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Cost-effectiveness analysis of laparoscopic and open surgery in routine Swedish care for colorectal cancer

  • Jacob GehrmanEmail author
  • Eva Angenete
  • Ingela Björholt
  • Eva Lesén
  • Eva Haglind
Open Access
Original Article
  • 184 Downloads

Abstract

Background

Laparoscopic surgery for colorectal cancer has been shown in clinical trials to be effective regarding short-term outcomes and oncologically safe. Health economic analyses have been performed early in the learning curve when adoption of laparoscopic surgery was not extensive. This cost-effectiveness analysis evaluates laparoscopic versus open colorectal cancer surgery in Swedish routine care.

Methods

In this national retrospective cohort study, data were retrieved from the Swedish ColoRectal Cancer Registry. Clinical effectiveness, resource use and unit costs were derived from this and other sources with nationwide coverage. The study period was 2013 and 2014 with 1 year follow-up. Exclusion criterion comprised cT4-tumors. Clinical effectiveness was estimated in a composite endpoint of all-cause resource-consuming events in inpatient care, readmissions and deaths up to 90 days postoperatively. Up to 1 year, events predefined as related to the primary surgery were included. Costs included resource-consuming events, readmissions and sick leave and were estimated for both the society and healthcare. Multivariable regression analyses were used to adjust for differences in baseline characteristics between the groups.

Results

After exclusion of cT4 tumors, the cohort included 7707 patients who underwent colorectal cancer surgery: 6060 patients in the open surgery group and 1647 patients in the laparoscopic group. The mean adjusted difference in clinical effectiveness between laparoscopic and open colorectal cancer surgery was 0.23 events (95% CI 0.12 to 0.33). Mean adjusted differences in costs (open minus laparoscopic surgery) were $4504 (95% CI 2257 to 6799) and $4480 (95% CI 2739 to 6203) for the societal and the healthcare perspective respectively. In both categories, resource consuming events in inpatient care were the main driver of the results.

Conclusion

In a national cohort, laparoscopic colorectal cancer surgery was associated with both superior outcomes for clinical effectiveness and cost versus open surgery.

Keywords

Cost-effectiveness analysis Laparoscopic surgery Colorectal cancer 

Colorectal cancer is the second most common form of cancer in men and third most common cancer in women [1]. Surgery, sometimes combined with radio(chemo)therapy, is primary curative treatment. The three surgical techniques used are: open-, laparoscopic and robot-assisted laparoscopic surgery. Laparoscopic surgery compared to open surgery for colon cancer has been reported with benefits such as less postoperative pain [2, 3, 4], earlier return of bowel function [2, 3], less intraoperative blood loss [3], and higher quality of life 30 days after surgery [5]. Clinical trials have also established similar long-term overall survival and recurrence [2, 3, 4]. Regarding rectal cancer, laparoscopic surgery has been deemed as safe and effective as open surgery in the long-term [6] with similar positive short-term outcomes as for colon cancer [7]. However, two recent trials were unable to demonstrate non-inferiority for laparoscopic versus open surgery regarding short-term surrogate oncologic end-points [8, 9]. Robotic rectal cancer surgery has been associated with lower conversion rate, 1 day shorter hospital stay and longer operating time compared to laparoscopic surgery according to a large database study [10]. However, the only large randomized trial found no significant differences in conversion to open surgery, short-term surrogate oncological end-points, complication rates or health-related quality of life within 6 months [11].

Laparoscopic and robot-assisted laparoscopic surgery face higher cost for basic surgical equipment and instruments, and longer operating time than open surgery [12, 13, 14, 15]. However, it has been reported that higher up-front costs can be offset by shorter length of hospital stay and less time in the intensive care unit [16, 17]. Several cost studies have been conducted in the setting of randomized controlled trials early in the learning curve of laparoscopic surgery for colorectal cancer [12, 13, 15, 18]. It can be expected that with increased experience, resource utilization will decrease. In addition, costs vary by the degree of uptake of laparoscopic technique, in regions/hospitals with high uptake costs were lower, as was demonstrated in a retrospective database study of some 1400 Australian patients treated at public hospitals [17]. In Sweden, the uptake of laparoscopic surgery for colorectal cancer was 5–10% in 2007 and 20–25% in 2014, according to the Swedish Colorectal Cancer Registry SCRCR [19, 20].

The aim of this study was to evaluate the cost-effectiveness of laparoscopic versus open surgery in colorectal cancer using national registry data.

Methods

Study population

All patients with a diagnosis of colorectal cancer with subsequent surgery during 2013 and 2014 registered in the SCRCR were included. The only exclusion criterion was preoperatively staged T4 cancer based on the fact that there is a higher risk for selection bias to open surgery in more advanced tumors. During 2013, the SCRCR did not indicate if the index procedure was performed using robot-assisted laparoscopic technique. To be consistent, we chose to include robot-assisted operations during 2014 in the laparoscopic group. Patients were followed for 1 year after index surgery using data from the Swedish National Board of Health and Welfare retrieving data on readmissions and resource consuming events in inpatient care, such as reoperations, and data on deaths from the Cause of Death Registry and sick-leave from the Swedish Social Insurance Agency. The study protocol was approved by the local ethics committee (Dnr 661-16).

Health economic methodology

This study evaluates costs from two perspectives: society (including cost of production loss due to sick-leave) and the healthcare sector alone. Health economic evaluation methods compare the incremental cost to the incremental health benefit of a treatment [21]. The benefit is expressed as the clinical effectiveness of a treatment. In this study, a composite clinical end-point was chosen as the measure of effectiveness.

Accounting for censoring because of death or loss to follow-up provides unbiased estimates of cost [22]. This study applied the method proposed by Bang and Tsiatis [23] in which data is partitioned into smaller time intervals and then each observation of cost is weighted by the inverse probability of the observation being censored. As a result, observations of cost with high probability of being censored are weighted greater than otherwise.

Costs are expressed in 2016 USD, SEK was converted from using purchasing power parity from OECD [24].

Effectiveness measure

The outcome measure used was defined as a composite end-point comprised of three types of clinical events: resource consuming events in inpatient care, readmissions and death.

Events were scored with one point each to calculate the outcome variable. Resource consuming events in inpatient care included events such as surgical procedures for example stoma closure or reoperation for wound dehiscence, transfusions, as well as rectoscopy. A readmission was defined in this study as a resource consuming event in inpatient care without a specified event recorded in the National Patient Registry.

For the initial 90 days after index surgery, every clinical event was counted (one point each), regardless of underlying cause. From day 91 and up to 1 year after index surgery, only procedure-related events were counted. To define procedure related causes for readmissions and deaths, two colorectal cancer surgeons (EA and EH) independently selected diagnoses using ICD10-codes. Procedure-related causes for resource-consuming events in inpatient care were determined before data collection using NOMESCO (Nordic Medico-Statistical Committee, version 1.16) chapters. If disagreement occurred, it was resolved by including the diagnosis or procedure as related. In sensitivity analyses, all events from index surgery up to 1 year were included. The list of predefined procedure-related events can be found in online supplementary material.

Resource use and unit costs

All resource use in this study was measured and valued using gross-costing [25]. It implies that the resource use associated with surgical technique is broken down into relatively large factors, e.g. resources consumed per average episode of inpatient stay associated with a certain NOMESCO-code. Thus, it was assumed that only the type and frequency of resource consuming event and readmission, differed between surgical techniques, not the exact amount of resources consumed during each event.

Resource-consuming events in inpatient stay, including the index operation, was costed by collecting the type of event (NOMESCO-code) and frequency from the National Patient Registry. Then, the corresponding unit cost was collected from a national database (Swedish Association of Local Authorities and Regions) covering approximately 75% of Swedish inpatient care, regardless of private or public care provider. Hospitals reporting to the database collected per patient resource use in their administrative systems during inpatient stay. The minimum requirement is to collect resources consumed per individual in the operating theater including anesthesia, intensive care unit, postoperative care including time in recovery room and medical service use on the ward, X-ray, laboratory tests, expensive materials and pharmaceuticals.

The resource use per readmission was costed using the DRG (diagnosis related group) weight as registered in the national patient registry. That DRG-weight was multiplied by the cost of one DRG weight ($5723), as determined for Sweden according to 2016 data.

The classification of sick-leave related to the procedure was based on the same definition as for clinical effectiveness. The productivity cost per sick-leave day was calculated using the human capital approach [21], the average monthly wage (Statistics Sweden) plus the social security and supplementary pension fees was multiplied by the per patient sick-leave days.

Statistical analysis

Baseline characteristics were compared at group level using median, inter-quartile range, mean values, standard deviation and 95% confidence intervals (CI) for continuous variables while for categorical variable frequencies and percentages were reported. The former was tested using Mann–Whitney U and the latter χ2 test, respectively. All tests were two-sided and 5% significance level was applied.

To account for differences in baseline characteristics that could potentially affect the estimation of mean effectiveness and cost between laparoscopic and open surgery, multivariate regression methods were used. The included potential confounders were surgical technique, preoperative tumor-stage, ASA-classification (American Society of Anesthesiologists), tumor location, sex and age. Because it is the sample arithmetic mean that is interesting to decision-makers, generalized linear models (GLM) were utilized for the primary analysis. Both distributional family and link function were tested using modified Park’s test [26], Pregibon link test [27], modified Hosmer–Lemeshow test [28] and the Copas-test [29]. To transform mean cost back to its original scale and avoid introducing covariate imbalances, recycled predictions were used for the two models estimated using GLM [22].

As both clinical resource use and costs typically exhibit a heavily right skewed distribution, non-parametric bootstrap was used to estimate percentile-based 95% CI [30].

The robustness of the results was explored in several sensitivity analyses. The clinical effectiveness measure was tested by including all events from 3 months and for the reminder of the follow-up instead of using predefined causes. The robustness of the cost difference was tested by varying costs per resource use category and surgical technique by 30% at a time. For both the clinical effectiveness and costs, ordinary least squares (OLS) regression was used as robustness check of the GLM.

Statistical analysis was performed using STATA® version 14 (StataCorp, College Station, Texas, USA).

Results

After excluding preoperatively staged T4-tumors a total of 7707 patients were eligible for analysis, 6060 patients in the open surgery group and 1647 in the laparoscopic surgery group.

Key baseline characteristics are outlined in Table 1, stratified for open and laparoscopic surgery as well as colon and rectal cancer. Median age was significantly higher in the open group than in the laparoscopic colorectal cancer surgery group, 74 vs. 72 (p value < 0.001) but not between open and laparoscopic rectal cancer surgery, 69 vs. 70 (p value = 0.067). A larger share of patients in the open colon cancer surgery group was categorized as ASA-grade three or four than in the laparoscopic colon cancer surgery group, indicating patients with more co-morbidities in the open group. There were significantly more missing data regarding preoperative T and N stages for open than laparoscopic surgery (both colon and rectal cancer).
Table 1

Demographic and clinical characteristics

 

Colon cancer

P value

Rectal cancer

P value

Open (n = 4346)

Lap (n = 1139)

Open (n = 1714)

Lap (n = 508)

Age

Median (IQR)

74 (67–81)

72 (65–80)

< 0.001

69 (61–76)

70 (63–77)

0.067

Sex, n (%)

 Male

2090 (48)

605 (53)

0.003

1103 (64)

266 (52)

< 0.001

 Female

2256 (52)

534 (47)

 

611 (36)

242 (48)

 

ASA, n (%)

 1

477 (11)

192 (17)

< 0.001

304 (18)

121 (24)

0.005

 2

2226 (52)

629 (55)

 

988 (58)

290 (57)

 

 3

1408 (33)

303 (27)

 

397 (23)

90 (18)

 

 4

175 (4)

11 (1)

 

17 (1)

5 (1)

 

 5

2 (0)

0 (0)

 

0 (0)

0 (0)

 

 Missing

58

4

 

8

2

 

T-stage, n (%)

 1–2

675 (30)

300 (39)

< 0.001

487 (30)

179 (37)

0.008

 3

1553 (70)

468 (61)

 

1128 (70

311 (63)

 

 Missing

2118

371

 

99

18

 

 N-stage, n (%)

 0

2176 (67)

669 (69)

0.417

705 (44)

220 (45)

0.502

 1–2

1054 (33)

304 (31)

 

914 (56)

266 (55)

 

 Missing

1116

166

 

95

22

 

M-stage, n (%)

 0

3833 (89)

1079 (95)

< 0.001

1574 (92)

482 (95)

0.018

 1

473 (11)

58 (5)

 

138 (8)

25 (5)

 

 Missing

40

2

 

2

1

 

Neoadjuvant chemotherapy, n (%)

 No

4250 (98)

1130 (99)

0.002

1389 (81)

456 (90)

< 0.001

 Yes

94 (2)

9 (1)

 

323 (19)

52 (10)

 

 Missing

2

0

 

2

0

 

Neoadjuvant radiotherapy, n (%)

 No

4330 (100)

1137 (100)

0.725

645 (38)

208 (41)

0.180

 Yes

10 (0)

2 (0)

 

1068 (62)

300 (59)

 

 Missing

6

0

 

1

0

 

Adjuvant therapy, n (%)

 No

2860 (68)

797 (71)

0.072

1123 (67)

364 (73)

0.010

 Yes

1355 (32)

331 (29)

 

554 (33)

134 (27)

 

 Missing

131

11

 

37

10

 

Hospital type, n (%)

 District hospital

1841 (42)

575 (50)

< 0.001

563 (33)

153 (30)

0.436

 County hospital

1476 (34)

259 (23)

 

587 (34)

175 (34)

 

 University hospital

1025 (24)

305 (27)

 

564 (33)

180 (35)

 

 Missing

4

0

 

0

0

 

BMI

 Median (IQR)

25 (23–28)

26 (23–28)

0.062

25 (23–28)

26 (23–28)

0.952

 Missing

373 (9%)

28 (2%)

 

45 (3%)

9 (2%)

 

Death within 12 months, n (%)

      

 No

3804 (88)

1081 (95)

< 0.001

1620 (95)

491 (97)

0.052

 Yes

542 (12)

58 (5)

 

94 (5)

17 (3)

 

P values are based on the Chi2 test, except for age that is tested using Mann–Whitney test. The tests do not account for missing data. ASA American Society of Anesthesiologists, BMI Body Mass Index, IQR Interquartile range

The unadjusted measure of clinical effectiveness is presented in Table 2. The difference in mean number of events was 0.33 (95% CI 0.23 to 0.43) in favor of laparoscopic surgery. Increased resource consuming events in inpatient care was the main contributor to this difference with 0.22 events (95% CI 0.13 to 0.30), followed by readmissions 0.07 (95% CI 0.03 to 0.11) and deaths 0.05 (95% CI 0.04 to 0.06). One reason for increased resource consuming events in inpatient care (n.b. data not shown) was more prevalent in the open surgery group were reoperation of wound dehiscence, 2.3% and 1.7% for open colon and rectal cancer surgery, respectively. After open rectal cancer surgery 4.8% of the patients were given blood transfusions compared to 1.7% in the laparoscopic surgery group.
Table 2

Mean unadjusted differences in clinical effectiveness and resource use open versus laparoscopic colorectal cancer surgery

 

Mean events open surgery

Mean events laparoscopic surgery

Difference in mean events

95% CI

Primary analysis, events

 Clinical effectivenessa

1.35 (1.87)

1.02 (1.67)

0.33 (4.47)

0.23–0.43

 Resource consuming events in inpatient carea

0.87 (1.51)

0.66 (1.33)

0.22 (3.60)

0.13–0.30

 Readmissionsa

0.39 (0.80)

0.33 (0.71)

0.07 (1.90)

0.03–0.11

 Deathsa

0.08 (0.28)

0.03 (0.18)

0.05 (0.63)

0.04–0.06

Secondary analysis

 Clinical effectiveness

1.86 (2.55)

1.40 (2.26)

0.46 (6.07)

0.32–0.59

 Resource consuming events in inpatient care

1.24 (2.08)

0.93 (1.78)

0.31 (4.93)

0.20–0.42

 Readmissions

0.51 (0.96)

0.42 (0.87)

0.08 (2.29)

0.03–0.11

 Deaths

0.10 (0.31)

0.05 (0.21)

0.06 (0.70)

0.03–0.08

Sick leave

 Sick leave, daysa,,b

29.9 (81.7)

29.0 (77.0)

0.9 (196.9)

− 3.5–5.3

 Sick leave, daysb

33.1 (85.8)

31.8 (80.4)

1.3 (206.5)

− 3.4–5.9

Numbers are mean (standard deviation)

aBased on predefined diagnoses and NOMESCO-chapters for readmission, resource consuming events in inpatient care and deaths, included in supplementary material

bSick leave was not part of the clinical effectiveness measure

As can be seen in Table 3, the adjusted mean difference between open and laparoscopic surgery was 0.23 events (95% CI 0.12 to 0.33), meaning that laparoscopic surgery patients on average had 0.23 events less than open surgery patients during 1-year follow-up.
Table 3

Mean adjusted differences in clinical effectiveness open versus laparoscopic colorectal cancer surgery

 

Difference mean

Standard error

95% CI

Clinical effectivenessa, b

0.23

0.05

0.12–0.33

Clinical effectivenessc

0.22

0.06

0.11–0.34

CI Confidence interval. Adjusted by TNM-stage, ASA-grade Age, Sex and tumor location (colon or rectal cancer) and surgical technique

aBased on predefined diagnoses and NOMESCO-chapters, included in Supplement 1

bGeneralized linear model with identity link and poisson family, bootstrap confidence interval and standard error based on 1000 replications

cOrdinary least squares

Results regarding societal and healthcare costs associated with the two surgical techniques are presented in Table 4. Since number of deaths differ between laparoscopic and open surgery, costs in the primary analysis were weighted according to the method proposed by Bang and Tsiatis [23]. The difference in mean costs for the societal perspective were $6698 (95% CI 4474 to 8922) and $6513 (95% CI 4644 to 8381) for the healthcare sector, respectively, in the unadjusted analyses. Not weighting costs made little difference, $6494 (95% CI 4360 to 8628) and $6363 (95% CI 4590 to 8135) for the societal and healthcare perspectives, respectively. The difference in unweighted total cost for the index operation was $3136 (95% CI 2492 to 3781). As seen in Table 4, resource-consuming events in inpatient care had the biggest impact on the difference in costs, $6065 (95% CI 4242 to 7887) followed by readmissions $448 (95% CI 232 to 664) and sick-leave $185 (95% CI − 914 to 1285).
Table 4

Mean unadjusted differences in cost (USD, $) open versus laparoscopic colorectal cancer surgery

 

Mean open surgery (standard deviation)

Laparoscopic surgery (standard deviation)

Difference (standard deviation)

95% CI

P value

Societal perspective

 Weighted

  Total costa

40 217

(41 370)

33 519

(38 768)

6698

(99 600)

4474–8922

< 0.0001

  Resource consuming events in inpatient carea

30 876

(34 196)

24 811

(30 585)

6065

(81 619)

4242–7887

< 0.0001

  Readmissiona

1885

(4120)

1437

(3346)

448

(9679)

232–664

< 0.0001

  Sick-leavea

7457

(20 412)

7271

(19 329)

185

(49 243)

-914–1285

0.7412

  Total cost

45 116

(46 020)

37 484

(44 010)

7632

(111 238)

5148–10 116

< 0.0001

  Resource consuming events in inpatient care

34 389

(38 471)

27 579

(35 651)

6811

(92 424)

4747–8874

< 0.0001

  Readmission

2415

(4956)

1871

(4255)

544

(11 747)

282–806

< 0.0001

  Sick leave

8312

(21 625)

8035

(20 360)

277

(52 111)

-886–1441

0.6403

 Unweighted

  Total costa

38 800

(39 724)

32 305

(37 087)

6494

(95 570)

4360–8628

< 0.0001

  Resource consuming events in inpatient carea

29 884

(32 672)

23 908

(27 304)

5976

(77 092)

4254–7697

< 0.0001

  Readmissionsa

1804

(3926)

1385

(3210)

418

(9255)

212–625

0.0001

  Sick-leavea

7049

(19 235)

6836

(18 125)

214

(46 358)

-821–1249

0.6855

  Total cost

43 223

(43 813)

35 894

(41 845)

7330

(105 875)

4965–9694

< 0.0001

  Resource consuming events in inpatient care

33 152

(36 919)

26 624

(34 329)

6527

(88 752)

4546–8509

< 0.0001

  Readmissions

2285

(4662)

1783

(4024)

502

(11 087)

254–749

0.0001

  Sick leave

7793

(20 190)

7496

(18 927)

297

(48 612)

-789–1382

0.5919

Health-care perspective

 Weighted

  Total costa

32 761

(35 091)

26 248

(31 194)

6513

(83 665)

4644–8381

< 0.0001

  Total cost

36 804

(39 679)

29 449

(36 831)

7355

(95 356)

5226–9484

< 0.0001

 Unweighted

  Total costa

31 750

(33 943)

25 470

(30 254)

6281

(80 965)

4473–8088

< 0.0001

  Total cost

35 430

(38 036)

28 398

(35 427)

7033

(91 466)

4990–9075

< 0.0001

 Index episode of care

  Costa

18 655

(12 738)

15 519

(7574)

3136

(28 849)

2492–3781

< 0.0001

Numbers are mean (standard deviation)

aBased on predefined diagnoses and NOMESCO-chapters, included in Supplementary material, otherwise based on all diagnoses and NOMESCO-chapters as recorded in registries

Adjusting for differences between the two techniques (Table 5) with regards to the potential confounders outlined in the method section, decreased the difference to $4505 (95% percentile-based CI 2257 to 6799) for the societal perspective and to $4480 (95% percentile-based CI 2739 to 6203) for the health care sector. Neither weighting the costs nor accounting for different relationships between mean and variance (GLM versus OLS) had significant impact on the results.
Table 5

Mean adjusted differences in cost (USD) open versus laparoscopic colorectal cancer surgery

 

Adjusted difference

Standard error

95% CI

P value

Societal perspective

 Total costa,b,c

4504

1178

2257–6799

< 0.001

 Total costb,d

4944

1346

2305–7584

< 0.001

 Total costa,d

4319

1131

2101–6537

< 0.001

 Total costd

4803

1279

2295–7310

< 0.001

Health-care perspective

 Total costa,b,c

4480

889

2739–6203

< 0.001

 Total costb,d

4781

1186

2456–7106

< 0.001

 Total costa,d

4236

979

2317–6155

< 0.001

 Total costd

4576

1134

2353–6800

< 0.001

CI Confidence interval. Adjusted by TNM-stage, ASA-grade age, sex and tumor location and surgical technique. The healthcare perspective does not include sick-leave

aBased on predefined diagnoses and NOMESCO-chapters, included in Supplementary material

bWeighted cost

cGLM with power link (0.3) and poisson family, mean value adjusted by recycled predictions, and standard errors, confidence intervals and p values are based on non-parametric bootstrap, 1000 replications

dOLS Ordinary least squares regression

The results from the deterministic sensitivity analysis can be found in Table 6. Since different regression methods did not change the results ordinary linear regression with the primary cost outcome as dependent variable was used for all sensitivity analyses. A 30% cost increase for resource consuming events in inpatient care for laparoscopic surgery or its mirror image of 30% decrease in resource consuming events in inpatient care for open surgery changed the results the most; in these analyses, open surgery was statistically significantly less costly than laparoscopic surgery. Assuming a 30% rise in sick-leave cost for laparoscopic surgery, or the equivalent decrease for open surgery, laparoscopic surgery was no longer statistically significantly associated with lower cost than open surgery.
Table 6

Mean adjusted deterministic sensitivity analysis of cost differences

 

Adjusted difference (open-laparoscopy) ($)

95% CI

Total costa,b

3242

1577–4906

Resource consuming events in inpatient care

 Laparoscopy − 30%

9119

7456–9119

 Laparoscopy + 30%

− 2511

− 4339–(− )2511

 Open minus − 30%

− 3473

− 4935–(− )3473

 Open plus +30%

10081

8033–10081

Readmission

 Laparoscopy − 30%

3640

1907–3640

 Laparoscopy + 30%

2968

1229–2968

 Open − 30%

2941

1215–2941

 Open + 30%

3668

1920–3668

Sick-leave

 Laparoscopy − 30%

5014

3310–5014

 Laparoscopy + 30%

1594

− 184–1594

 Open − 30%

1592

− 66–1592

 Open + 30%

5016

3177–5016

All costs have been estimated using ordinary least squares and regular confidence intervals

aBased on predefined diagnoses and NOMESCO-chapters, included in Supplementary material

bOLS Ordinary least squares regression

Because both clinical effectiveness and costs were in favor of laparoscopic surgery, no joint analysis of cost-effectiveness was warranted.

Discussion

To our knowledge, this is the first large study of routine care demonstrating that laparoscopic surgery for colorectal cancer was both more effective and less costly than open surgery in a 12-month perspective.

A recent study using Medicare data from the United States concluded that laparoscopic colon cancer surgery was associated with lower expenditures for Medicare beneficiaries [31]. However, the authors did not include rectal cancer surgery in the analysis, neither did they present societal costs for their health economic evaluation. Another large study [32] from the United States used a population-based administrative database to compare economic and clinical outcomes between laparoscopy and open surgery for different colorectal procedures. It concluded that laparoscopy was associated with lower costs and led to better clinical outcomes than open surgery. The study did not focus on colorectal cancer alone, did not study sick-leave costs, and compared charges, which is not directly comparable to cost. A European study [33] from the Netherlands studied accumulated hospital costs during 90 days after index surgery. Data was collected in a population-based database containing 29 hospitals and patients were stratified according to tumor location, ASA-grade and age. Overall, laparoscopy was significantly less costly than open surgery after colon cancer surgery but not after rectal cancer surgery. Again, only health care costs were studied and the follow-up was shorter than in the current study.

Laparoscopic surgery has previously been regarded as costlier to the healthcare sector than open surgery. Earlier studies include factors such as a steeper learning curve, conversion to open surgery and more expensive equipment. The cost difference reported in earlier studies, often RCTs, was not found in this study where we included routine care on a national basis and using a time when higher uptake of laparoscopic surgery was established. Uptake has been slow in Sweden, as can be seen in the percentage of laparoscopic surgery, varying around 20% for colon cancer and 25% for rectal cancer, when for example Denmark [34], Australia [35], Great Britain and Ireland [36] reached these levels some 5 years earlier. This could mean that with even higher uptake the difference in favor of laparoscopy could be larger.

Resource-consuming events in inpatient care was the main contributor to the difference in mean cost. In previous studies, bowel obstruction and incisional hernia [37] and wound infection [37, 38] have been reported to be more prevalent after open than after laparoscopic surgery. Many observations on preoperative clinical T and, to some extent, N-stage were missing in open surgery group. There were also more patients with distant metastases in the open group. It is possible that it was considered less necessary with detailed preoperative assessment in patients with distant metastases.

The national registries used in this study all have high validity [19, 39, 40]. Further, there are no reasons to believe that there was a systematic bias between the surgical techniques regarding classification of ICD-10 or NOMESCO codes. In Sweden, it is mandatory by law to send information regarding inpatient care to government agencies. In addition, the national register on cost per patient has high coverage, about 75% of all episodes of care are registered.

One limitation of this study is that patients were not randomized and thus possible selection bias due to observable and unobservable differences in patient characteristics between the two surgical techniques. To correct for observable imbalance in characteristics, patients in the open colon surgery group were generally frailer than in the other groups, a multivariate regression model was utilized. The results were robust as demonstrated by different regression methods as well as in various sensitivity analyses. The unobserved characteristics might still influence the results, but it is unlikely that those would explain the entire difference across surgical techniques. Moreover, Sheetz et al. [31] found robust evidence for laparoscopic surgery being less costly than open surgery for colon cancer even after controlling for unobserved characteristics using an instrumental variables approach.

For an economic evaluation to be conclusive, the preferred outcome measure is quality-adjusted life-years (QALY), which accounts for both survival and quality of life for the remainder of patients’ life. SCRCR had not yet begun collecting data regarding quality of life for the study period, i.e. estimation of QALYs was not possible. However, no study has concluded that quality of life would be worse after laparoscopic surgery than after open surgery, rather the opposite [5]. Together with the outcomes in this study, lead us to believe that such analysis would strengthen reached conclusions. Furthermore, the SCRCR did not differentiate whether the index procedure was performed using robot-assisted laparoscopic or laparoscopic technique during 2013 and in order to be consistent we decided to include robot-assisted laparoscopic technique in the laparoscopic group for 2014 as well, thus in the entire analysis. According to the SCRCR less than 10% of all rectal cancer prodecures in 2014 were operated on using robot-assisted laparoscopic technique. To avoid bias in cost estimates, the unit cost for the laparoscopic index procedures were applied also to the robot-assisted laparoscopic procedures performed during 2014. The costs accumulated during the 1-year follow-up are assumed to be related to type of index procedure, but it is not expected that laparoscopic and robot-assisted laparoscopic procedure for colorectal cancer would differ in resource-consuming events or readmission during the follow-up.

In the future, it would be interesting to redo the current analysis with quality of life weights collected from the SCRCR and to increase the knowledge of which resource consuming events in inpatient care that contributed to the difference in clinical effectiveness and cost found in this study.

In conclusion, laparoscopic surgical technique can be regarded as preferable from the patient, the societal and the healthcare perspective as primary treatment for colorectal cancer, except those with advanced tumors, as clinical effectiveness and costs were favorable compared with open techniques and other trials have reported no significant differences in long-term oncological outcome.

Notes

Acknowledgements

Open access funding provided by University of Gothenburg.

Compliance with ethical standards

Disclosures

Eva Angenete reports grant from Sahlgrenska University Hospital, ALF Agreement concerning research and education of doctors (ALFGBG-716581). Ingela Björholt and Eva Lesén reports remuneration for work paid to employer (PharmaLex Sweden AB) from University of Gothenburg, during the conduct of the study. Eva Haglind reports Grants from Swedish Cancer Society (2016-362), grants from ALF-Gbg (4307771) during the conduct of the study. Jacob Gehrman have no conflicts of interest or financial ties to disclose.

Supplementary material

464_2019_7214_MOESM1_ESM.pdf (55 kb)
Supplementary material 1 (PDF 55 kb)

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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.Department of Surgery, Institute of Clinical Sciences, SSORG–Scandinavian Surgical Outcomes Research Group, Sahlgrenska University Hospital/ÖstraSahlgrenska Academy, University of GothenburgGothenburgSweden
  2. 2.PharmaLex (Formerly Nordic Health Economics)GothenburgSweden

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