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Prognostic Significance of Extent of Disease in Bone in Patients With Androgen-Independent Prostate Cancer

From the Genitourinary Oncology Service, Division of Solid Tumor Oncology, Department of Medicine; Nuclear Medicine Service, Department of Medical Imaging; and Department of Biostatistics and Epidemiology, Memorial Sloan-Kettering Cancer Center, New York, NY; and Janssen Research Foundation, Titusville, NJ.

Address reprint requests to Howard I. Scher, MD, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, New York, NY 10021; email scherh{at}mskcc.org

	ABSTRACT

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION REFERENCES

 
PURPOSE: To evaluate the prognostic significance of a bone scan index (BSI) based on the weighted proportion of tumor involvement in individual bones, in relation to other factors and to survival in patients with androgen-independent prostate cancer.

PATIENTS AND METHODS: Baseline radionuclide bone scans were reviewed in 191 assessable patients with androgen-independent disease who were enrolled onto an open, randomized trial of liarozole versus prednisone. The extent of skeletal involvement was assessed by scoring each scan using the BSI and independently according to the number of metastatic lesions. The relationship of the scored bone involvement to other known prognostic factors was explored in single- and multiple-variable analyses.

RESULTS: In single-variable analyses, the pretreatment factors found to be associated with survival were age (P = .0446), performance status (P = .0005), baseline prostate-specific antigen (P = .0001), hemoglobin (P = .0001), alkaline phosphatase (P = .0002), AST (P = .0021), lactate dehydrogenase (P = .0001), and treatment (P = .0098). The extent of osseous disease was significant using both the BSI (P = .0001) and the number of lesions present (P = .0001). In multiple-variable proportional hazards analyses, only BSI, age, hemoglobin, lactate dehydrogenase, and treatment arm were associated with survival. When the patient population was divided into three equal groups, with BSI values of < 1.4%, 1.4% to 5.1%, and > 5.1%, median survivals of 18.3, 15.5, and 8.1 months, respectively, were observed (P = .0079).

CONCLUSION: The BSI quantifies the extent of skeletal involvement by tumor. It allows the identification of patients with distinct prognoses for stratification in clinical trials. Further study is needed to assess the utility of serial BSI determinations in monitoring treatment effects. The BSI may be particularly useful in the evaluation of agents for which prostate-specific antigen changes do not reflect clinical outcomes accurately.

	INTRODUCTION

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION REFERENCES

 
PATIENTS WITH metastatic androgen-independent prostate cancer comprise a heterogeneous group representing a range of prognoses. Improving the ability to stratify risk and to predict outcome is important for counseling patients, designing and reporting clinical trials, and selecting patients for whom aggressive treatment approaches might be considered.^1-5 Pretreatment clinical parameters that have been used to predict either response to treatment or survival include changes in weight,² performance status,^3,4 and the presence or absence of bone pain.³ Tumor characteristics such as grade⁵ and pretherapy biochemical parameters such as hemoglobin (HgB),^4,5 acid phosphatase,^2,4-6 lactate dehydrogenase (LDH),^7,8 and alkaline phosphatase (an indirect marker of bone involvement)^2,3 have also been shown to be prognostic for survival. Mixed results have been observed with baseline prostate-specific antigen (PSA) levels, with a relationship between PSA and outcome observed in some⁹ but not in other^10-13 series of patients with androgen-independent disease.

In contrast to prognostic analyses based on patient and tumor factors, few studies have focused on quantifying or stratifying risk according to the extent of bone involvement, the most frequent site of spread of prostate cancer.^14,15 Likewise, few studies have evaluated ways to quantify changes in serial bone scintigraphy in relation to other clinical outcomes in a reproducible way.¹⁶ One method designed to determine the percentage of bone involvement in selected regions of the skeleton was abandoned after the variability of the estimation was noted.¹⁷ Other systems based on measurements of total radiotracer uptake in the skeleton or retention in specific regions of interest have been reported but have not translated into routine practice.^18,19 A simplified staging system based on a visual inspection of the patterns of spread (axial versus appendicular)²⁰ showed a statistically significant association with survival but was limited by the poor discrimination of the survival outcomes between two of the three groups. Similarly, a scale based on a count of the number of lesions was shown to be predictive when there were less than five or more than 20 lesions, but discrimination was lost in the middle groups. Particular difficulties were encountered when trying to quantify areas where the lesions had coalesced into large single areas.²¹

At Memorial Sloan-Kettering Cancer Center, we recently developed a bone scan index (BSI) to quantify the extent of skeletal involvement by tumor. It is based on the known proportional weights of each of the 158 bones that were derived from the reference man, a standardized skeleton in which autopsy-based individual bone weights were reported for the average adult.²² A preliminary analysis showed that changes in the BSI paralleled changes in PSA.²³ The interobserver variability of the measure among blinded reviewers was less than 10% in the 0% to 20% range, where the majority of patients fall. Intraobserver estimations showed correlation coefficients of .97 (reader 1) and .94 (reader 2) using a simple correlation analysis (P < .001) when the same group of scans were interpreted after a 2-year interval by the same individual. Calculating the BSI takes an average of 13.5 minutes per reader with a manual method of assessment.²⁴ An automated method using a computer algorithm with image segmentation is under development to reduce the evaluation time.²⁵ In the present study, we assessed the relationship between BSI and survival in relation to other known prognostic factors.

	PATIENTS AND METHODS

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION REFERENCES

 
Study Population
All patients in the current study were enrolled from November 1991 through November 1994 in an open, randomized trial of liarozole 150 mg orally bid versus prednisone 10 mg orally bid (USA-Janssen 22). Entry required histologically confirmed prostate cancer; disease progression after chemical or surgical castration; adequate hematologic, hepatic, and renal reserve; the ability to take oral medication; and an Eastern Cooperative Oncology Group (ECOG) performance status of 3 or less. Written informed consent was obtained before treatment. Study outcomes included response proportions, time to progression, and overall survival, the details of which will be reported separately (data on file, Janssen Pharmaceutica, Titusville, NJ). The effect of the individual treatments was not the end point of this analysis. The baseline variables analyzed were age, ECOG performance status, PSA, HgB, alkaline phosphatase, AST, LDH, BSI, number of bone lesions, and treatment arm. All scans were interpreted blindly with respect to treatment arm. Variables with skewed distributions, such as PSA, were fit in the model both in their natural form and using a logarithmic transformation.

Of the 220 patients enrolled in the trial, 191 patients (87%) had a radionuclide bone scan at entry that was available for independent review; two patients had normal scans. All scans were interpreted by one reviewer (S.M.L.), and extent of disease was determined according to the number of lesions²¹ and the BSI.²⁴

Numeric counting.
The total number of lesions was determined by counting each discrete lesion, as previously described.²¹ Because of the difficulty of assigning a number to a bone where a number of lesions had coalesced, single confluent bones were assumed to have a standard maximum number of lesions as follows: rib, six; clavicle, 10; vertebrae, four; pubis, 10; and large bones such as the humerus, femur, and large bones of skull, 20.

The Memorial BSI.
Each bone was considered individually and assigned a numeric score representing the product of the percentage involvement with tumor times the known weight of the bone derived from the reference man.²² The BSI is the sum of the numeric scores for each bone in the skeleton.

Statistical Analysis
All baseline parameters were analyzed as dichotomous and continuous variables using specific cut points (normal versus abnormal, or PSA range as defined) in life-table and proportional hazards regression analyses. In the analysis of survival, patients who died of any cause were classified as failures. Patients who were still alive or who were lost to follow-up during the study period were coded as censored. Survival was defined as the time interval from the date of entry onto the study to the end point of the trial (death or censoring). The Kaplan-Meier method²⁶ was used to derive the survival function, and the log-rank test²⁷ was used to determine whether these clinical variables were associated with survival by using the LIFETEST procedure in SAS.²⁸ Proportional hazards regression analysis was used to estimate relative risks (RRs) and their 95% confidence intervals in data analysis.^29,30 RRs for continuous variables indicate the increased (or decreased) risk of deaths associated with a one-unit increase of a continuous variable.

The association between BSI and survival was explored using the BSI as a continuous value and separately for each cohort representing the patients divided into three equal groups according to the overall range of BSI values. For the assessment of a possible BSI-survival relationship, dummy variables were used to estimate the risk ratios for each of the three BSI groups in the proportional hazards model. The presence of a trend for BSI as an ordered variable was assessed by assigning a score j to the jth BSI level and treating the score as a continuous variable in the proportional hazards model. To assess the contribution of BSI toward predicting survival, all parameters that were significant at the .05 level in single-variable analysis were included in the multiple-variable proportional hazards model.

The patients were then divided on the basis of number of bone lesions present using the groupings previously proposed,²¹ and potential relationships were explored using a scatterplot analysis. The median survival for each group was also estimated. For these analyses, the two patients with normal scans were combined with the group having less than six lesions.

	RESULTS

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION REFERENCES

 
The baseline patient characteristics are listed in Table 1 and presented as median, quartile, and overall ranges. The median age of the patient population was 71 years, with a median of 24 bone lesions per patient. The median LDH and HgB levels were normal, and PSA values ranged from 1.9 to 14,228 ng/mL (median, 82 ng/mL). The median follow-up time was 30.4 months (range, 26 to 39 months). Pretreatment variables evaluated by single-variable analysis are listed in Table 2. Using the log-rank test, age (P = .0446), ECOG performance status (P = .0005), baseline PSA (P = .0001), HgB (P = .0001), alkaline phosphatase (P = .0002), AST (P = .0021), LDH (P = .0001), and treatment arm (P = .0098) were significantly associated with survival. No improvement or difference was detected when using logarithmic transformations of a variable. For subsequent analyses, all variables were left in their natural form. Based on the risk ratio observed, each unit increase in age increased the risk of death by 5%, and each unit of LDH increased the risk of death by 0.2%, whereas each 1-g increase in HgB decreased the risk of death by 22%.

The BSI ranged from 0% to 54%, and the number of lesions ranged from 0 to 395. Figure 1, A and B, shows representative ^99mTc-methylene diphosphonate–labeled scans with BSI values of 0.7% and 12.4%, respectively, and Fig 1C shows a superscan with a BSI of 48%. Figure 2A shows the relationship between BSI and survival when BSI is considered as a continuous variable, and Fig 2B shows the survival distributions for extent of disease defined by the ranges in BSI representing a division of the patient population into three equal groups (log-rank P = .0001), using the method of Kaplan and Meier.²⁶ A strong association between a measured increase in BSI and decreased survival is apparent. Figure 3A shows the association between BSI and number of lesions using a scatterplot analysis for the entire range of BSI and number of lesions³¹ and for the range of 0 to 50 lesions and BSI of 0% to 10% (Fig 3B). The associations are strong for both a small and large number of lesions. Figure 4 shows the survival distributions based on the number of bone lesions in the groupings originally described²¹ (log-rank P = .0001). The results indicate that the Kaplan-Meier estimates of survival for patients with less than six lesions and with six to 20 lesions touch, suggesting poor discrimination between these two groups of patients.

View larger version (199K): [in this window] [in a new window]   Fig 1. Representative examples of different bone scan indices: (A) minimal bone disease with a BSI of 0.7%; (B) intermediate disease with a BSI of 12.4%, and (C) a superscan with a BSI of 48%.

View larger version (28K): [in this window] [in a new window]   Fig 2. Associations between BSI and survival, analyzed (A) as a continuous variable and (B) based on a division of the patients into three equal groups using the Kaplan-Meier method.

View larger version (18K): [in this window] [in a new window]   Fig 3. Scatterplots of BSI (vertical axis) and number of lesions (horizontal axis), (A) for the entire range of measurements and (B) for a BSI of 0% to 10% (vertical axis) and 0 to 50 lesions (horizontal axis)31 (A, inset).

View larger version (14K): [in this window] [in a new window]   Fig 4. Kaplan-Meier survival distributions of patients using the groupings for number of lesions as previously proposed.21

When the parameters of significance in Table 2 were considered in a multiple-variable proportional hazards analysis, age, baseline HgB and LDH, treatment arm, and BSI remained significant (Table 3). The RRs were 1.86 (95% confidence interval, 1.18 to 2.94) for patients whose BSI was between 1.4% and 5.1%, and 2.12 (95% confidence interval, 1.11 to 4.00) for those with a BSI of more than 5.1% (P for trend = .007). Baseline PSA was no longer associated with survival if BSI was included in the analysis. When PSA was excluded from the analysis, the RRs increased to 1.88 (95% confidence interval, 1.20 to 2.95; P = .006) for those with a BSI between 1.4% and 5.1%, and 2.13 (95% confidence interval, 1.12 to 4.03; P = .02) for those with a BSI of more than 5.1%, in comparison with individuals with a BSI of less than 1.4% (data not shown). Increasing age (RR, 1.05; P = .0002) and LDH (RR, 1.002; P = .004) were associated with a negative effect, whereas increasing HgB (RR, 0.78; P = .0001) and treatment arm (RR, 0.56; P = .003) were associated with a positive effect on survival in the multiple-variable analysis. The BSI remained significant when these factors were included in the model, whereas ECOG performance status, baseline PSA, AST, and number of bone lesions (RR, 1.00; P = .85) were no longer associated (Table 3).

Table 4 presents the multiple-variable proportional hazards analysis of survival based on the number of metastatic lesions when controlling for the variables listed in Table 3. Although an association between number of lesions considered as a continuous variable and survival was observed (P for trend = .03), no association was observed for the individual groupings previously reported.²¹ These associations were not influenced by the inclusion of BSI in the analysis.

	DISCUSSION

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION REFERENCES

 
This study demonstrates the prognostic significance of extent of disease in bone when accounting for other known prognostic factors, using a new method to quantify bone involvement by tumor. Grouped according to a range of BSI values corresponding to the division of the population into three equal groups, patients with low (< 1.4%), intermediate (1.4% to 5.1%), and extensive (> 5.1%) skeletal involvement and median survivals of 18.3, 15.8, and 8.1 months, respectively, were identified (Fig 2B).

Using scatterplot and correlation analysis, the measured BSI was closely associated with the counted number of lesions on the scan (correlation = .92, Spearman nonparametric correlation). In a previous report of patients with M1 disease who had not received hormone therapy, five groups were defined according to the number of lesions present at the start of treatment: 0, normal; 1, less than six lesions, each involving less than 50% of a vertebral body; 2, six to 20 lesions; 3, more than 20 lesions but not a superscan; and 4, a superscan. The survival distributions for groups 1 and 4 differed significantly, whereas there was no difference in outcomes for groups 2 and 3 (P = .37).²¹ In an analysis of our population of patients with androgen-independent disease using the same criteria, the predictive trend remained significant (P = .025), but the significance was lost when group 2 or group 3 was compared with group 0 or group 1. The lack of association may reflect the range of tumor burdens or, more likely, the inability to count coalesced lesions accurately (Fig 4).

Other methods of quantifying bone disease have shown an association with outcome but highlight the need for a standard methodology. Some investigators have divided the skeleton on the basis of the whether the lesions occurred singly or multiply and diffusely,³² or according to the pattern of spread, such as pelvic versus distal sites,³³ or axial versus appendicular regions.^34,35 It would be difficult, however, to envision how a solitary lesion in a rib would confer a different outcome relative to a lesion in the thoracic spine, a factor that the latter method does not account for. Other methods include measures obtained by recording a gamma count rate in specific regions^18,36,37 or the total skeleton.¹⁹ These methods measure global radiotracer uptake but offer no qualitative information, and as such, they have not been adopted into routine clinical practice. More recent schemes have involved semiquantitative methods.³⁷ A digitized model of the skeleton on which the amount of bone involvement was visually estimated showed no correlation between the pretreatment area of bone involvement and ultimate survival in a cohort of breast cancer patients.²⁵ These methods have also shown wide variation among individual investigators in the estimates of percentage of involvement.³⁸ In the calculation of the BSI, the variability is reduced by dividing the skeleton into 158 separate areas, which permits a more precise estimate of each area. As a result, each individual measurement participates less in the total percentage calculations.

In the current study, cut points based on a division of the calculated BSI into three equal groups identified patients with different median survivals. A review of the pattern of metastases in these groups of patients showed a parallel with the distribution of the normal marrow based on radiolabeled marrow scans³⁹ and scans of ⁵⁹Fe in the erythron⁴⁰ (Fig 5). This is consistent with seeding and attachment in the red marrow, followed by expansion to adjacent bone.¹⁷ We estimate the bone marrow organ volume in the normal adult male to be 36.7% of the total skeleton, on the basis of the known weights of these bones.^39,40 When the red marrow is destroyed by tumor or responds to chronic stress such as hemolysis, it expands peripherally to replace yellow marrow in the extremities in a centrifugal pattern. Extramedullary hematopoiesis may also occur. This explains why a BSI above 36.7%, the percentage of the skeleton that involves bone marrow, is possible, and why the average superscan falls into the 35% to 50% range. In this study, the median survival of patients in each of the risk groups differed. However, this finding cannot be interpreted to mean that the groupings described represent the optimal ranges to define prognosis, particularly because the range of BSI in the patients defined as high risk is broad. As such, the prognostic validity of these or other groupings, if any, and their relative performance in comparison to other classification schemes, will require prospective and independent validation.

View larger version (91K): [in this window] [in a new window]   Fig 5. Schematic illustration of the distribution of normal bone marrow in the adult, illustrating the characteristic involvement of the central skeleton with variable involvement of the upper portions of the femurs, humeri, and base of skull. Reprinted with permission.39

This study addresses the prognostic significance of a single BSI determination at baseline. A key issue will be whether serial changes in the BSI can be used to monitor treatment effects.²³ This is important because of the controversies surrounding the use of posttherapy change in PSA as an outcome measure for clinical trials in patients with androgen-independent disease and the difficulties in interpreting changes in radionuclide bone scans in a reproducible way.¹⁶ Currently, a PSA-based outcome parameter is used by some groups, but not by others. Under these circumstances, defining covariables that are associated with survival is important. Furthermore, such corroborating measures may be particularly useful when evaluating agents that produce declines in PSA that are unrelated to their effect on cellular proliferation, or for the evaluation of differentiating agents, for which a rising PSA is not necessarily indicative of treatment failure.¹⁶

Patients with androgen-independent prostate cancer represent a wide range of prognoses. A standardized method that quantifies the extent of osseous disease is useful to stratify patients in clinical trials and provides prognostic information. The Memorial BSI provides a reproducible, direct way to quantify the amount of osseous disease present in these patients.²⁴ It serves as a pretreatment predictive factor of survival and functions as a covariate with PSA, a relationship which needs to be explored further. With continued development, the index may be most useful in allowing the inclusion of patients with disease limited to bone in clinical trials and providing a systematic way to determine outcomes in this population. Now that correlation of the baseline BSI with survival has been completed, work is under way to complete automation of the index,²⁵ assess its role in monitoring response to treatment,²³ and determine its contribution to the assessment of prognosis in relation to posttherapy changes in PSA.

	ACKNOWLEDGMENTS

 
Supported by grant no. CA-05826 from the Janssen Research Foundation and grant no. CA-09207 (T32) from the PepsiCo Foundation.

We thank Melissa Fazzari for a critical review of the manuscript.

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Submitted April 23, 1997; accepted November 11, 1998.

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