THE COSTS OF TREATING BREAST CANCER IN AUSTRALIA AND THE IMPLICATIONS FOR BREAST CANCER SCREENING

Aust. N . Z . J . Siirg. (1995) 65,485-49 I

ORIGINAL ARTICLE

THE COSTS OF TREATING BREAST CANCER IN AUSTRALIA AND THE IMPLICATIONS FOR BREAST CANCER SCREENING

J. R. G. BUTLER," C. M. FURNIVAL' AND R. F. G. HART$' *National Centre for Epidemiology urid Popiilutioii Heulth, The Austi~uliuii Nutioiiul University, Cutiheri.u. Austi.uliun

Capital Territory, 'Division (f Surgery, The Royal Brishune Hospital, Brishuiie, Qiieerisluiid arid $Depur.tnieiit of Applied Ecoiiomics, Victoria Unii7ersity of Technnlogy,,. Melhour.iie Victoriu, Austruliu

The aim of the study was to determine if there is a relationship between the stage of breast cancer at the time of detection and the costs of treatment and to assess whether any such relationship would have an influence on the cost of a mammographic screening programme.

A retrospective analysis of the stage at presentation for primary breast cancer and the treatment costs over the duration of treatment was made. Multiple regression analysis was employed, with treatment cost as the dependent variable and categorical variables to represent stage at detection. A total of 301 women whose treatment for breast cancer commenced at the Royal Brisbane Hospital participated in the study.

A statistically signficiant relationship was found between the stage of disease at the time of detection and subsequent treatment costs; more advanced stages of disease incurred higher treatment costs. This relationship was robust even after taking into account the age of patients, their discharge status, and differences between patients in the duration of treatment. When the effect of earlier detection on treatment cost was assessed in relation to a breast screening programme, cost savings were estimated to be in the range of 8-36% of total screening costs.

There are treatment cost savings to be gained from breast cancer screening as a result of the detection of earlier stages of disease. These treatment cost savings should be offset against the cost of a mammographic screening programme.

Key words: mammographic screening programme, treatment costs.

INTRODUCTION

The aim of a screening programme for breast cancer is to detect disease at a stage earlier than it would otherwise be detected. The advantages of screening for breast cancer include an improved probability of survival and the prospect of less radical surgical treatment for screen-detected cancers. Controlled trials of mammographic screening have demon- strated a higher proportion of cases detected at an early stage and a lower proportion of advanced disease compared with the distribution which is usually found in the community.'.'

Since mammographic screening is a costly exercise, any cost advantage for the treatment of early stage breast cancer could result in a significant saving which might offset the cost of a screening programme. Few estimates have been made of the costs of treatment for breast cancer, but it is known that the cost of treating advanced disease with chemotherapy or radiotherapy is substantial.'-' It seems probable that the cost of treating breast cancer is related directly to the stage of disease at the time of its detection."

In the following study, the actual costs of treatment have been measured for a sample of patients with breast cancer and a statistical analysis of the relationship between the cost of treatment and stage of the disease at the time of presentation has been undertaken.

Correhpondence: Dr Jim Butler. National Centre for Epidemiology and Population Health. The Australian National University, Canberra. Austral- ian Capital Territory 0200. Australia.

Accepted for publication I7 November lYY.1.

METHODS

Selection of sample and data collection The Royal Brisbane Hospital (RBH) is a metropolitan teaching hospital with more than 1000 beds and has facilities for the treatment of all stages of breast cancer. These facilities include a Surgical Breast Clinic and a multidisciplinary clinic for the treatment of advanced disease in the Division of Oncology (Queensland Radium Institute). Data on all patients discharged from the RBH are entered into the Queensland Hospital Information System (QHIS), a comput- erized database in which the cause of admission to hospital is specified according to the International Classification of Diseases (ICD). The unit record of the QHIS database is the discharge.

For the present study, a list was obtained from QHIS of all patients discharged from RBH for whom breast cancer was denoted as the principal, other or underlying condition from I February 1983 to 18 April 1989. Of the 1516 patients identified, 12 were males who were excluded from the study. The remaining 1504 patients included in the sampling frame gave rise to a total of 2770 discharges.

A random sample of these 1 504 women was obtained by listing the cases in order of the terminal digits of the Unit Record Number and obtaining progressively the case records until the sample size had been achieved. Women whose treatment had not commenced at RBH were excluded from the sample. Initially, 250 women were selected but a further sample of 51 women whose initial treatment commenced

486 BUTLER ET AL.

prior to 1985 was also obtained. The selection of 1985 allowed a minimum 5 year follow up for this subset of the sample. This procedure provided a total sample of 301 women of whom 146 (48.5%) had their initial treatment no later than the end of 1984. Fifty-one of these women were registered as ‘deceased’ on their last date of contact with RBH. Given the retrospective nature of the study it is not known how many women in the sample received follow-up management at sites other than the RBH because this information is not recorded in case records. However, it would be unusual for a woman whose breast cancer was initially treated at RBH to have subsequent treatment elsewhere.

The information extracted from the case record of each patient in the sample included total number of days hospital- ized, status at last discharge, pathology and radiology investigations, TNM Stage at presentation (determined by histopathology, clinical examination or a combination of these), surgical procedures (primary and other treatment), recurrence of disease, treatment of recurrent disease, number of follow-up visits, radiation treatment technique (number of courses, fractions, evaluation visits), chemotherapeutic drugs, other drugs and support services. Detailed information on radiation treatment was obtained from case records at the Queensland Radium Institute (QRI). This information related to all discharges arising from the treatment of breast cancer for each woman in the sample.

The date on which any of these treatments or services was provided was not recorded; to do so would have increased the complexity and cost of the data collection considerably. However, the distribution of treatment costs over time is important for the purpose of discounting, a technique which is used to take into account the lower present value of costs incurred in the future.’ In the absence of data on this distribution for purposes of discounting, treatment costs per year for each patient have been calculated as the total treatment costs divided by the number of years from the date of first admission to the date of last discharge.

Estimates of cost for each investigaiion, treatment or service, were based on costs current for the year 1987- 1988 and thus were dissociated from the effects of inflation on treatment costs.

Investigations carried out prior to the diagnosis of breast cancer were not included in the cost of treatment. Therefore the costs of open biopsy performed as a separate diagnostic procedure prior to definitive surgery were not included.

Staging

Al l cases were staged retrospectively using the information obtained from each patient’s hospital record. The staging system used was the 1987 revision ofthe International Union Against Cancer (UICC) system based on tumour size (T), nodal involvement (N) and metastatic status (M) (i.e. TNM staging) but details of lymph node involvement sufficient to allow a discrimination between Stage 3A and 3B were often not available from the case records.’ Accordingly, these two substages were amalgamated to a single Stage 3 in accord- ance with the earlier (1973) UICC system.’Of the 301 cases in the sample, 194 were staged on the basis of histopathology, 70 were staged exclusively on the basis of clinical examination, 36 were staged by a combination of both (e.g.

tumour size based on clinical examination and nodal involvement based on histopathology or vice versa) and one chart was missing when the data for staging were recorded.

Cost data

The data used to estimate treatment costs were based on maintenance expenditures for the RBH for the year 1987- 1988. These data did not include any capital costs as no economically meaningful estimates of such costs were available.

There are two components in the treatment costs for inpatients based on maintenance expenditures: a per diem cost of hospitalization and a treatment-specific component. The per diem component comprises a detailed estimate of the medical and nursing salary costs for the type of ward in which a breast cancer patient would stay, to which are added other per diem costs which are common to all patients in the hospital. The latter pan of this per diem component was based on the salary and on-costs of all staff other than medical. nursing. pathology and radiology together with the costs of food supplies, medical and surgical supplies, domes- tic charges, fuel. light and power, maintenance and repairs, administrative expenses etc. The per diem cost on this basis was $238.95.

The second component of the estimated treatment cost was a treatment-specific component calculated for each patient based on information extracted from their medical record. These treatment-specific costs included pathology, radiology, surgery, radiotherapy, drugs, follow-up visits and support services. In order to provide estimates of the per unit costs of each procedure in pathology and radiology, these costs were calculated by applying the Medical Benefits Schedule relativities (i.e. the ratio of the schedule fee for each item to the schedule fee for an arbitrarily selected benchmark item) to the pathology and radiology budgets for RBH. In the case of surgery, the cost of operating theatre procedures was estimated by calculating the labour costs of the procedure and adding to this the cost of pre-operative preparation and recovery room time.

For radiotherapy, treatment was costed on the basis of a matrix supplied by QRI showing. for each technique, the labour inputs required for its provision. An additional cost per visit to QRI, which was invariant with respect to treatment provided. was added to this cost. This per visit cost encompassed all other maintenance expenditures at QRI. The cost of drugs for each patient, including chemotherapeutic agents, was based on the relevant prices paid by the RBH pharmacy and dosages extracted from the medical record. Throughout this exercise, care was taken to ensure that these treatment-specific costs were not also included in any of the cost categories assigned on a per diem basis. Double counting therefore should not have occurred.

The total cost of treatment for each patient was therefore obtained by adding the treatment-specific cost for each individual patient to the per diem cost multiplied by the number of days of hospitalization. A more detailed account of the costing estimates used in this study has been published elsewhere. I(’

BREAST CANCER TREATMENT COSTS 487

RESULTS

Age of sample With respect to age at first contact, the sample is generally representative of the RBH population of breast cancer patients and the age distribution of breast cancer among Australian women (Fig. 1). In this figure, the RBH curve indicates the age at presentation of the 1504 women who underwent treatment during the study period and the sample curve records the age distribution of the 301 women who were selected randomly for detailed study. The average age at presentation for breast cancer in Australia in 1982 was 59.36 years," for RBH 59.92 years and for the sample 60.25 years.

Stage of disease The characteristics of the sample by stage at detection are presented in Table 1. Nearly half (49.5%) of the cases in the sample presented with Stage 2 disease and another one-fifth (20.6%) with Stage 1 disease. A one-way analysis-of-variance indicates that the mean age of presentation did not differ significantly between stages (F = 1.35; P = 0.25). Relatively few Stage 0 ( in sifu) cases occurred prior to the introduction of a mammographic screening programme at the RBH.

The duration of hospitalization for each stage of the disease differed significantly between stages. Table 1 shows a progressive increase in days of hospitalization with in- creasing stage at presentation (F= 8.80; P < 0.001). How- ever, the standard deviation demonstrates a considerable amount of variation around the mean number of days in hospital for each stage. It should be noted that this is the

total hospitalization during the period of study so that the average for each stage includes days of hospitalization for some women who were re-admitted for further treatment.

When the sampling procedure was adjusted to increase the sample size for women whose treatment commenced prior to 1985, this resulted in a subsample of 146 women for whom at least 5 years follow up was recorded since initial treatment commenced. There was no statistically significant difference between the stage at presentation or the age at presentation in this subset compared with the post-1985 subset. However, one striking difference between these subsets was a reduction of 7.5 days in the mean hospitalization of post- 1985 patients compared with the pre- 1985 patients (Table 2). This difference, which was evident in all stages except Stage 4, was statistically significant at the 5% level ( P < 0.05).

Prognosis The prognostic implications of the staging system used in this study are confirmed by the number of deaths in each stage of the disease as shown in Table 3. In this table the number of deaths is recorded as a proportion of the total number of cases in each stage; the proportion of deaths in each subset is clearly related to the stage of disease, from zero for Stages 0 and 1 disease to 54.2% for Stage 4 disease.

Costs of treatment The treatment costs for each stage of breast cancer based on the total number of days of hospitalization together with 'actual usage' cost estimates are shown in Table 4 (column C3). This shows a progressive rise in the cost of treating each stage of the disease from $3856 for Stage 0 ( in siru disease) to $14408 for Stage 4 disease.

l 6 T

Table 2. Numbers of cases and duration of hospitalization by stage at detection

0-4 10-14 20-24 30-34 4 0 4 5054 60-64 70-74 80*

Age group

Fig. 1. Percentage of cases presenting with breast cancer by age group, (-B-) Australia 1982. (-3-) Royal Brisbane Hospital and (---.---) Sample.

Table 1 . Characteristics of full sample by stage at detection

Stage

0 1 2 3 4 Total

No. cases Age at (%) presentation

(mean t s.d.)

13 (4.3) 54.69 2 11.69 62 (20.6) 62.00 f 13.45

149 (49.5) 59.07 -t 14.18 53 ( I 7.6) 61.40 f 16.51 24 (8.0) 63.46 2 14.08

301 (100.00) 60.25 It_ 14.41

No. days of hospitalization (mean 2 s.d.)

12.00 i- 7.02 12.00 2 4.78 26.07 f 27. I2 37.77 t 45.33 44.42 + 39.67 26.09 f 30.77

s.d.. standard deviation. Stage 0 is iri si/u disease.

Stage Pre- 1985 subsample Post- 1985 subsample No. No. days of No. No. days of

cases hospitalization cases hospitalization (mean f s.d.) (mean -t s.d.)

0 4 16.50 2 11.62 9 10.00 t 2.96 I 29 13.14 k 4.27 33 11.00 f 5.04 2 76 30.72 ? 26.50 73 2 I .22 +- 27.09 3 26 44.58 2 57.03 27 3 1.22 _t 29.85 4 I I 38.55 -+ 36.70 13 49.39 f 42.85 Total 146 29.90 -+ 33.60 155 22.50 2 27.48

s.d.. standard deviation. Stage 0 is in siru disease.

Table 3. Cases deceased at last discharge by stage at detection

Stage No. cases No. deceased o/c

0 13 0 0.0 I 62 0 0.0 2 I49 22 14.8 3 53 16 30.2 4 24 13 54.2 All cases 30 I 51 16.9

Stage 0 is iri .\itit di\ea\e.

488 BUTLER ET AL.

However, as these costs could be incurred over a period of some years, there is scope for the total cost of treatment to be discounted. In the absence of information on the actual dates on which treatments were provided, the treatment costs for each patient have been averaged over the number of years from the date of first admission to the date of last discharge for the purpose of discounting. This time period is referred to here as the ‘duration of treatment’. It differs from the ‘duration of follow up’ which is the time from the date of first admission to either the date of data extraction or the date of death.

The effects of using discount rates of 5 and 20% per year on the total cost of treatment are shown in columns C4 and C7, respectively, of Table 4. The effects of discounting are limited because of the relatively short mean duration of treatment of just over 1 year in the ful l sample and 1.69 years in the pre-I985 subsample. Table 5 presents data on the mean, the minimum and the maximum values of duration of treatment observed in our sample by stage at detection. The maximum duration of treatment observed ( 13 years) was for a patient with Stage 2 disease but it is clear from the mean values that the duration of treatment for most patients in the sample was no more than a few years. This is true in the pre- 1985 subsample also. Hence, although discounting does reduce the absolute values of mean treatment costs (both by stage and overall), i t does not substantially affect relative mean treatment costs by stage at detection even when a relatively high discount rate of 20% is used.

A detailed breakdown of treatment-specific (actual usage) cost components by stage of the disease is shown together with the per diem cost in Table 6 . For every stage, the ‘actual usage’ component which includes investigations and treatment is a small proportion of the total cost of care; the per diem costs of hospitalization form the larger proportion for every stage of the disease. Table 6 also shows the variations across stages in the costs for single modalities of therapy: these actual usage costs are exclusive of the aftercare (deliv- ered by RBH or at home) associated with each of the modalities. For surgery, actual usage costs do not vary greatly by stage. The categories which account for the bulk of the variation between stages in actual usage costs are radiotherapy and chemotherapy. Regarding diagnostic services, cost variation by stage is more marked for pathology than for radiology. Mean costs in each of these categories generally increase substantially the more advanced the disease is on presentation.

The effects of stage at detection and other relevant factors on treatment costs were analysed using multivariate statistical techniques. Specifically, multiple regression analysis was employed with categorical variables used to represent the stages of detection.’? This analysis indicates that the difference between treatment costs by stage are significant statistically. These differences continue to be significant even after allowing for the influence of three additional factors: age. discharge status (alive/deceased, again incorporated as

Table 4. Mean treatment costs for breast cancer by stage at detection using various measures of cost

Stage C3 c 4 c 7

0 3856 37723 35x0 ( I .OO) ( 1 .00) ( I .OO)

I 4330 42x9 41x5 (1.12) (1.14) (1.17)

2 921 I 8773 7766 (2.39) (2.32) (2 I .7)

3 12210 1 1x63 11051 (3.17) (3.14) (3.091

4 14408 14345 14157 (3.74) (3.X0) (3.95)

All stages X917 X622 7936

~- -~

Costs are expressed in Australian dollars ( 19x7- I 9 X X prices). Nunibers in parentheses are the ratios of treatment costs for each rtage to trratnient costs for Stage 0. for each cost measure (C3. C4 etc). C3 = ($238.9.5 X total number of days of hospitalization) + ’actual usage’ cost estimates (see text). ondiscotinred. C4 = C3 discounted at 5% per annuni. C7 = C3 discounted at 20% per annuni.

Table 5. Duration of treatment by stage at detection, full sample and pre-19x5 subsample

Stage Mean

0 0.54 I 0.45 2 1.35 3 I .OY 4 0.46

All stages I .O I

~ - ~~

Full \ample Minilnuin Maximum

0.00 5.00 0.00 6.00

0.00 9.00 0.00 2.00

0.00 13.00

0.00 1 3 . ~ )

Pre- 1985 subsample Mean Minimum Maximum

I .75 0.00 5.00 0.x3 0.00 h.00 2.20 0.00 13.00 I .62 0.00 Y .oo 0.64 0.00 2.00

I .69 0.00 13.00

~ ~ - - ~-

Duration of treatment was calculated as the number of years from the date of tirst admishion to the date of lust &charge. rounded to the nearest whole year. A duration of treatiiient of let\ than 6 months wa\ rounded down to mro years.

Table 6. Breakdown of undiscounted treatment cost estimates by stage at detection and by costs assigned on a per diem and actual usage basis ($. 1987-1988. n=301)

Stage Per Actual usage Total diem Surgery Surgery Pathology Radiology Radiotherapy Chemotherapy Other Follow- Support actual

drugs up visits services usage

0 2867 252 0 57 269 I30 4 I 155 121 9x9 I 2867 247 0 I33 202 444 I19 3 172 142 I462 2 6229 287 1 27 I 493 8x3 507 28 149 365 2982 3 9025 205 2 395 489 I162 3x5 32 89 425 31x4 4 10614 212 2 43 I 642 I I16 709 64 25 592 3795

All 6234 257 1 268 435 x2n 400 25 134 337 2683 stages

- _ _ _ _ _ ~ _ - _ _ _ _ - - (theatre) (ward)* ~ ._ __ - ~ -~

*The mean of a sinall number of minor procedures. e.g. paracentesis.

BREAST CANCER TREATMENT COSTS 4x9

Table 7. Predicted undiscounted treatment costs by stage at detection and discharge status

Stage Alive Deceased

0 4329

1 4445

2 6930 19075

3 8906 21 050

4 9740 21 884

~~

-

(270- 83 80) -

(2599-629 I )

(566 1-8 199) (16636-21 513)

(6775-1 I 036) ( 18 366-23 734)

(6482-12998) (18581-25 188)

Predictions obtained from multivariate sratistical analysh wing mean age at presentation of 60 years and mean duration of fol low up of 131X.S days. All costs are expressed in Ausrralian dollars ( 19X7-19XX prices). Numbers in parentheses are 9.5% prediction intervals.

a categorical variable), and time elapsed since the patient's first admission. The detailed results of this analysis have been described elsewhere. I"

The parameters obtained from our multiple regression analysis can be used to obtain predictions of treatment costs and the associated confidence intervals for patients alive and deceased at last discharge. These results are shown in Table 7. Since no deaths were recorded in Stage 0 or Stage 1 disease, no data are available for deceased patients in those categories, but for Stages 2 , 3 and 4 disease there is a substantial increase in cost of treatment of $12 145 for patients who subsequently died, compared with those who remained alive for the duration of the study.

DISCUSSION

Although breast cancer is the most common malignant tumour (apart from skin cancer) among women in Australia, there is little information about the costs of treating this condition. Breast cancer may present at any stage in its clinical course from the smallest palpable tumour to advanced disease with widespread distant metastases. Increas- ingly, breast cancer is being detected in mammographic screening programmes which offer an increased probability of disease control with a significant reduction in the risk of eventual metastatic disease. If the costs of treating breast cancer are related to the stage at detection, this may have important implications for the costing of a breast screening programme. If substantial savings in the cost of treatment can be made by the detection of disease at an early stage, these treatment cost savings can be offset against the cost of a screening programme.

Treatment cost variation The present study was designed to examine this question by estimating the cost of treatment of breast cancer according to the stage of disease at the time of presentation. While the evidence presented above supports the contention that costs are related directly to stage at presentation, it is recognized that clinicopathological staging is a relatively imprecise measure of prognosis. Clinical assessment of axillary lymph nodes is an inaccurate index of nodal metastases, so that any histopathological information together with objective meas-

urements of tumour size greatly strengthen the validity of a staging system. I' Even so, it is well known that factors such as histological grade, hormone receptor content. tumour- specific proteins etc., are independent variables which influence prognosis, yet none of these is included in current staging systems. Nevcrtheless, the data presented show a direct relationship between the stage at the time of presentation and the probability of death from disease in the duration of the study (Table 3). I t may therefore be concluded that as a generalization the staging system which was used provided a practical measure of the extent of disease at the time of presentation and also reflected the prognosis for each of these subsets.

If useful conclusions are to be drawn from a study of this type, there must also be some assurance that the sample examined is representative of women with primary breast cancer. Figure I confirms that this is so and, in the total sample of 301 women, the age distribution conforms not only to the pattern of all cases of breast cancer identified at the RBH but also to the age distribution of breast cancer throughout Australia. I ' I n this sample, the temporary decline in incidence which occurs at the time of menopause':' appears to be accentuated but it seems unlikely that this would have any influence on the results of this study. In relation to the pre- 1985 and post- 1985 subsamples, there was no significant difference in the mean age at presentation between these groups; however. analysis-of-variance showed that the variation in mean age by stage at detection did approach statistical significance in the post- 1985 group ( F = 2.24; P = 0.071, in favour of an earlier stage at detection among younger women. There were no significant differences in the percentage of cases presenting at each stage between the two samples.

The treatment costs were found to vary significantly by stage at presentation and this reflects in part differences in the duration of stay in hospital. This is shown clearly in Table I , where the total number of days of hospitalization by stage rises progressively from 12 days for Stages 0 and I disease to 44.42 days for Stage 4 disease. The standard deviation, particularly for Stages 2, 3 and 4 is large, due to variations in the course of the disease in individual patients. This, in turn, is due to the higher probability of recurrence in later stage disease together with variation in the onset and duration of recurrent disease.

The difference in the number of days of hospitalization between the pre-1985 and post- 1985 subsamples (seeTable 2) almost certainly rcflects changes i n policies of treatment which have developed i n recent years. These include a more rapid throughput of paticnts in surgical wards and the steps taken in recent times towards minimizing hospitalization during the treatment of advanced disease.

The method used for the costing of treatment takes into account the probable cost of hospitalization i n the types of ward which are used for the treatment of breast cancer (as opposed to the average cost of hospitalization in a metropolitan teaching hospital) together with specific actual costs which reflect the utilization of individual modalities of treatment. This mcthodology provides a secure basis for the results which are presented in Tables 4 and 6. In Table 4, the direct relationship between stage at the time of presentation and the mean cost of treatment is clearly shown, with

costs rising from an average of $3856 for Stage 0 disease to $14408 for Stage 4 disease. a ratio of 3.74 between these two stages.

These treatment cost estimates may be compared with those used i n a study by Eddy c t ul. in the USA." The estimates used in that study (calculated from US Medicare

who would otherwise die is instead cletcctetl with Stage 0 or 1 disease and survives. I n these circumstances, the savings which could be expected t o iiccruc would on itverage bc in the range of S 14 500 to S I 7 500 in undiscounted terms.

Implications for breast screening data) disaggregate only the cost of initial treatment by stage at detection. These estimates are as follows (US$): Stage 0, $5559: Stage I . $5880: Stage 2, $6150: Stage 3, $6540: and Stage 4, $6863. To the cost of initial treatment. the cost of continuing care per month ($239) and the cost of terminal care ($14053) must be added, where relevant. Hence. a Stage 4 woman receiving terminal care would be expected to have a treatment cost of $20916 (plus the cost of continuing care). Interestingly, this sum is 3.76 times the cost of initial treatment for a Stage 0 case which is about the same as the difference i n this series. Thus, the treatment cost relativities presented in this paper seem to be of a comparable magnitude.

In Table 6, the detailed break-down of actual usage costs shows that the direct labour costs for surgery form a very small component of the total treatment costs for breast cancer and vary only marginally by stage at presentation. I n the case of Stage 1 disease where surgery might be expected to be a major component of the cost of treatment, the direct labour costs of surgery account for only 5.7%. of the total treatment cost; overall, in the treatment of all stages, surgery accounts for a mere 2.9% of the cost of treating breast cancer. Although these estimates of surgical cost appear small, they are based on actual surgical labour costs (which reflect rates of remuneration) in Queensland public hospitals. Furthermore, they exclude the costs of hospitalization associated with surgery (which are included in the per diem component) and the costs of surgical aftercare which are a substantial component of the total cost of surgical care. Nevertheless, these estimates emphasize that in the global cost of treating breast cancer, the surgical procedure is a small component.

By far the largest component of treatment costs in all stages with the exception of Stage 0 disease is the cost of radiotherapy, and this exceeds the cost of chemotherapy in all stages, including Stage 4 disease. Although it is specula- tive, the trend towards the use of radiotherapy as an alternative to radical surgery for the treatment of Stages 1 and 2 disease could result in an increase in future costs of treatment. To some extent these could be offset by a reduction in hospital costs, as a consequence of less radical surgery. A complete resolution of this issue, however, would require some allowance for the direct costs of hospitalization and aftercare associated with surgery and radiotherapy.

The significance of the outcome of treatment upon the cost of treatment (Table 7) shows a substantial difference in costs for women who died during the period of the study compared with those who remained alive. Overall, the outcome of treatment is related to stage at the time of deteclion. However, the higher treatment costs of non- survivors compared with survivors for any given stage indicates that stage alone is not the sole predictor of treatment costs: outcome variation within stage reflects uncon- trollable differences in the biology of individual cancers.

Nevertheless, it is evident that substantial savings in treatment costs would be achieved if a Stage 2 , 3 or 4 patient

-

There is littlc doubt that these data have implications for thc overall costs of a breast cancer screening programme. The magnitude of the treatment cost savings which can he attained as a rcsult of maminographic screening depends upon the extent of the change in the stage distribution of cases presenting i n a screening programme conipared with no screening. As the stage distribution changes towards earlier detection iis a result of screening. overall tre;itment costs can be expected to be reduced.

An estimate of the magnitude o f treatment cost savings can be obtained by comparing the stage distribution of cases in our sample, which is typical of an unscreened population. with the stage distributions attained in randomized clinical trials of maminographic screening. We have taken the stage distributions achieved in the study groups in the Edinburgh Trial of Breast Cancer Screening' and the Malmo Trial I " as being illustrative of the stage distributions attainable in a screening programme. The Malmo Trial, which shows a much higher proportion of Stage I disease (64%, \ a s 32% in

Table 8. Stage distribution data from Royal Brisbnne Hospital sample and study groups i n Edinburgh and Malriio Trials, and weighted iiieiin treatment costs by stage

Stage Stage distribution of caws No. RBH NO. No. Malmo \onlple Edinburgh ~ d y group

( % ) \tudy group ( % ) (% 1

- ~-

0 13 (4.3) 40 (10.3) 61 (16.3) I 62 (20.6) 126 (32.0) 241 (64.4) 2 149 (49.5) I65 (41.9) 6X (18.2) 3 53 (17.6) 50 (12.7) 4 ( 1 . 1 ) 4 24 (X.0) 13 (3.3) 0 (0.0)

Total 301 ( 100.0) 394 ( I(K).O) 374 ( 100.0)

Treatment costs ($)

(RBH sample)

4320 4445 x727

I2 573 16322

Table 9. Treatment cost savings relative to upper and lower esti- inates of costs of ;i breast weening programme

~~~~

Using upper Using lower estimate of estimate of

cost o f cost of screening screen i ng

programme programme ~ - ~- ~

Cost per woiiiiin screened $127.5 I $XO.00 Cost of screening 1000 women $127 5 10 $80 000 No. cases detected X X Treatment cost savings from screening I000 women if stage distribution chnngrs from RBH experience to:

Edinburgh study group $10 304 $10304 (% of costs of screening) (X.I%) (12.9%)

Malmo study group $29 168 $29 168 ( % of costs ol' screening) (22.9% ) (36.5% )

BREAST CANCER TREATMENT COSTS 49 I

the Edinburgh study), may be a more appropriate reference for the stages of cancers detectcd in a contemporary screening programme. The relevant data are presented in Table 8.

The treatment costs by stage at detection shown i n Table 8 are the weighted sums of the predicted mean treatment costs from Table 7, with the weights being the proportion of cases alive or deceased at each stage from Table 3 . The mean treatment cost per case in any treated population can then be calculated as the weighted sum of treatment costs by stage, with the weights being the proportions of cases detectcd at each stage: these calculations give the following estimates of mean treatment costs per case for the threc alternative stage distributions shown in Table 8: RBH sample, S8938: Edinburgh, $7650: Malmo, $5292.

The implications for the costs of treatment under a breast screening programme are evident from these results. If mammographic screening were to result i n a shift in the stage distribution from that found in the RBH sample to that attained in the Edinburgh Study Group, the mean treatment cost per case would fall by $1288 or 14.4%. Altetiiatively. if the Malmo stage distribution were attained in a mammographic screening programme, an even larger reduction in mean treatment costs per case could be expected, ri: $3646 or 40.8%. The larger reduction gained from the Maltno example is a reflection of the greater proportions detected in Stages 0/1 in that trial compared with the Edinburgh Trial (Table 8).

How do these treatment cost savings compare with the costs of implementing a breast cancer screening programme in Australia? Two recent studies of breast cancer screening in Australia provide estimates of the total cost per woman screened (including recruitment, screen taking. diagnostic investigations and opeti biopsy) of $1 27.5 1 Taking these as upper and lower estimates of the cost per woman screened, the cost of screening 1000 women would then be $127510 and $80000 respectively (Table 9). Aus- tralian data suggest that the tirst round of mammographic screening would yield about eight cancers per 1000 women screened.I7 If we assume that the stage distribution for these cases is altered from the RBH sample experience to the Edinburgh stage distribution, the treatment cost savings to be offset against the screening costs would amount to 8- 13% of the cost of the screening programme. If the Malmo stage distribution were achieved, the treatment cost savings would amount to 23-37% of the cost of the programme. Under these terms, the potential cost savings per 1000 women screened in Australia are in the range $I0300 to $29 200, as shown in Table 9.

These calculations are indicative of the maximum treatment cost savings which could be expected, and are predi- cated on the assumption that the participation rate in an Australian screening programme is comparable to the participation rates in the Edinburgh and Malmo programmes. Furthermore, the treatment cost savings to be obtained in the second and subsequent rounds of screening would depend upon the number of cases detected in those rounds and consequent alteration in the stage at presentation.

In conclusion, this study confirms that the cost of treating breast cancer is related to the stage of disease at the time of presentation. A detailed analysis of these results shows that this relationship could be an important offset to the cost of a breast cancer screening programme.

and $80.

ACKNOWLEDGEMENTS The authors are grateful for the helpful co-operation of the Royal Brisbane Hospital, the Queenslatid Radium Institute and the Queenslatid Department of Health. A number of staff i n these organizations have assisted us with various aspects of the project. G. Cawdell and M. Brunello provided exceptional assistance with medical records, and G. Rawlitis with computer programming. This study hiis been funded by a grant from the Commonwealth Department of Community Services and Health to the Epidemiology and Prevention Unit , Quecnslmd Department of Health.

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Documents

THE COSTS OF TREATING BREAST CANCER IN AUSTRALIA AND THE IMPLICATIONS FOR BREAST CANCER SCREENING