific hospital in which patients received care proved to be the strongest predictor of survival in that analysis. Lastly, an NCDB study of 27,660 women with stage IIB-IIIB cervical cancer who received radiation found that treatment at HVCs was independently associated with improved adherence to standard therapy and improved survival [6]. There are some notable limitations associated with our analysis. As is the case with any administrative dataset, we were unable to determine the factors that contributed to patients' or physicians' treatment decisions. A limitation specific to our analysis and use of the NCDB is that we were unable to determine whether rates of local recurrence differ across volume settings, which has important implications in this population. While initial treatment information is captured in the NCDB, subsequent treatment data is not chronologically catalogued, rendering analysis of local recurrence not feasible. We evaluated 5-year survival and all-cause mortality and found no difference across volume settings, which may indicate that, if differences in local recurrence are present, they do not appear to affect survival. Additionally, the cancer cases in NCDB include both suspected then confirmed cases and occult malignancies diagnosed after surgery on pathology alone. Amongst the 3469 patients, 167 patients lacked information regarding clinical or FIGO stage and instead were only pathologically staged raising suspicion that this group may represent occult malignancies not suspected at time of surgery. There are several additional limitations associated with analyzing hospital volume. First, within each hospital are potentially wide ranges of different provider volumes. To account for this, researchers can perform provider volume and hospital volume analyses in parallel or perform provider-level cluster analysis to mitigate the influence of any dominant provider on overall hospital volume. The NCDB does not provide data at the provider level, limiting our ability to perform these analyses. Second, there is the well-known potential for overestimation of volume-based differences when volume is evaluated as a categorical variable. To account for this, we included a sensitivity analysis for the multivariate model, which included volume as a continuous variable (Supplementary Table S1). In our analysis, volume was not a significant predictor of mortality as either a categorical or continuous variable. Moreover, the fact that hospital volume as a categorical variable was not significant in the adjusted survival analysis provides further reassurance that hospital volume is not a significant predictor of survival in these patients. Lastly, when considering the impact of high- and low-volume centers on patients with early-stage cervical cancer, fertility-preserving surgery is an important consideration that we did not incorporate into our analysis. There may be volume-dependent differences in the safety and efficacy of radical trachelectomy and other fertility-sparing options that were, therefore, beyond the scope of the current study. 5. Conclusions In summary, these findings provide important direction for future efforts aimed at elevating the quality of care delivered to patients with
early-stage cervical cancer. Notably, only 54.6% of patients treated at LVCs in our cohort received guideline-concordant surgery, with an 11.4% increase at HVCs. Though statistically significant, the difference in compliance between low and high volume centers did not lead to a difference in survival based on the high and low volume cutoffs generated by the dataset. Additional studies, focused on determining if there is a high-volume threshold that leads to a survival difference, are warranted. Additionally, public reporting of compliance rates, and focused quality improvement efforts that aim to identify and disseminate processes at high-performing hospitals, are needed to meaningfully improve the disparities in guideline compliance found across hospital volume settings. Supplementary data to this article can be found online at https://doi. org/10.1016/j.ygyno.2020.02.029.
Funding This study was funded in part through the NIH/NCI Support Grant P30 CA008748 (Dr. Wright).
Disclosures Dr. Wright reports personal fees from Clovis Oncology, personal fees from Tesaro, grants from Merck, outside the submitted work. Dr. Leitao is a consultant for Intuitive Surgical, outside the submitted work.
CRediT authorship contribution statement Emeline Aviki:Conceptualization, Formal analysis, Writing - original draft, Writing - review & editing.Ling Chen:Conceptualization, Formal analysis, Writing - review & editing.Kimberly Dessources:Formal analysis, Writing - original draft.Mario M. Leitao: Conceptualization, Formal analysis, Writing - review & editing.Jason D. Wright:Conceptualization, Formal analysis, Writing - review & editing.
Declaration of competing interest None declared. References [1] R.L. Siegel, K.D. Miller, A. Jemal, Cancer statistics, 2019, CA Cancer J. Clin. 69 (2019) 7–34. [2] National Comprehensive Cancer Network Clinical Practice Guideline in Oncology, Cervical cancer, Available at https://www.nccn.org/professionals/physician_gls/ pdf/cervical.pdf Date accessed: August 14, 2019. [3] K. Matsuo, M. Shimada, S. Yamaguchi, et al., Association of radical hysterectomy surgical volume and survival for early-stage cervical cancer, Obstet. Gynecol. 133 (2019) 1086–1098. [4] T.P. Robin, A. Amini, T.E. Schefter, et al., Disparities in standard of care treatment and associated survival decrement in patients with locally advanced cervical cancer, Gynecol. Oncol. 143 (2016) 319–325. [5] J.D. Wright, Y. Huang, C.V. Ananth, Influence of treatment center and hospital volume on survival for locally advanced cervical cancer, Gynecol. Oncol. 139 (2015) 506–512. [6] J.F. Lin, J.L. Berger, T.C. Krivak, et al., Impact of facility volume on therapy and survival for locally advanced cervical cancer, Gynecol. Oncol. 132 (2014) 416–422. [7] K.Y. Bilimoria, A.K. Stewart, D.P. Winchester, et al., The National Cancer Data Base: a powerful initiative to improve cancer care in the United States, Ann. Surg. Oncol. 15 (2008) 683–690. [8] R.A. Deyo, D.C. Cherkin, M.A. Ciol, Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases, J. Clin. Epidemiol. 45 (1992) 613–619. [9] J.D. Wright, S.N. Lewin, I. Deutsch, et al., The influence of surgical volume on morbidity and mortality of radical hysterectomy for cervical cancer, Am. J. Obstet. Gynecol. 205 (2011), 225.e1-7. [10] T.Y. Sia, L.C. Chen, A. Melamed, et al., Trends in use and effect on survival of simple hysterectomy for early-stage cervical Cancer, Obstet. Gynecol. 134 (2019) 1132–1143.
Please cite this article as: E.M. Aviki, L. Chen, K. Dessources, et al., Impact of hospital volume on surgical management and outcomes for early-stage cervical cancer, Gynecologic Oncology, https://doi.org/10.1016/j.ygyno.2020.02.029
Contents lists available at ScienceDirect
Gynecologic Oncology journal homepage: www.elsevier.com/locate/ygyno
Impact of hospital volume on surgical management and outcomes for early-stage cervical cancer Emeline M. Aviki a, Ling Chen c, Kimberly Dessources a, Mario M. Leitao Jr. a,b, Jason D. Wright c,d,e,⁎ a
Gynecology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA Joan & Sanford I. Weill Medical College of Cornell University, New York, NY, USA Department of Obstetrics and Gynecology, Columbia University College of Physicians and Surgeons, New York, NY, USA d Herbert Irving Comprehensive Cancer Center, Columbia University College of Physicians and Surgeons, New York, NY, USA e New York Presbyterian Hospital, New York, NY, USA b c
H I G H L I G H T S • Higher hospital procedural volume is associated with higher rates of indicated radical hysterectomy. • Higher hospital volume is associated with higher rates of indicated lymph node assessment. • Hospital volume is not associated with differences in mortality.
a r t i c l e
i n f o
Article history: Received 30 December 2019 Received in revised form 14 February 2020 Accepted 17 February 2020 Available online xxxx
a b s t r a c t Objective. To determine whether process and outcome measures varied for patients with early-stage cervical cancer based on hospital surgical volume. Methods. Using the National Cancer Database, we identified women with stages IA2 – IB1 cervical cancer (2011 −2013). Annual hospital volume was calculated using number of hysterectomies performed in the prior year and grouped into patient level-quartiles. Centers in the highest quartile of volume were defined as HVCs; those in the lowest quartile, as LVCs. Demographics, type/mode of hysterectomy, lymph node assessment, NCCN-compliant surgery (radical hysterectomy (RH) with LND), and survival outcomes were compared across quartiles of hospital volume. Cox Proportional Hazards model was performed to determine impact of volume on mortality. Results. We identified 3469 women treated at 598 different hospitals. RH was more likely at HVCs versus LVCs (68.9% vs. 59.6%, p b 0.001). LND was more likely at HVCs versus LVCs (96.1% vs 87.3%, p b 0.001). Patients treated at HVCs were 11.4% more likely to receive guideline-compliant surgery compared to LVCs (67.8% vs. 56.4%, p b 0.001). There was no difference in 5-year survival, 90-day survival, all-cause mortality across volume quartiles. Thirty-day mortality was significantly lower at HVCs (0 deaths in 880 patients) versus LVCs (1 in 1058 (0.1%, p = 0.02)). Age ≥ 80, Medicaid and Medicare insurance, Hispanic race, and poorly differentiated histology were independent predictors of mortality. Hospital volume was not found to be an independent predictor of mortality (p = 0.95). Conclusions. HVCs demonstrated higher rates of NCCN-recommended surgery for early-stage cervical cancer. There was no association between hospital volume and survival. © 2020 Published by Elsevier Inc.
1. Introduction There will be an estimated 13,170 new cases of cervical cancer diagnosed in 2019 [1]. For women with International Federation of Gynecology and Obstetrics (FIGO) 2009 Stage IA2 and 1B1 disease, which ⁎ Corresponding author at: Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Columbia University College of Physicians and Surgeons, 630 West 168th Street, New York, NY 10032, USA. E-mail address: [email protected] (J.D. Wright).
includes tumors that are b4 cm and confined to the cervix, the 5-year survival rate is 92% [1]. The recommended surgical treatment for Stage IA2 and IB1 disease includes radical hysterectomy (or radical trachelectomy in cases where fertility preservation is desired) with pelvic lymph node sampling [2]. An acceptable alternative to surgery is pelvic external beam radiotherapy with brachytherapy [2]. Radical hysterectomy is a complex surgical procedure that involves removal of the uterus, cervix, upper part of the vagina, and parametrial tissue. In a recent multicenter retrospective study, Matsui et al., reported that patients with Stage IB1 - IIA cervical cancer who underwent
https://doi.org/10.1016/j.ygyno.2020.02.029 0090-8258/© 2020 Published by Elsevier Inc.
Please cite this article as: E.M. Aviki, L. Chen, K. Dessources, et al., Impact of hospital volume on surgical management and outcomes for early-stage cervical cancer, Gynecologic Oncology, https://doi.org/10.1016/j.ygyno.2020.02.029
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radical hysterectomy and received treatment at higher volume centers had decreased rates of local recurrence and all-cause mortality [3]. Additional studies involving women with locally advanced cervical cancer have demonstrated improvements in guideline compliance and survival when care is delivered at high volume centers (HVCs) [4–6]. Robin et al. reported improved guideline compliance at HVCs and a corresponding survival benefit when guidelines were followed [4]. Wright et al. evaluated patients who were treated with radiation therapy and found that rates of guideline adherence were higher at HVCs, but that hospital volume did not affect survival [5]. Lastly, Richard et al. studied patients with stage IIB – IIIB cervical cancer who received radiation therapy and found that treatment at HVCs was independently associated with better adherence to guidelines and improved survival [6]. For women with early-stage cervical cancer, it remains unclear how often guideline recommended care is delivered and whether hospital volume affects guideline compliance and survival outcomes. In this analysis, we explore surgical treatment patterns in women diagnosed with early-stage cervical cancer, and whether hospital volume affects surgical guideline compliance and survival outcomes. 2. Materials and methods 2.1. Data source and patient selection The National Cancer Data Base (NCDB) is a nationwide hospital registry of cancer patients sponsored by the American Cancer Society and the American College of Surgeons [7]. The NCDB gathers information on approximately 70% of all new invasive cancer diagnoses from N1500 Commission on Cancer-affiliated hospitals within the United States. Data captured include hospital factors, patient demographics, disease stage, first course of treatment, and overall survival (OS). This study was deemed to be non-human subjects research and approved by the Columbia University Institutional Review Board. We queried the NCDB for all patients diagnosed with cervical cancer from 2010 to 2013 (n = 38,545). We included all women with Stage IA2 and IB1 cervical cancer, with squamous cell, adenocarcinoma, or adenosquamous histologies, who underwent radical or simple hysterectomy for their initial treatment (n = 5263). We excluded all patients with an unknown surgical modality (n = 453), patients for whom this was not a first or only cancer diagnosis (n = 209), those without a microscopic confirmation of cancer (n = 6), and those who received chemotherapy or radiotherapy prior to surgery (n = 48). The original cohort included 4547 patients from 661 hospitals.
Table 1 Patient-level quartiles of prior year volume. Volume category
Number of patients (N = 3469)
Annual cervical cancer hysterectomy volume
Low Medium-Low Medium-High High
1058 519 1012 880
0–1 2 3–5 6–20
≥80 years), race (white, black, Hispanic, other, unknown), year of diagnosis (2011, 2012, 2013), insurance status (uninsured, private, Medicaid, Medicare, other/unknown), and income (b$38,000, $38,000– $47,999, $48,000–$62,999, ≥$63,000, unknown) were evaluated. Location was classified as metropolitan, urban, or rural, determined by matching zip codes to rural-urban continuum codes from the United States Department of Agriculture Economic Research Service. Comorbidity status was described using the Deyo classification of the Charlson Comorbitidy score (0, 1, ≥2) [8]. Facility type was based on classification by the American College of Surgeons Commission on Cancer Accreditation program as a community cancer program, comprehensive community cancer program, academic/research program, or integrated network cancer center [5]. The region of the treating facility was classified as Northeast, Midwest, South, or West. Tumor characteristics included stage based on American Joint Committee on Cancer (AJCC) clinical stage, FIGO stage, or AJCC pathologic stage (IA2 or IB1), histology (squamous, adenocarcinoma, or adenosquamous), and grade (well, moderate, poorly differentiated, or unknown). Surgical modality was classified as intent-totreat and reported as minimally invasive surgery (MIS) or open. 2.4. Defining outcomes and process measures The primary process measure evaluated was National Comprehensive Cancer Network (NCCN) guideline-compliant surgical management. NCCN guideline compliance was defined as a radical hysterectomy with lymph node assessment. The secondary outcome of interest was 30-day mortality, 90-day mortality, and OS, reported as all-cause mortality, which includes death from cancer and other causes. 2.5. Statistical analysis
Hospital volume was computed using the number of simple and radical hysterectomies (Codes: 50, 51, 52, 53, 54, 60, 61, 62) performed at a given hospital in the previous year on patients with suspected, confirmed, or occult Stage IA2 or IB1 cervical cancer (C53.0 – C53.9). Hospital volume was analyzed as a categorical variable and divided into patient-level volume quartiles. Based on patient-level quartiles from procedures performed in the previous year, low volume was defined as an annual volume of ≤1, medium-low as a volume of 2, mediumhigh as a volume of 3–5, and high as a volume of 6–20 cases in the prior year (Table 1). As seen in Table 1, the volume of patients in each quartile are not evenly distributed as they are based on volume from the previous year. Sensitivity analyses were performed using volume as a continuous variable. The final analytical cohort excluded patients from 2010 due to the absence of surgical modality, leaving a total of 3469 patients for the analysis.
We sought to examine the effect of hospital volume on NCCN guideline-compliant surgical management and OS. An unadjusted analysis was performed to compare demographics and outcomes of interest across volume quartiles using X2 test. The results of these tests were described in the text to highlight a comparison of differences between centers in the highest quartile of volume (HVCs) and centers in the lowest quartile of volume (LVCs). However, all statistical tests were conducted across volume quartiles. OS was compared across volume quartiles using the Kaplan-Meir method and compared using the Log-rank test. Thirty-day and 90-day mortality were compared across volume quartiles using X2 test. A marginal multivariable Cox Proportional Hazards model was used to determine factors associated with all-cause mortality, accounting for hospital-level clustering. Results from the Cox Proportional Hazards models are reported as hazards ratios (HRs) with 95% confidence intervals (CIs). A sensitivity analysis comparing the effect of volume as a continuous variable was performed using a similar model. All hypothesis tests were two-sided. A p-value of b0.05 was considered statistically significant. Analyses were conducted using SAS version 9.4 (SAS institute Inc., Cary, NC).
2.3. Data collection
3. Results
For the 3469 patients included in the analysis, demographic characteristics including age at diagnosis (b40, 40–49, 50–59, 60–69, 70–79,
We identified 3469 women treated at 598 different hospitals, including 1058 (30.5%) at LVCs, 519 (15.0%) at medium-low volume
2.2. Defining hospital volume
Please cite this article as: E.M. Aviki, L. Chen, K. Dessources, et al., Impact of hospital volume on surgical management and outcomes for early-stage cervical cancer, Gynecologic Oncology, https://doi.org/10.1016/j.ygyno.2020.02.029
E.M. Aviki et al. / Gynecologic Oncology xxx (xxxx) xxx
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Table 2 Characteristics stratified by hospital volume quartiles. Characteristics
Number of patients Number of hospitals Age of diagnosis b40 40–49 50–59 60–69 70–79 N/=80 Race White Black Hispanic Other Unknown Year of diagnosis 2011 2012 2013 Insurance Uninsured Private Medicaid Medicare Other government/unknown Median household income b$38,000 $38,000–$47,999 $48,000–$62,999 $63,000+ Unknown Patient's residence area Metropolitan Urban Rural Unknown Comorbidity score 0 1 N/=2 Facility type Community cancer Comprehensive community ca Academic/research Integrated network cancer Facility location Northeast Midwest South West Stage 1A2 1B1 Histology Squamous cell Adenocarcinoma Adenosquamous Grade Well Moderate Poorly Unknown Hysterectomy type Simple Radical Route of surgery Open Minimally invasive Lymphadenectomy No Yes a
Low
Medium low
Medium high
High
p-Value
N
%
N
%
N
%
N
%
1058
(30.5)
519
(15.0)
1012
(29.2)
880
(25.4)
323 349 214 199 41 12
(30.5) (33.0) (20.2) (11.2) (3.9) (1.1)
174 153 106 66 15
(33.5) (29.5) (20.4) (12.7) (2.9)
(34.4) (33.6) (18.6) (8.6) (3.8)
a
(33.8) (30.7) (20.7) (11.0) (2.9) (1.0)
303 296 164 76 33
a
342 311 209 111 29 10
a
a
723 112 149 54 20
(68.3) (10.6) (14.1) (5.1) (1.9)
351 59 70 36
(67.6) (11.4) (13.5) (6.9)
642 113 176 75
(63.4) (11.2) (17.4) (7.4)
602 100 123 50
(68.4) (11.4) (14.0) (5.7)
a
a
a
a
a
a
353 366 339
(33.4) (34.6) (32.0)
182 186 151
(35.1) (35.8) (29.1)
332 295 385
(32.8) (29.2) (38.0)
293 320 267
(33.3) (36.4) (30.3)
59 611 225 124 39
(5.6) (57.8) (21.3) (11.7) (3.7)
36 303 111 55 14
(6.9) (58.4) (21.4) (10.6) (2.7)
86 566 199 126 35
(8.5) (55.9) (19.7) (12.5) (3.5)
86 509 155 90 40
(9.8) (57.8) (17.6) (10.2) (4.5)
176 258 308 315
(16.6) (24.4) (29.1) (29.8)
88 114 150 164
(17.0) (22.0) (28.9) (31.6)
220 268 245 278
(21.7) (26.5) (24.2) (27.5)
177 213 243 244
(20.1) (24.2) (27.6) (27.7)
a
a
a
a
a
a
a
a
899 121 17 21
(85.0) (11.4) (1.6) (2.0)
432 61 16 10
(83.2) (11.8) (3.1) (1.9)
836 135 14 27
(82.6) (13.3) (1.4) (2.7)
694 141
(78.9) (16.0)
a
a
37
(4.2)
910 120 28
(86.0) (11.3) (2.6)
445 62 12
(85.7) (11.9) (2.3)
891 105 16
(88.0) (10.4) (1.6)
766 93 21
(87.0) (10.6) (2.4)
78 488 356 136
(7.4) (46.1) (33.6) (12.9)
17 192 211 99
(3.3) (37.0) (40.7) (19.1)
14 341 513 144
(1.4) (33.7) (50.7) (14.2)
a
a
193 626 61
(21.9) (71.1) (6.9)
200 289 356 213
(18.9) (27.3) (33.6) (20.1)
114 102 183 120
(22.0) (19.7) (35.3) (23.1)
161 196 440 215
(15.9) (19.4) (43.5) (21.2)
108 221 396 155
(12.3) (25.1) (45.0) (17.6)
190 868
(18.0) (82.0)
78 441
(15.0) (85.0)
102 910
(10.1) (89.9)
106 774
(12.0) (88.0)
634 376 48
(59.9) (35.5) (4.5)
312 176 31
(60.1) (33.9) (6.0)
595 360 57
(58.8) (35.6) (5.6)
502 325 53
(57.0) (36.9) (6.0)
203 482 279 94
(19.2) (45.6) (26.4) (8.9)
103 228 142 46
(19.8) (43.9) (27.4) (8.9)
153 437 324 98
(15.1) (43.2) (32.0) (9.7)
129 436 221 94
(14.7) (49.5) (25.1) (10.7)
427 631
(40.4) (59.6)
178 341
(34.3) (65.7)
347 665
(34.3) (65.7)
274 606
(31.1) (68.9)
429 629
(40.5) (59.5)
217 302
(41.8) (58.2)
432 580
(42.7) (57.3)
392 488
(44.5) (55.5)
134 924
(12.7) (87.3)
39 480
(7.5) (92.5)
62 950
(6.1) (93.9)
34 846
(3.9) (96.1)
0.47
0.01
0.001
0.03
0.02
b0.001
0.65
b0.001
b0.001
b0.001
0.66
0.002
b0.001
0.35
b0.001
Fewer than 10 patients.
Please cite this article as: E.M. Aviki, L. Chen, K. Dessources, et al., Impact of hospital volume on surgical management and outcomes for early-stage cervical cancer, Gynecologic Oncology, https://doi.org/10.1016/j.ygyno.2020.02.029
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Table 3 Comparing NCCN guideline compliance across quartiles of volume. Characteristics
Low N
NCCN guideline compliance No Yes
%
Medium low
Medium high
High
N
N
N
%
%
p-Value % b0.001
461 (43.6) 191 (36.8) 363 (35.9) 283 (32.2) 597 (56.4) 328 (63.2) 649 (64.1) 597 (67.8)
*NCCN compliance was defined as having radical hysterectomy and lymph node dissection.
centers, 1012 (29.2%) at medium-high volume centers, and 880 (25.4%) at HVCs (Table 1). Most patients had stage 1B1 disease (86.3%), underwent radical hysterectomy (64.7%), and received MIS (57.6%). Additionally, most patients were white (66.8%), had private insurance (57.3%), and lived in metropolitan areas (82.5%). Hospital volume was found to be associated with race, year of diagnosis, insurance type, median household income, patient's residence area, facility type, facility location, stage, grade, hysterectomy type, and lymphadenectomy (Table 2). Uninsured patients comprised a larger proportion of patients at HVCs (9.8% vs 5.6%) and Medicaid patients comprised a larger proportion of patients at LVCs (21.3% vs. 17.6%) (p = 0.03). Patients residing in zip codes with a median household income b$38,000 were more likely to receive care at HVCs (20.1% vs. 16.6%) (p = 0.02). Patients living in metropolitan areas were more likely to receive care at LVCs (85.0% vs 78.9%) and those living in urban areas were more likely to receive care at HVCs (16.0% vs 11.4%)
(p b 0.001). HVCs were more frequently described as academic/research facilities (71.1%) whereas LVCs were more frequently described as comprehensive community cancer centers (46.1%) (p b 0.001). Women in the Northeast were more likely to receive care at low- or medium-low volume centers (53.9%) and those in the South were more likely to receive care at high- or medium-high volume centers (60.8%) (p b 0.001). Patients with Stage IA2 disease were more likely to receive care at LVCs (39.9%) while patients with Stage IB1 disease were more likely to receive care at medium-high and HVCs (30.4%) (p b 0.001). The majority of patients across quartiles of hospital volume underwent radical hysterectomy; performance of radical hysterectomy was 59.6% at LVCs-, 65.7% at medium-low, 65.7% at medium-high and 68.9% at HVCs (p b 0.001). Volume was not found to be associated with whether the procedure was done via an open or minimally invasive approach, with 59.5% of women at LVCs undergoing MIS compared to 55.5% at HVCs (p = 0.35). Lymph node assessment was more likely to occur at HVCs compared to LVCs (96.1% vs 87.3%, p b 0.001). We then examined NCCN guideline compliance defined as both radical hysterectomy and lymph node assessment across volume quartiles. In this analysis, patients at HVCs were significantly more likely to receive NCCN guideline-compliant surgical management compared to patients seen at LVCs (Table 3). Patients treated at HVCs were 11.4% more likely to receive NCCN-compliant surgical management compared to patients treated at LVCs (67.8% vs 56.4%, p b 0.001). In the initial unadjusted survival analysis, 5-year survival, 30-day mortality, and 90-day mortality were compared across volume quartiles (Table 4). There was no difference in 5-year survival across volume quartiles (Fig. 1). Thirty-day mortality was significantly lower at HVCs,
Table 4 Comparing survival outcomes across quartiles of volume. Survival characteristics
Low N
All 5-Year survival 95% CI 30-Day mortality 90-Day mortality a
%
1058
1 2
Medium low
Medium high
N
N
%
519 91.8 (89.4–93.8) 0.1 0.2
0 0
High %
1012 92.2 (89.1–94.4) 0.0 0.0
2 3
N
p-Value %
880 89.5 (86.3–91.9) 0.2 0.3
0 1
90.2 (86.9–92.8) 0.0 0.1
0.97 0.02a 0.09a
Chi-Square test performed in lieu of Fisher's Exact test.
Fig. 1. Overall survival expressed as months from diagnosis grouped by hospital volume quartiles. p = 0.97 by log rank test (n = 3469).
Please cite this article as: E.M. Aviki, L. Chen, K. Dessources, et al., Impact of hospital volume on surgical management and outcomes for early-stage cervical cancer, Gynecologic Oncology, https://doi.org/10.1016/j.ygyno.2020.02.029
E.M. Aviki et al. / Gynecologic Oncology xxx (xxxx) xxx
with 0 deaths in 880 patients at HVCs compared to 1 death in 1058 patients (0.1%) at LVCs (p = 0.02). There was no difference in 90-day mortality across volume quartiles (p = 0.09). In the adjusted survival model, hospital volume as a categorical variable was not an independent predictor of mortality (Table 5). A Table 5 Multivariable Cox Proportional Hazards model of mortality controlling for quartiles of volume. Characteristics
Adjusted hazards ratio
Number of patients Number of hospitals Age of diagnosis b40 40–49 50–59 60–69 70–79 N/=80 Race White Black Hispanic Other Unknown Year of diagnosis 2011 2012 2013 Insurance Private Medicaid Medicare Other government/unknown Uninsured Median household income b$38,000 $38,000–$47,999 $48,000–$62,999 $63,000+ Unknown Comorbidity score 0 1 N/=2 Facility type Academic/Research Community cancer Comprehensive community ca Integrated network cancer Stage 1A2 1B1 Histology Squamous cell Adenocarcinoma Adenosquamous Grade Well Moderate Poorly Unknown Hysterectomy type Simple Radical Route of surgery Open Minimally invasive Lymphadenectomy No Yes Prior year volume, quartiles Low High Medium high Medium low
3469 598
a
p-Value b 0.05.
Referent 0.83 (0.55–1.24) 1.31 (0.88–1.95) 1.20 (0.75–1.92) 1.45 (0.69–3.06) 5.90 (2.61–13.33)a Referent 1.02 (0.67–1.56) 0.38 (0.23–0.64)a 0.88 (0.46–1.71) 0.62 (0.08–4.51) Referent 1.01 (0.74–1.38) 0.91 (0.63–1.31) Referent 1.47 (1.02–2.10)a 1.85 (1.21–2.81)a 1.34 (0.66–2.73) 1.07 (0.57–2.02) Referent 0.92 (0.60–1.40) 0.93 (0.63–1.38) 0.70 (0.44–1.10) 1.83 (0.19–17.12) Referent 1.06 (0.72–1.57) 0.46 (0.14–1.52) Referent 1.83 (0.84–3.95) 1.36 (0.99–1.86) 1.10 (0.67–1.82) 0.54 (0.28–1.03) Referent Referent 0.71 (0.49–1.03) 1.39 (0.81–2.40) Referent 1.07 (0.63–1.83) 2.36 (1.34–4.16)a 0.80 (0.38–1.70) Referent 0.97 (0.72–1.30) Referent 1.27 (0.97–1.67) Referent 1.18 (0.65–2.16) Referent 1.07 (0.70–1.64) 0.99 (0.70–1.40) 1.03 (0.67–1.60)
5
sensitivity analysis was performed using volume as a continuous variable, and results were unchanged (Supplementary Table S1). In the Cox Proportional Hazards model, age ≥ 80, Medicaid and Medicare insurance, and having a poorly differentiated cervical cancer were independent predictors of increased mortality, and Hispanic race was an independent predictor of decreased mortality. 4. Discussion These findings suggest that patients with early-stage cervical cancer are more likely to receive guideline-recommended surgery and less likely to die within 30 days of surgery when treated at HVCs. However, treatment at HVCs does not appear to influence 90-day or all-cause mortality. This is one of the first analyses to specifically investigate the relationship between volume and outcomes in patients surgically treated for Stage IA2 and IB1 cervical cancer. Several previously published reports have examined the association between volume and outcomes in different populations of patients with cervical cancer. An early perspective database study of 1500 women who underwent radical hysterectomy for cervical cancer, surgeon volume was found to influence rates of postoperative medical complications, length of stay, and transfusion requirements. While surgeon volume had a strong impact on outcomes, hospital volume did not appear to have an independent effect on outcomes [9]. In a recent study of 5964Japanese women with FIGO stage IB1 - IIB cervical cancer treated with radical hysterectomy, the authors demonstrated lower rates of local recurrence and lower rates of all-cause mortality when patients were treated at HVCs [3]. In our cohort of patients with IA2 and IB1 cervical cancer, we did not find any differences in all-cause mortality across hospital volume settings. However, there are notable differences between our study and the Japanese study which might explain this. First, in our analysis and the perspective database study, the highestvolume hospital cohort included far lower-volume hospitals than those in the highest-volume cohort in the Japanese study [3,9]. For example, the perspective database study defined high volume as hospitals with an average annual volume of N7, and we defined high volume as hospitals with a prior year volume of between 6 and 20; whereas the Japanese study defined high volume as hospitals with an average annual volume of ≥21. This may indicate that, unlike the Japanese cohort, very few centers in the U.S. are truly high-volume enough to demonstrate mortality differences. Second, we included all patients with IA2 and IB1 cervical cancer who underwent hysterectomy, regardless of the type of hysterectomy performed. Extrafascial (simple) hysterectomy is technically less complex and carries lower risk of surgical complications; therefore, in our cohort volume would be less likely to affect mortality. Additionally, we did not include patients with FIGO Stage IB2 – IIB disease who might require an even more technically complex surgery for complete tumor removal and are often treated with radiation in lieu of surgery. By only evaluating radical hysterectomy across volume settings and by including higher-risk patients, differences in immediate surgical outcomes and longer-term oncologic outcomes may be more profound and therefore show a mortality difference. By including all surgically treated patients in our analysis, we were able to demonstrate higher rates of guideline-compliant surgery in patients treated at HVCs. In our analysis, 62.6% of patients received guideline-compliant surgery, a figure that increased to 67.8% at centers in the highest quartile of volume. This finding raises the question of whether performing simple hysterectomy in patients with Stage IA2 and IB1 cervical cancer results in higher rates of local recurrence. We were unable to evaluate rates of local recurrence due to limitations of the NCDB dataset. A recent study used the NCDB to evaluate survival differences associated with use of simple compared to radical hysterectomy in patients with IA2 and IB1 (2 cm or less). The authors found no survival difference between simple and radical hysterectomy for patients with Stage IA2 cancers. However, in patients with stage IB1 (2 cm or less) disease, simple hysterectomy was associated with a 55% increased risk of death compared to radical hysterectomy [10].
Please cite this article as: E.M. Aviki, L. Chen, K. Dessources, et al., Impact of hospital volume on surgical management and outcomes for early-stage cervical cancer, Gynecologic Oncology, https://doi.org/10.1016/j.ygyno.2020.02.029
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E.M. Aviki et al. / Gynecologic Oncology xxx (xxxx) xxx
Though there are few studies evaluating volume-outcomes in patients with early-stage cervical cancer, several studies have evaluated the association between volume and outcomes in patients with locally advanced cervical cancer [4,8,9]. A prior NCDB study of 15,194 women with locally advanced cervical cancer showed improved guidelinecompliant treatment using chemotherapy, external beam radiotherapy, and brachytherapy at higher-volume centers [4]. In this patient cohort, 44.3% received guideline-compliant treatment and guidelinecompliance was associated with improved survival. However, the impact of volume on survival outcomes was not evaluated [4]. An NCDB study of 20,766 women with stage IIB-IVA cervical cancer examined factors associated with survival and found that while hospital volume did not affect survival, adherence to treatment guidelines, and the specific hospital in which patients received care, impacted survival [5]. In fact, the specific hospital in which patients received care proved to be the strongest predictor of survival in that analysis. Lastly, an NCDB study of 27,660 women with stage IIB-IIIB cervical cancer who received radiation found that treatment at HVCs was independently associated with improved adherence to standard therapy and improved survival [6]. There are some notable limitations associated with our analysis. As is the case with any administrative dataset, we were unable to determine the factors that contributed to patients' or physicians' treatment decisions. A limitation specific to our analysis and use of the NCDB is that we were unable to determine whether rates of local recurrence differ across volume settings, which has important implications in this population. While initial treatment information is captured in the NCDB, subsequent treatment data is not chronologically catalogued, rendering analysis of local recurrence not feasible. We evaluated 5-year survival and all-cause mortality and found no difference across volume settings, which may indicate that, if differences in local recurrence are present, they do not appear to affect survival. Additionally, the cancer cases in NCDB include both suspected then confirmed cases and occult malignancies diagnosed after surgery on pathology alone. Amongst the 3469 patients, 167 patients lacked information regarding clinical or FIGO stage and instead were only pathologically staged raising suspicion that this group may represent occult malignancies not suspected at time of surgery. There are several additional limitations associated with analyzing hospital volume. First, within each hospital are potentially wide ranges of different provider volumes. To account for this, researchers can perform provider volume and hospital volume analyses in parallel or perform provider-level cluster analysis to mitigate the influence of any dominant provider on overall hospital volume. The NCDB does not provide data at the provider level, limiting our ability to perform these analyses. Second, there is the well-known potential for overestimation of volume-based differences when volume is evaluated as a categorical variable. To account for this, we included a sensitivity analysis for the multivariate model, which included volume as a continuous variable (Supplementary Table S1). In our analysis, volume was not a significant predictor of mortality as either a categorical or continuous variable. Moreover, the fact that hospital volume as a categorical variable was not significant in the adjusted survival analysis provides further reassurance that hospital volume is not a significant predictor of survival in these patients. Lastly, when considering the impact of high- and low-volume centers on patients with early-stage cervical cancer, fertility-preserving surgery is an important consideration that we did not incorporate into our analysis. There may be volume-dependent differences in the safety and efficacy of radical trachelectomy and other fertility-sparing options that were, therefore, beyond the scope of the current study. 5. Conclusions In summary, these findings provide important direction for future efforts aimed at elevating the quality of care delivered to patients with
early-stage cervical cancer. Notably, only 54.6% of patients treated at LVCs in our cohort received guideline-concordant surgery, with an 11.4% increase at HVCs. Though statistically significant, the difference in compliance between low and high volume centers did not lead to a difference in survival based on the high and low volume cutoffs generated by the dataset. Additional studies, focused on determining if there is a high-volume threshold that leads to a survival difference, are warranted. Additionally, public reporting of compliance rates, and focused quality improvement efforts that aim to identify and disseminate processes at high-performing hospitals, are needed to meaningfully improve the disparities in guideline compliance found across hospital volume settings. Supplementary data to this article can be found online at https://doi. org/10.1016/j.ygyno.2020.02.029.
Funding This study was funded in part through the NIH/NCI Support Grant P30 CA008748 (Dr. Wright).
Disclosures Dr. Wright reports personal fees from Clovis Oncology, personal fees from Tesaro, grants from Merck, outside the submitted work. Dr. Leitao is a consultant for Intuitive Surgical, outside the submitted work.
CRediT authorship contribution statement Emeline Aviki:Conceptualization, Formal analysis, Writing - original draft, Writing - review & editing.Ling Chen:Conceptualization, Formal analysis, Writing - review & editing.Kimberly Dessources:Formal analysis, Writing - original draft.Mario M. Leitao: Conceptualization, Formal analysis, Writing - review & editing.Jason D. Wright:Conceptualization, Formal analysis, Writing - review & editing.
Declaration of competing interest None declared. References [1] R.L. Siegel, K.D. Miller, A. Jemal, Cancer statistics, 2019, CA Cancer J. Clin. 69 (2019) 7–34. [2] National Comprehensive Cancer Network Clinical Practice Guideline in Oncology, Cervical cancer, Available at https://www.nccn.org/professionals/physician_gls/ pdf/cervical.pdf Date accessed: August 14, 2019. [3] K. Matsuo, M. Shimada, S. Yamaguchi, et al., Association of radical hysterectomy surgical volume and survival for early-stage cervical cancer, Obstet. Gynecol. 133 (2019) 1086–1098. [4] T.P. Robin, A. Amini, T.E. Schefter, et al., Disparities in standard of care treatment and associated survival decrement in patients with locally advanced cervical cancer, Gynecol. Oncol. 143 (2016) 319–325. [5] J.D. Wright, Y. Huang, C.V. Ananth, Influence of treatment center and hospital volume on survival for locally advanced cervical cancer, Gynecol. Oncol. 139 (2015) 506–512. [6] J.F. Lin, J.L. Berger, T.C. Krivak, et al., Impact of facility volume on therapy and survival for locally advanced cervical cancer, Gynecol. Oncol. 132 (2014) 416–422. [7] K.Y. Bilimoria, A.K. Stewart, D.P. Winchester, et al., The National Cancer Data Base: a powerful initiative to improve cancer care in the United States, Ann. Surg. Oncol. 15 (2008) 683–690. [8] R.A. Deyo, D.C. Cherkin, M.A. Ciol, Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases, J. Clin. Epidemiol. 45 (1992) 613–619. [9] J.D. Wright, S.N. Lewin, I. Deutsch, et al., The influence of surgical volume on morbidity and mortality of radical hysterectomy for cervical cancer, Am. J. Obstet. Gynecol. 205 (2011), 225.e1-7. [10] T.Y. Sia, L.C. Chen, A. Melamed, et al., Trends in use and effect on survival of simple hysterectomy for early-stage cervical Cancer, Obstet. Gynecol. 134 (2019) 1132–1143.
Please cite this article as: E.M. Aviki, L. Chen, K. Dessources, et al., Impact of hospital volume on surgical management and outcomes for early-stage cervical cancer, Gynecologic Oncology, https://doi.org/10.1016/j.ygyno.2020.02.029