Original Article
Indicators of Prognosis in Node-Negative Breast Cancer
N Engl J Med 1990; 322:1045-1053April 12, 1990
- Abstract
- Abstract
Measures of the proliferative activity of tumor cells have prognostic value in patients with node-negative breast cancer. We studied 367 women in southern Sweden who had undergone surgical resection for such cancer. Tumor specimens were analyzed with DNA flow cytometry in order to estimate both the DNA content (ploidy) and the fraction of cells in the synthetic phase of the cell cycle (S phase). The median duration of follow-up was four years; 28 percent of the patients received adjuvant therapy, usually with tamoxifen (n = 83).
A multivariate analysis based on complete data on 250 patients included the following covariates: age (≥75, 50 to 74, and ≤49 years), tumor size (≤20 vs. >20 mm), concentration of estrogen and progesterone receptors (<10 vs. ≥10 fmol per milligram of protein), ploidy (diploid vs. nondiploid), and S-phase category (fraction of cells in S phase: <7.0 percent, 7.0 to 11.9 percent, and ≥12 percent). The S-phase fraction yielded the most prognostic information, followed by progesterone-receptor status and tumor size. A prognostic model based on these three variables identified 37 percent of the patients as constituting a high-risk group with a fourfold increased risk of distant recurrence. In the remaining 63 percent of the patients, the five-year overall survival rate (92±4 [±SE] percent) did not differ from the expected age-adjusted rate for Swedish women.
We conclude that a prognostic index that Includes indicators of the proliferative activity of tumor cells may be able to identify women with node-negative breast cancer in whom the risk of recurrence is sufficiently low that adjuvant chemotherapy can be avoided. (N Engl J Med 1990; 322:1045–53.)
Media in This Article
Figure 1
Overall Survival, Survival with Breast Cancer, Disease-free Survival, and Distant-Disease—free Survival among Patients with Node-Negative Breast Cancer, According to S-Phase—Fraction Category.Figure 2
Survival According to Defined Risk Group.Article Activity
- Article
LONG-TERM follow-up studies of survival show that in most cases, primary breast cancer is a systemic disease that may recur decades after it has been initially diagnosed.1 However, findings from studies of the survival of patients with this disorder suggest that the disease takes two forms: one that is rapidly fatal, and another in which the outcome differs little from that of women of similar age without disease.2
Most women with node-negative breast cancer who receive only local treatment will survive without further symptoms and eventually die of other causes.1 , 3 The proportion of such women is probably increasing as screening programs allow breast cancer to be diagnosed at an earlier stage. In the future, more than half of women with newly diagnosed breast cancer will have node-negative disease.4
Both the proliferative activity of tumor cells as assessed with the thymidine-labeling technique and the DNA content of individual tumor cells as determined by static (image) cytometry have been shown to yield prognostic information in node-negative disease.5 6 7 8 9 Flow-cytometric measurements of DNA provide information about both DNA ploidy and proliferative activity as represented by the fraction of cells in the DNA synthetic phase, or S phase, of the cell cycle. In a recent report Clark et al.10 evaluated the prognostic value of the combination of data on ploidy and data on the S-phase fraction in cases of node-negative disease; after these investigators had adjusted for other prognostic factors, they found that ploidy was an independent prognostic factor and the S-phase fraction yielded additional prognostic information only if the tumor was diploid.
On the basis of results from randomized clinical trials, it has been recommended that some sort of systemic adjuvant therapy should be given to all women with node-negative breast cancer11 , 12; however, if all such women are grouped together, many will be overtreated.13 The aim of this study of women with node-negative breast cancer was to determine whether it was possible to distinguish those with a good prognosis from those with a poor one, on the basis of several risk factors.
Methods
Patients
In the health care region of southern Sweden, which has a population of approximately 1.5 million, there are 13 community hospitals with surgery departments and 2 university hospitals with both surgery and oncology departments. Hormone-receptor analyses are routinely performed on tumor specimens from patients with primary breast cancer, and any residual specimens are stored in a tumor bank at the Department of Oncology at University Hospital, Lund. The series we considered for study consisted of 410 consecutive patients in whom node-negative breast cancer had been diagnosed between September 1982 and January 1986 and for whom tumor specimens were available at the tumor bank. This group represented approximately 40 percent of all women with new cases of node-negative disease diagnosed in the region during the period.
Of the 410 patients, 43 were excluded from analysis for one or more of the following reasons: no tumor cells were identified with certainty by a cytopathologist who had examined imprints of all tumor specimens without being aware of the clinical status of the patient or the results of flow cytometry (n = 18); the occurrence of distant metastases was confirmed within two months after surgery (n = 3); the tumor specimen was of recurrent node-negative cancer (n = 13), carcinoma in situ (n = 2), breast cancer in a man (n = 1), cystosarcoma phylloides, or squamous-cell cancer (n = 4); metastasis to the breast from another primary tumor had occurred (n = 1); or bilateral cancer and subsequent systemic disease had occurred (n = 4). The characteristics of the remaining 367 patients are listed in Table 1Table 1
Characteristics and Treatment of 367 Patients with Node-Negative Breast Cancer..The details of nodal status and tumor size were recorded from the original pathology reports. In most cases the maximal diameter of the primary tumor had been measured on an unfixed specimen. The routine base-line evaluation of the patient included laboratory analyses, chest radiography, mammography, and often bone scanning. Each patient was examined clinically at least once a year; follow-up evaluations included radiography and mammography. As a rule, bone scanning or other assessments were performed only when clinically indicated.
Clinical data were updated in the summer and autumn of 1988, and all clinical records from the oncology and surgery departments were screened for details of treatment and clinical events, including the date of the last follow-up evaluation, the site and date of any recurrence, and the date of death. Death certificates were examined; however, recurrent disease was considered to be the cause of death only if its presence had been clinically confirmed before death. The presence of other neoplasms was recorded from the cancer registry, and the date of death from the population registry.
Treatment
Local treatment was given in accordance with guidelines for treatment drawn up by the South Swedish Breast Cancer Group and consisted either of modified radical mastectomy with axillary dissection or, in some patients with tumors less than 20 mm in diameter (n = 44), of conservative breast surgery with axillary dissection and postoperative irradiation of the breast (with the tangential technique [two opposing fields] and a dose of 54 Gy usually given as split-course treatment over a period of seven weeks). Some patients (n = 85), most of whom had primary tumors more than 20 mm in diameter, underwent irradiation after modified radical mastectomy (with the four-field technique [45 to 48 Gy to the axillary, supraclavicular, infraclavicular, and parasternal nodes and the thoracic wall], given as a split-course treatment over a period of seven weeks). Adjuvant therapy was given to 102 patients (28 percent) for one year, as endocrine treatment (n = 83) (usually tamoxifen, 30 mg per day by mouth), single-drug chemotherapy (n = 9) (cyclophosphamide, 130 mg per square meter of body-surface area, by mouth, during the first 14 days of a 28-day treatment cycle), or both (n = 10).
Laboratory Assays
Estrogen-receptor and progesterone-receptor content was assayed with isoelectric focusing and with the dextran-coated charcoal method and Scatchard analysis.14 The values obtained were excluded from analysis (n = 21) if the tumor specimens had not been kept at the proper temperature before arrival at the laboratory or had been too diluted (<0.5 mg of protein per milliliter).15 Progesterone-receptor status was not analyzed in 21 specimens assayed for estrogen-receptor status.
The DNA content of individual cell nuclei was analyzed by flow cytometry with use of an Ortho 50H instrument after staining with propidium iodide.16 , 17 Tumors were defined as either DNA diploid (with one stem-cell population — G0 G1) or DNA nondiploid (with two or more stem-cell populations).18 Ploidy was established in all 305 specimens analyzed, although in 19 (6 percent) it was not possible to estimate the fraction of cells in the S phase, usually because of extensive background debris. The percentage of nuclei in the S-phase fraction was calculated planimetrically.19
Statistical Analysis
The value of the prognostic factors (covariates) was determined according to statistical models and methods for analyzing data on time to treatment failure, with the use of the BMDP statistical package (BMDP Statistical Software, Los Angeles). Survival was expressed as the number of months from the date of primary surgery to the occurrence of an event20 and was analyzed in four ways: as overall survival, based on deaths due to any cause; as survival with breast cancer, based on deaths due to or with advanced breast cancer; as disease-free survival, based on the presence of clinically confirmed distant, local, or regional recurrence; and as distant-disease—free survival, based on the presence of clinically confirmed distant recurrence.
Statistical analysis included continuous as well as discrete covariates, all of which were considered as fixed (not time-dependent). For optimal categorization of continuous covariates, univariate comparison was performed with chi-square values,21 with various cutoff levels for both hormone-receptor and S-phase values. The prognostic value of the different covariates was evaluated with the use of the product—limit estimate of survival function.22 Differences between the survival functions were assessed with the log-rank test23 and confirmed with the generalized Wilcoxon test.
Multivariate survival analyses were performed with the Cox proportional-hazards model.24 Covariates were selected in a stepwise fashion (backward to forward), with use of the maximum-likelihood ratio. A P value of 0.15 was adopted as the limit for the inclusion of a covariate. The assumptions of the proportional-hazards model were checked by plotting the log of the cumulative-hazard function.
A prognostic index was constructed from the results of the multivariate analyses in relation to distant-disease—free survival. Finally, the observed overall survival in various prognostic groups was compared with the expected survival in the general Swedish population of comparable age.25 Correlations are expressed as Spearman rank-correlation coefficients (rs).
Results
The median duration of follow-up was 48 months (range, 24 to 70); as of their last recorded follow-up evaluation, 276 patients (75 percent) were alive and had had no recurrence. Table 1 summarizes the characteristics and treatment of the patients and the observed events.
Correlation of Covariates
Age correlated with both estrogen-receptor content (rs = 0.39, P<0.0005) and progesterone-receptor content (rs = 0.10, P = 0.03). It was inversely related to the S-phase fraction (rs = −0.20, P<0.0005) and nondiploidy (rs = −0.10, P = 0.04), though its relation to nondiploidy was weak.
Tumor size correlated weakly with the S-phase fraction (rs = 0.16, P = 0.03) and was inversely related to estrogen-receptor content (rs = −0.21, P<0.0005) and progesterone-receptor content (rs = −0.18, P<0.0005). Estrogen-receptor and progesterone-receptor values were strongly correlated (rs = 0.60, P<0.0005). S-phase-fraction values were inversely related to estrogen-receptor content (rs = −0.30, P<0.0005) and progesterone-receptor content (rs = −0.26, P<0.0005). S-phase values and nondiploidy were strongly correlated (rs = 0.60, P<0.0005).
There were no significant correlations between age and tumor size, tumor size and ploidy, or ploidy and estrogen-receptor content.
Univariate and Multivariate Analyses of Survival
The use of commonly applied cutoff levels for tumor size,26 estrogen-receptor content,27 and progesterone-receptor content28 produced lower P values than the use of continuous variables. The optimal cutoff levels for S-phase-fraction values were found to be 7 percent and 12 percent. This was first shown in 566 patients with primary breast cancer and later confirmed in different subgroups (premenopausal and postmenopausal women, women with node-negative and node-positive tumors, and those with diploid and nondiploid tumors) and with different durations of follow-up (one, two, three, and four years). Thus, S-phase—fraction values were divided into three categories (<7.0 percent, 7.0 to 11.9 percent, and ≥12 percent), which were used to classify the patients according to their level of risk.
With respect to diploid and nondiploid tumors, the risk of death or recurrence was up to 50 percent higher for patients in the high S-phase category than for those in the intermediate category, and approximately 50 percent higher for the patients in the intermediate category than for those in the low category. The determination of ploidy provided no additional prognostic information with reference to any of the three S-phase categories. Among patients with low S-phase—fraction values, survival in those with diploid tumors did not differ from survival in those with nondiploid tumors; at four years, the mean (±SE) overall survival was 85±6 percent in patients with diploid tumors and 91±3 percent in those with nondiploid tumors, and survival with breast cancer was 94±3 percent and 98±2 percent in these groups, respectively. The risk of death due to breast cancer was higher in the patients with diploid high—S-phase tumors than in those with nondiploid low—S-phase tumors (P = 0.07).
The assumptions of the proportional-hazards model were fulfilled for the covariate categories of tumor size and estrogen-receptor and progesterone-receptor status and for the three S-phase categories. It was more difficult to fit age into the model, but it has been shown29 that in Scandinavia generally, patients with breast cancer can be divided into four risk groups according to age (<35, 35 to 49, 50 to 74, and ≥75). In the present study, only 11 patients were less than 35 years of age; they were combined with the next older age group (35 to 49), thus forming three age groups that met the assumptions of the proportional-hazards model.
The results of univariate analysis of variables included in the multivariate analysis are shown in Table 2Table 2
Univariate Analysis of Prognostic Covariates of Survival in 367 Patients with Node-Negative Breast Cancer.*. The S-phase categories had the greatest prognostic value, according to univariate analysis (Table 2 , Fig. 1Figure 1Overall Survival, Survival with Breast Cancer, Disease-free Survival, and Distant-Disease—free Survival among Patients with Node-Negative Breast Cancer, According to S-Phase—Fraction Category.). In multivariate analyses the S-phase categories were invariably an independent prognostic factor, whose prognostic value was followed closely by that of progesterone-receptor status (Table 3Table 3
Multivariate Analysis (Cox Proportional-Hazards Regression) of Prognostic Covariates of Survival in 250 Patients Followed up for a Median of Four Years.*). In the multivariate analysis of overall survival, estrogen-receptor status replaced progesterone-receptor status as an independent prognostic factor (Table 3). Tumor size was an independent prognostic factor in relation to disease-free and distant-disease—free survival, but not in relation to overall survival and survival with breast cancer.When S-phase categories were excluded from the multivariate analysis, ploidy approached the borderline of significance as an independent prognostic factor (P<0.1), as did estrogen-receptor status when progesterone-receptor status was excluded from analysis (P<0.1). The fraction of cells in S phase was of more prognostic value than an index of proliferation that was calculated by adding the fraction of cells in S phase to the fraction in gap 2 phase (G2 phase).
The prognostic strength (expressed as a β coefficient) of each of the three covariates that gave independent prognostic information in the multivariate analysis in relation to distant-disease—free survival (Table 3) was used in a simplified model for prognosis, giving the following index values: for S-phase—fraction values, <7.0 percent = 0, 7.0 to 11.9 percent = 0.5, and ≥12 percent = 1; for progesterone-receptor content, ≥10 fmol per milligram of protein = 0 and <10 fmol = 1; and for tumor size, ≤20 mm = 0 and >20 mm = 1. The model yielded good prognostic information (Table 4Table 4
Cumulative Survival According to the Pattern of Risk Factors Derived from the Prognostic-Index Model, in 250 Patients Followed up for a Median of Four Years. and Fig. 2Figure 2Survival According to Defined Risk Group.), and when this model was included in the multivariate analysis, the other covariates added no further prognostic information.The patients were compared with age-matched subjects selected from the national population registry.25 Among patients with fewer than two risk factors (63 percent), only 3 percent (n = 5) of whom had clinically confirmed distant metastases (Fig. 3Figure 3
Overall Survival According to Number of Risk Factors.), survival was comparable to the expected survival in the general Swedish population of comparable age. The patients with two or more risk factors (37 percent) had a threefold higher risk of death due to any cause and a six-fold higher risk of death due to or with advanced breast cancer (Table 4 and Fig. 3).Patients for whom any prognostic variable was missing (n = 117) were excluded from the multivariate analysis; when they were compared with the rest of the patients, no significant differences were found in survival (four-year disease-free survival, 85 percent vs. 82 percent) or in the distribution of the prognostic variables (age, primary-tumor size, steroid-receptor status, ploidy, and S-phase—fraction values).
To exclude treatment bias, all patients who received adjuvant therapy (n = 102) were compared with those who did not; no significant differences were found in survival (four-year disease-free survival, 82 percent vs. 83 percent) or in the distribution of the prognostic variables (age, primary-tumor size, steroid-receptor status, ploidy, and S-phase—fraction values). Adjuvant therapy was not found to be an independent prognostic factor when it was included in a separate multivariate analysis. Finally, a multivariate analysis was performed only with patients who received no adjuvant therapy (n = 178); the S-phase category remained an independent prognostic factor, as did tumor size in relation to disease-free and distant-disease—free survival, but not in relation to overall survival and survival with breast cancer. Progesterone-receptor status seemed to be a prognostic factor according to univariate analysis, but it was not statistically significant according to multivariate analysis.
When patients who received postoperative radiation therapy (n = 127) were compared with all others, this group had a nonsignificant trend toward younger age (median, 57 vs. 65 years), a greater frequency of nondiploid tumors (66 percent vs. 54 percent), and a higher median S-phase fraction (8.1 percent vs. 5.7 percent). However, no difference was found between the two groups in overall survival (83 percent vs. 83 percent; P = 0.72) or disease-free survival (78 percent vs. 86 percent; P = 0.11).
A subsequent refined analysis excluded 26 patients for one of the following reasons: suspected but not clinically confirmed systemic disease (n = 2), bilateral breast cancer (n = 19), or another concomitant neoplasm (n = 5). Thus analyzed, the S-phase category became a significantly more valuable prognostic factor, whereas progesterone-receptor status was less valuable.
Discussion
Our findings confirm previously reported results showing that the proliferative activity of tumor cells in primary breast cancer is an independent prognostic factor,6 7 8 9 10 , 30 , 31 even in cases of node-negative disease.6 7 8 9 10 In our series of patients with node-negative breast cancer, the S-phase category together with the progesterone-receptor status and tumor size, which followed the S-phase category in prognostic value, were the only independent prognostic factors. The use of these three factors in combination identified a group of patients at high risk (37 percent of the cohort, with a prognostic index of 2.0 to 3.0), who had an eightfold higher risk of distant recurrence during four years of follow-up than the patients with the best prognosis (24 percent of the cohort, with a prognostic index of 0.0). This group of high-risk patients had a fourfold higher risk than all the other patients in the series as a whole (63 percent), among whom overall survival did not differ from life expectancy in the general Swedish population of comparable age (Fig. 3).
Ewers and coworkers32 from our institution have previously reported that ploidy is a prognostic indicator according to univariate analysis in patients with node-negative breast cancer; however, these authors did not analyze S-phase—fraction values. In our study, ploidy had prognostic value on the basis of univariate analysis but had a value on the borderline of significance as an independent prognostic factor in multivariate analysis when the S-phase category was not included. However, the three S-phase categories yielded more prognostic information than did the determination of ploidy, which was not an independent prognostic factor when both factors were included in multivariate analysis.
The independent prognostic value of estrogen-receptor and progesterone-receptor status is a matter of dispute.27 , 33 In patients with node-negative breast cancer, both Clark34 and Fisher27 and their colleagues have shown that estrogen-receptor status is a stronger prognostic variable than progesterone-receptor status. In our study, however, progesterone-receptor status seemed to be a stronger prognostic variable, as in the study by the Danish Breast Cancer Cooperative Group28 and the more recent study by Clark et al.10 Also in accord with the findings of the Danish group,28 the prognostic value of estrogen-receptor status became weaker with time in the present investigation, whereas the value of progesterone-receptor status remained stable. Most patients in the present study who died of intercurrent disease were elderly. Since the correlation between age and estrogen-receptor status was stronger than that between age and progesterone-receptor status, it probably accounts for the higher value of estrogen-receptor status as a prognostic indicator in relation to overall survival (Table 3). Although the administration or absence of adjuvant therapy did not seem to affect the overall results, steroid-receptor status was found to have no independent prognostic value when patients who received adjuvant therapy were excluded from analysis. This might suggest that the prognostic value of the steroid receptors is to some extent related to treatment. When progesterone-receptor status was excluded from our prognostic model, estrogen-receptor status became a weak independent prognostic factor; in combination with the S-phase category and tumor size, estrogen-receptor status can probably be used if the value for progesterone-receptor status is not available.
Lymph-node status is generally accepted as the most valuable predictor of recurrence in breast cancer.35 Tumor size is also a predictor of recurrence,26 but these two factors are closely related, and the relative strength of tumor size as an independent predictor of relapse is unclear; tumor size may chiefly reflect the age of the tumor and to a lesser degree its aggressiveness.36 In the present study, there was a weak inverse relation between tumor size and estrogen-receptor and progesterone-receptor content, and a weak positive correlation between tumor size and S-phase—fraction values, suggesting that tumor size may reflect biologic behavior. In fact, tumor size was an independent prognostic factor in relation to disease-free and distant-disease—free survival but not to overall survival or to survival with breast cancer (Table 4), which implies that tumor size is a time-dependent prognostic factor. Indeed, as Fisher et al. have shown in a multivariate analysis, after 10 years of follow-up tumor size becomes an independent prognostic indicator of survival.37
The report that S-phase—fraction values are significantly higher in nondiploid tumors than in diploid tumors38 was confirmed in the present study, in which the median S-phase—fraction value was 4.3 percent for diploid tumors and 11.0 percent for nondiploid tumors. Grouping patients according to ploidy and according to the median S-phase—fraction value in the whole series, or according to the S-phase—fraction value for each ploidy group as proposed by Kallioniemi et al. (7 percent in diploid tumors and 12 percent in nondiploid),31 however, did not distinguish risk groups as well as did the use of the three S-phase categories. Clark et al.10 reported that in patients with node-negative breast cancer, the fraction of cells in S phase yielded additional prognostic information only in patients with diploid tumors, and they concluded that the prognosis was particularly good in patients with diploid tumors and low S-phase—fraction values (28 percent of the cohort). Our findings confirm their conclusion. When we used a single cutoff value (7 percent), we found that the S-phase fraction was of no added prognostic value in patients with nondiploid tumors; nevertheless, our use of the three S-phase categories had additional prognostic value in relation to both nondiploid and diploid tumors. By contrast, determination of ploidy did not distinguish the patients within each S-phase category.
A weakness of the present study was that, since uniform histopathological classification of the primary tumors was not performed, the independent prognostic value of the various biologic variables could not be compared with the value of the histologie grade and nuclear grade of the tumors, both of which have been shown to be related to prognosis. Indeed, nuclear grade is increasingly replacing histopathological grade as a prognostic marker,36 having been found to be at least as effective.27 Among the specific characteristics of nuclear grade, the frequency of mitosis has been claimed to be more accurate than nuclear pleomorphism in predicting relapse.39 Mitotic frequency reflects proliferative activity, as does estimation of the S-phase fraction,40 though the latter is more sensitive than the mitotic index as a marker of proliferation since the S phase of the cell cycle lasts longer than mitosis.40 Abnormal DNA content is associated with tumor aggressiveness41 and might predispose the tumor to nuclear pleomorphism. The drawback of nuclear grading is its subjective nature and lack of reproducibility42; conversely, the advantage of cytometric measurement is its objectivity and reproducibility.
The investigation of prognostic factors based on biologic variables is flawed by the potential bias toward the inclusion of patients with larger tumors. The present study, although it included only approximately 40 percent of all patients with primary node-negative breast cancer, had far less selection bias than controlled clinical trials.12 With regard to median age, age distribution, and the distribution of steroid-receptor values, the patients in the present series were comparable to a less selected group of more than 4000 patients from the same region15—i.e., approximately two thirds of all patients with newly diagnosed breast cancer. It is possible, however, that the conclusions drawn here do not fully apply to patients with very small tumors.
With regard to S-phase analysis, since both the means of storing tumor specimens and laboratory methods may vary from one center to another, each must define its own optimal cutoff levels. Because the presence of background debris may make it difficult to estimate the S-phase fraction,38 a computer program based on a statistical model for calculating the fraction has been developed at our institution43; the efficacy of the program is being compared with that of the planimetric estimation currently used to measure the fraction.19
On the basis of results of randomized clinical trials, it has been recommended that all women with node-negative breast cancer be given some type of systemic adjuvant therapy.11 , 12 However, it is likely that in the near future more than half of all patients with breast cancer will be found to have node-negative disease, in part because of the early detection of breast cancer through screening programs. It has been suggested that, if adjuvant therapy were given as a matter of policy to all patients with node-negative disease, the clinical use of new prognostic factors might be delayed for years to come.44
With regard to overall survival, our prognostic model enabled us to identify both a high-risk group and a low-risk group. Since the ultimate aim of adjuvant therapy is to increase survival, the feasibility of that aim is unclear with regard to patients at low risk. Although cure is difficult to ascertain, five-year survival in the low-risk group does not differ from life expectancy in the general Swedish population of comparable age25 (Fig. 3). Naturally, the outcomes in patients at low risk cannot be regarded as "cures," in view of the four-year survival rate of 97 percent among patients who survived with breast cancer. These results may also be interpreted as suggesting that node-negative breast cancer in fact has two distinct forms2 , 3 — one rapidly leading to death, and another with an outcome only negligibly different from that in women of similar age without disease. Thus, we would recommend that, instead of treating all women with node-negative breast cancer, the physician should follow an approach based on known and new prognostic variables that have defined specific risk groups within randomized clinical trials. Also, both the three S-phase categories and the prognostic model used in the present investigation should be validated independently.
Supported by grants from the Swedish Medical Research Council and the Swedish Society of Medicine, the Swedish Cancer Society, the John and Augusta Persson Foundation for Medical Scientific Research, the Inga Britt and Ame Lundberg Foundation, the Berta Kamprad Foundation, the Lund University Hospital Research Foundation, the Medical Faculty of the University of Lund, and the Swedish Institute of Applied Mathematics.
We are indebted to Ingrid Idvall for cytopathological examination of all imprints, to Ghita Hallencreutz, Ulla Johansson, and Gunilla Sellberg for skillful technical assistance, to Cecilia Dalberg and Eva Henriksson for help in preparing the manuscript and illustrations, to Claes Jogréus for reviewing the statistics, and to Harald Andersson for statistical help in selecting controls from the Swedish population registry.
Source Information
From the South Swedish Breast Cancer Group and the Department of Oncology, University Hospital, Lund, S-221 85 Sweden, where reprint requests should be addressed to Dr. Sigurdsson.
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