• No results found

OBJECTIVE RESULTS CONCLUSION

N/A
N/A
Protected

Academic year: 2021

Share "OBJECTIVE RESULTS CONCLUSION"

Copied!
5
0
0

Loading.... (view fulltext now)

Full text

(1)

Urological Oncology

INSURANCE STATUS AND OUTCOMES AFTER RADICAL PROSTATECTOMY GALLINA

et al.

Health-insurance status is a determinant of the stage at

presentation and of cancer control in European men

treated with radical prostatectomy for clinically localized

prostate cancer

Andrea Gallina*‡, Pierre I. Karakiewicz*, Felix K.-H. Chun*†, Alberto Briganti*‡,

Markus Graefen¶, Francesco Montorsi‡, Jochen Walz†, Claudio Jeldres*,

Andreas Erbersdobler§, Andrea Salonia‡, Nazareno Suardi‡, Federico Dehò‡,

Thorsten Schlomm†, Vincenzo Scattoni‡, Alexander Haese†, Hans Heinzer†,

Luc Valiquette*, Patrizio Rigatti‡ and Hartwig Huland†¶

*Cancer Prognostics and Health Outcomes Unit, University of Montreal, Montreal, Quebec, Canada, †Department of

Urology, ¶Martini Clinic – Prostate Cancer Center, and §Institute of Pathology, University of Hamburg, Hamburg,

Germany, and ‡Department of Urology, Vita-Salute University, Milan, Italy

Accepted for publication 7 December 2006 A.G and P.I.K contributed equally to the manuscript

variables according to insurance status (private vs public). Means and proportions tests were complemented with logistic regression or Kaplan–Meier analyses. RESULTS

Serum prostate-specific antigen level

(P< 0.001), clinical stage (P< 0.001),

pathological Gleason sum (P= 0.02), positive

surgical margin rate (18.4% vs 25.4%,

P< 0.001), extracapsular extension rate

(17.7% vs 20.0%, P= 0.047) and seminal

vesicle invasion rate (9.6% vs 11.6%, P= 0.04)

were more favourable in privately insured patients. Conversely, the rate of lymph-node involvement was higher in those with private than public insurance (4.4% vs 3.3%,

P= 0.045). In univariate analyses addressing

pathological variables, private insurance

was invariably protective (all P< 0.05). The

Kaplan–Meier analyses showed that privately insured patients had a lower rate of BCR after

RP (log-rank P= 0.017).

CONCLUSION

Despite uninhibited access to healthcare, insurance status represents a rate-limiting variable, which affects stage at presentation and the outcome of cancer control.

KEYWORDS

insurance status, prostate cancer, outcome prediction

OBJECTIVE

To determine whether health-insurance status might result in more localized stage at presentation, more favourable stage at surgery and in a lower rate of biochemical recurrence (BCR), in patients diagnosed with prostate cancer and treated with radical prostatectomy (RP), as despite uninhibited access to healthcare, private and public health insurance are available in most European countries.

PATIENTS AND METHODS

In all, 4442 consecutive men had RP in two large European centres, of whom 2372 had public and 2070 had private health insurance. The groups were compared for several

INTRODUCTION

Many European countries enjoy publicly funded and general access to healthcare [1]. However, patients have the choice of purchasing additional ‘private’ coverage, which might provide several advantages. These include the opportunity of choosing among different healthcare providers, to have access to more senior consultants, and to ‘jump the queue’ if there are long waiting times. We postulated that these advantages might result in better outcomes. This question

was raised by several investigators who addressed the effect of health-insurance status on medical care use in American and Australian patients [2–6]. However, these analyses are of limited applicability in European countries, as there are substantial healthcare differences that distinguish these continents. To the best of our best knowledge, no study has addressed the influence of insurance status on clinical and pathological outcomes in European patients treated with radical prostatectomy (RP) for clinically localized prostate cancer.

We hypothesized that insurance status might affect clinical and pathological variables, and the rate of biochemical recurrence (BCR) after RP. To test this hypothesis, we analysed 4442 men diagnosed with prostate cancer and treated in two large European referral centres.

PATIENTS AND METHODS

Between October 1992 and July 2005, 5033 consecutive patients diagnosed with clinically localized prostate cancer had RP in two large

(2)

I N S U R A N C E S T A T U S A N D O U T C O M E S A F T E R R A D I C A L P R O S T A T E C T O M Y

European referral centres (Vita-Salute University, Milan, Italy; and University of Hamburg, Hamburg, Germany). The private and public systems in both countries are very similar and can be considered identical for analytical purposes. Patients with data unavailable before (433) or after RP (158), e.g. for initial PSA level, clinical stage or biopsy Gleason score, organ-confined disease, extracapsular extension (ECE), seminal vesicle invasion (SVI), lymph node invasion (LNI), positive surgical margins (PSM), or pathological Gleason score, were excluded from the study. Thus the analyses targeted 4442 evaluable patients. Comparisons were based on insurance status, i.e. public (2372) vs private (2070), according to billing information. Finally, BCR analyses were restricted to 2655 patients with available BCR status (1442 public and 1213 private). The clinical stage was assigned by the attending urologist as either T1c, T2 or T3 [7]. The PSA level before RP (Abbott Axym PSA assay, Abbott Park, IL, USA) was measured before a DRE and TRUS. All biopsies were

taken under TRUS guidance and were graded according to the Gleason system. All RP specimens were processed according to the Stanford protocol [8] and were graded according to the Gleason system [9] by genitourinary pathologists. Pathological stages were assigned according to the Partin stages [10]. A PSM was defined as cancer cells in contact with the inked specimen surface. No patient received neoadjuvant androgen therapy. For all patients, PSA levels were measured every 3 months in the first year, followed by biannual measurements in the second and annual measurements in the third and subsequent years after RP. BCR was

defined as a PSA level of >0.1 ng/mL and

increasing after an initial undetectable PSA. Patients with no evidence of BCR were censored at the last PSA follow-up.

The chi-square and independent sample t-test

were used respectively for comparing proportions and means. Variables assessed before RP were PSA level, clinical stage, biopsy Gleason sum and insurance status. Univariate logistic regression models were used to assess

the magnitude of the effect of insurance status on pathological stages, i.e. ECE, SVI, LNI and PSM. Conversely, Cox regression models were used to assess the magnitude of the effect of insurance status on the rate of BCR. The rates of BCR were graphically represented with Kaplan–Meier curves; all tests were two-sided with a significance level set at 0.05.

RESULTS

The patients’ characteristics are shown in Table 1; of all patients, 2372 had public and 2070 private insurance. The PSA level before

RP (P< 0.001) and clinical stage (P< 0.001)

were more favourable in privately insured patients, as were the pathological Gleason

sum (P= 0.02), ECE (P= 0.047), SVI (P= 0.04)

and PSM (P< 0.001), but the biopsy Gleason

sum did not differ (P= 0.3). Moreover, the

rate of LNI was higher in privately insured

patients (4.4% vs 3.3%, P= 0.045).

Table 2 shows the univariate models assessing the ability to predict ECE, SVI, LNI and PSM; in all regression analyses, insurance status was invariably a statistically significant predictor

(all P≤ 0.05). Private insurance had a

‘protective effect’ against ECE, SVI and PSM

(all odds ratios ≤0.86). However, private

insurance was associated with a 1.4-fold increase in the risk of LNI.

Table 3 shows the Cox regression models addressing BCR after RP. Insurance status was a statistically significant predictor of BCR

(P= 0.02) and publicly insured patients had a

higher risk of BCR after RP (odds ratio 1.2). Table 4 shows the actuarial BCR-free survival according to insurance status; the overall

mean (SD, range) follow-up was 30.7 (26.5,

0.13–129.7) months. Privately insured patients had a higher actuarial BCR-free survival at 2, 3, 4 and 5 years after RP. Figure 1 shows the overall BCR-free survival rates (a) and those according to insurance status (b). DISCUSSION

The advantages of private healthcare might favourably affect the outcome of patients with private health insurance. Based on these considerations, we hypothesized that private insurance might be associated with more favourable clinical and pathological stages, and with lower BCR rates in men treated with RP. The analyses showed that at diagnosis privately insured patients had TABLE 1 Descriptive characteristics of 4442 patients included in the analyses

Characteristic

Insurance status

P

Overall Public Private

Number of patients (%) 0.4 Total 4442 2372 (53.4) 2070 (46.6) Institution 1 3684 1956 (53.1) 1728 (46.9) Institution 2 758 416 (54.9) 342 (45.1) Age, years 0.3 mean (median) 62.9 (63.3) 62.9 (63.4) 62.7 (63.1) range 39–82 42–81 39–82 Preoperative PSA, ng/mL <0.001 mean (median) 8.6 (6.7) 9.0 (6.9) 8.2 (6.5) range 0.1–50.0 0.1–50.0 0.1–50.0 Clinical stage, n (%) <0.001 T1c 2919 (65.7) 1484 (62.6) 1435 (69.3) T2 1464 (33.0) 847 (35.7) 627 (29.8) T3 59 (1.3) 41 (1.7) 18 (0.9)

Biopsy Gleason sum, n (%) 0.3

≤6 3094 (69.7) 1630 (68.7) 1464 (70.7)

7 1184 (26.6) 650 (27.4) 534 (25.8)

≥8 164 (3.7) 92 (3.9) 72 (3.5)

Pathological Gleason sum, n (%) 0.02

≤6 2045 (46.0) 1060 (44.7) 985 (47.6) 7 2253 (50.8) 1221 (51.1) 1032 (49.9) ≥8 144 (3.2) 91 (3.8) 53 (2.6) PSM, n (%) 982 (22.1) 602 (25.4) 380 (18.4) <0.001 ECE, n (%) 841 (18.9) 475 (20.0) 366 (17.7) 0.047 SVI, n (%) 473 (10.6) 274 (11.6) 199 (9.6) 0.04 LNI, n (%) 170 (3.8) 78 (3.3) 92 (4.4) 0.045

(3)

G A L L I N A E T A L .

more favourable clinical characteristics than their publicly insured counterparts (Table 1), as shown by a lower PSA level (8.2 vs

9.0 ng/mL, P≤ 0.001), and lower clinical

stage (T1c in 69.3% vs 62.6%, P< 0.001).

These more favourable clinical characteristics, as expected, translated into more favourable

pathological Gleason sum (P= 0.02), a lower

rate of ECE (17.7% vs 20.0%, P= 0.047), SVI

(9.6% vs 11.6%, P= 0.04) and PSM (18.4% vs

25.4%, P< 0.001).

These findings suggest that private insurance status is associated with more favourable cancer characteristics at both the diagnosis and at RP. However, despite overall better stages in privately insured patients, the rate of LNI was counter-intuitively higher in the privately insured group (3.3% vs 4.4%,

P= 0.045). This finding might be explained

by the extent of pelvic lymphadenectomy, whereby there is possibly a more meticulous and more extensive dissection. We previously showed that, unlike other pathological stages, the rate of LNI could be strongly affected by the extent of dissection [11–13]. Therefore, more attention to detail and greater extent of pelvic lymphadenectomy appear to represent a valid explanation for the observed effect of insurance status on LNI.

Moreover, PSM rates are linked to surgical volume and surgical skill. Private insurance status might provide more experienced surgeons, which translates into a lower rate of PSM [14,15]. Conversely, ECE and SVI are strongly associated with the tumour volume and they cannot be influenced by surgical skill or expertise [16]. Thus, they only reflect cancer characteristics, and therefore these unfavourable outcomes are more frequent in the publicly insured patients.

The analyses of BCR rates confirmed the results reported for clinical and pathological stages, where private insurance was related to more favourable disease characteristics. The rate of BCR was 1.2 times higher in publicly

insured patients (odds ratio 0.81, P= 0.018),

as shown in Fig. 1B.

We chose not to include multivariate analyses, as these might obscure the effect of insurance status on the targeted outcomes. Adjusting for clinical stage, PSA level and biopsy Gleason sum, and pathological stage and PSM, corresponds to voluntarily removing the underlying effect of insurance status, which rests on the observed differences in clinical

variables at presentation. Thus, multivariate analyses are not applicable to hypothesis testing. Insurance status represents a proxy of household annual income, socio-economic status, education, social status and health-conscious behaviour. These variables were identified as potential reasons for the discrepancy in several North American and

Australian studies [6,17,18]. Roetzheim et al.

[18] showed that, in the USA, more advanced cancers, including prostate cancer, were diagnosed in the uninsured and in patients on

Medicaid. Moreover, Ford et al. [17] found that

lack of health insurance coverage represents a TABLE 2 The univariate LRMs for each outcome

Predictors

Odds ratio, P

ECE SVI LNI PSM

Total PSA 1.04, <0.001 1.08, <0.001 1.08, <0.001 1.04, <0.001

Clinical stage <0.001 <0.001 <0.001 <0.001

T1c vs T2 2.60 2.88 2.70 1.46

T1c vs T3 2.56 12.62 18.98 3.50

Biopsy Gleason sum <0.001 <0.001 <0.001 <0.001

≤6 vs 7 2.80 4.81 6.12 1.40

≤6 vs 8–10 2.59 19.78 15.60 2.36

Insurance status 0.86, 0.047 <0.81, 0.04 1.39, 0.046 0.66, <0.001

TABLE 3 Univariate Cox regression models assessing BCR after RP

Predictors Rate ratio P

Total PSA 1.05 <0.001

Clinical stage <0.001

T1c vs T2 2.01

T1c vs T3 5.43

Biopsy Gleason sum <0.001

≤6 vs 7 3.14

≤6 vs 8–10 7.76

Insurance status 0.86 0.02

TABLE 4

Actuarial BCR-free survival percentage according to insurance status

Years after RP Overall Private Public P

N 2655 1213 1442 1 84 85 83 0.2 2 78 80 77 0.06 3 74 77 72 0.003 4 70 74 67 <0.001 5 65 69 62 0.002

FIG. 1. The overall BCR-free survival rates (A) and those according to insurance status (B).

B 100 90 80 70 60 50 40 30 20 10 0 0 20 40 60 80 100 120 140 Time, months

Percentage of patients free from BCR

A 100 90 80 70 60 50 40 30 20 10 0 0 20 40 60 80 100 120 140 Time, months

Percentage of patients free from BCR

Private

Public Log rank p = 0.017

(4)

I N S U R A N C E S T A T U S A N D O U T C O M E S A F T E R R A D I C A L P R O S T A T E C T O M Y

barrier to prostate cancer screening and

treatment in American patients. Hall et al. [6]

analysed >14 000 Australian men diagnosed

with prostate cancer and showed that the 3-year survival was lower in those with no private health insurance. Therefore, the present findings are consistent with previous reports, where insurance status was a determinant of various outcomes of cancer control. Notably, none of these studies relied on multivariate analyses to detect the effect of health insurance status. This further validates our univariate approach to data analysis.

Taken together, the present results showed that privately insured patients treated with RP for localized prostate cancer present with more favourable clinical and pathological characteristics. These in turn translate into lower BCR rates and better outcomes. There are several limitations to the present study. Unfortunately, we could not directly compare our results to North-American or Australian findings where the effect of insurance status was considered. The inability to make valid comparisons stems from fundamental differences between the North-American and the European health-economic and care systems. Our findings might not be applicable to small institutions, where the choice between private and public insurance might not translate into important differences in the care provided or in the delay before RP. Furthermore, all the present patients included in the analyses represent a referral population, and thus the findings do not apply to a screened population. However, previous studies indicate that screening participation rates are higher in populations with a high socio-economic status [19–21]. Delays related to urological referral, biopsy, diagnosis and definitive treatment might have affected our findings. Unfortunately, we have no data to comment on the effect of delays between initial suspicion of prostate cancer and urological referral. Similarly, we cannot comment on the effect of any delay between the initial urological assessment and histological proof of prostate cancer. However, the delay between diagnosis and RP had no effect on the rate of BCR, and therefore it is unlikely that publicly insured patients had worse outcomes due to longer waiting times [22]. Finally, our results are not applicable to other healthcare systems, where insurance status could be significantly different from that in Italy or Germany.

In conclusion, privately insured patients had more favourable clinical and pathological tumour characteristics, which translated in better pathological and cancer control outcomes.

ACKNOWLEDGEMENTS

Pierre I. Karakiewicz is partially supported by the Fonds de la Recherche en Santé du Québec, the CHUM Foundation, the Department of Surgery and Les Urologues Associés du CHUM.

CONFLICT OF INTEREST

None declared.

REFERENCES

1 Buchmueller TC, Couffinhal A, Grignon M, Perronnin M. Access to physician services: does supplemental insurance

matter? evidence from France. Health

Econ 2004; 13: 669–87

2 Tarman GJ, Kane CJ, Moul JW et al. Impact of socioeconomic status and race on clinical parameters of patients undergoing radical prostatectomy in an

equal access health care system. Urology

2000; 56: 1016–20

3 Greene KL, Cowan JE, Cooperberg MR, Meng MV, DuChane J, Carroll

PR;Cancer of the Prostate Strategic

Urologic Research Endeavor (CaPSURE) Investigators. Who is the average patient

presenting with prostate cancer? Urology

2005; 66 (Suppl.): 76–82

4 Optenberg SA, Thompson IM, Friedrichs P, Wojcik B, Stein CR, Kramer B. Race, treatment, and long-term survival from prostate cancer in an equal-access

medical care delivery system. JAMA 1995;

274: 1599–605

5 Mullins CD, Snyder SE, Wang J, Cooke JL, Baquet C. Economic disparities in treatment costs among ambulatory Medicaid cancer patients. J Natl Med Assoc 2004; 96: 1565– 74

6 Hall SE, Holman CD, Wisniewski ZS, Semmens J. Prostate cancer: socio-economic, geographical and private-health insurance effects on care and

survival. BJU Int 2005; 95: 51–8

7 Greene F, Page D, Fleming I et al. eds,

American Joint Committee on Cancer. AJCC Cancer Staging Manual, 6th edn. New York, NY: Springer, 2002 8 McNeal JE, Villers AA, Redwine EA,

Freiha FS, Stamey TA. Histologic differentiation, cancer volume, and pelvic lymph node metastasis in adenocarcinoma of the prostate. Cancer

1990; 66: 1225–33

9 Gleason DF and the Veterans Administration Cooperative Urological Research Group. Urologic Pathology. Philadelphia: Lea & Febiger, 1977 10 Partin AW, Kattan MW, Subong EN

et al. Combination of prostate-specific

antigen, clinical stage, and Gleason score to predict pathological stage of localized prostate cancer. A multi-institutional

update. JAMA 1997; 277: 1445–51

11 Briganti A, Chun FK, Salonia A et al. Validation of a nomogram predicting the probability of lymph node invasion based on the extent of pelvic lymphadenectomy in patients with clinically localized

prostate cancer. BJU Int 2006; 98: 788–93

12 Briganti A, Chun FK, Salonia A et al. A nomogram for staging of exclusive nonobturator lymph node metastases in men with localized prostate cancer. Eur Urol 2007; 51: 112–20

13 Briganti A, Chun FK, Salonia A et al. Validation of a nomogram predicting the probability of lymph node invasion among patients undergoing radical prostatectomy and an extended pelvic

lymphadenectomy. Eur Urol 2006; 49:

1019–27

14 Eastham JA, Kattan MW, Riedel E et al. Variations among individual surgeons in the rate of positive surgical margins in radical prostatectomy specimens. J Urol

2003; 170: 2292–5

15 Hernandez DJ, Epstein JI, Trock BJ, Tsuzuki T, Carter HB, Walsh PC. Radical retropubic prostatectomy. How often do experienced surgeons have positive surgical margins when there is extraprostatic extension in the region of the neurovascular bundle? J Urol 2005;

173: 446–9

16 Nelson BA, Shappell SB, Chang SS et al. Tumour volume is an independent predictor of prostate-specific antigen recurrence in patients undergoing radical prostatectomy for clinically localized

prostate cancer. BJU Int 2006; 97: 1169–

72

17 Ford ME, Vernon SW, Havstad SL, Thomas SA, Davis SD. Factors

(5)

G A L L I N A E T A L .

influencing behavioral intention regarding prostate cancer screening among older African-American men. J Natl Med Assoc 2006; 98: 505–14 18 Roetzheim RG, Pal N, Tennant C et al.

Effects of health insurance and race on early detection of cancer. J Natl Cancer Inst 1999; 91: 1409–15

19 Duffy CM, Clark MA, Allsworth JE.

Health maintenance and screening in breast cancer survivors in the United

States. Cancer Detect Prev 2006; 30: 52–7

20 Parker PA, Cohen L, Bhadkamkar VA

et al. Demographic and past screening

behaviors of men attending a free community screening program for prostate cancer. Health Promot Pract

2006; 7: 213–20

21 Swan J, Breen N, Coates RJ, Rimer BK, Lee NC. Progress in cancer screening practices in the United States: results from the 2000 National Health Interview

Survey. Cancer 2003; 97: 1528–40

22 Graefen M, Walz J, Chun KH, Schlomm T, Haese A, Huland H. Reasonable delay of surgical treatment in men with localized prostate cancer – impact on

prognosis? Eur Urol 2005; 47: 756–60

Correspondence: Pierre I. Karakiewicz, Cancer

Prognostics and Health Outcomes Unit, University of Montreal Health Center (CHUM), 1058, rue St-Denis, Montréal, Québec, Canada, H2X3J4.

e-mail: [email protected]

Abbreviations: RP, radical prostatectomy;

BCR, biochemical recurrence; ECE,

extracapsular extension; SVI, seminal vesicle

invasion; LNI, lymph node invasion; PSM,

Figure

Table 2 shows the univariate models assessing  the ability to predict ECE, SVI, LNI and PSM; in  all regression analyses, insurance status was  invariably a statistically significant predictor  (all  P ≤  0.05)
TABLE 3  Univariate Cox regression models  assessing BCR after RP

References

Related documents

Based on the review of previous studies, the research finally resulted in identifying Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI)

The second challenge, which is ignored in Washington and barely recognized elsewhere, concerns the pressing needs that have been neglected by the federal government since the Nixon

 Rooted floating:  These flowering plants are rooted in the sediment.  

The Higher Education Academy (2017) recommends embedding health and wellbeing within the curriculum, offering examples of good practice and making encouraging

This standards document is to be used for any projects on the University of Calgary campus that involves the voice and data distribution system or the facilities that house them..

Things are different for the bandwidth usage: at the beginning of the system deployment, the bandwidth usage might not be too much; but it might be

Specifically, we give a van Benthem-Rosen characterization theorem of WAML based on an intuitive notion of bisimulation and show that each basic WAML system Kn lacks

Interestingly, while three mental health conditions were associated with not achieving diabetes care for spe- ci fic care goals, this was not for the same goals, and not all