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PubMed2006

Cost-effectiveness of using prognostic information to select women with breast cancer for adjuvant systemic therapy.

OBJECTIVES: To investigate the cost-effectiveness of using prognostic information to identify patients with breast cancer who should receive adjuvant therapy. DATA SOURCES: Electronic databases from 1980 through to February 2002. A survey of clinical practice in UK cancer centres and units. Large retrospective dataset containing data on prognostic factors, treatments and outcomes for women with early breast cancer treated in Oxford. REVIEW METHODS: Between six and nine databases were searched by an information expert. Evidence-based methods were used to review and select those studies and the quality of each included paper was assessed using standard assessment tools reported in the literature or piloted and developed for this study. A survey of clinical practice in UK cancer centres and units was carried out to ensure that conclusions drawn from the report could be implemented. These data, along with the information gathered in the systematic reviews, informed the methodological approach adopted for the health economic modelling. An illustrative framework was developed for incorporating patient-level prediction within a health economic decision model. This framework was applied to a large retrospective dataset containing data on prognostic factors, treatments and outcomes for women with early breast cancer treated in Oxford. The data were used to estimate directly a parametric regression-based risk equation, from which a prognostic index was developed, and prognosis-specific estimates of the baseline breast cancer hazard could be observed. Published estimates of treatment effects, health service treatment costs and utilities were used to construct a decision analytic framework around this risk equation, thus enabling simulation of the effectiveness and cost-effectiveness of adjuvant therapy for all possible combinations of prognostic factors included in the model. RESULTS: The lack of good-quality systematic reviews and well-conducted studies of prognostic factors in breast cancer is a striking finding. There are no registers of studies of prognostic factors or of reviews of prognostic studies. Many of the reviews used weak methods, primary studies are similar with poor methodology and reporting of results. In addition, there is much variation in patient populations, assay methods, analysis of results, definitions used and reporting of results. Most studies appear to be retrospective and some use inappropriate methods likely to inflate outcomes such as optimising cut points and failing to test the results in an independent population. Very few reviews used meta-analysis to conduct a pooled analysis and to provide an estimate of the average size of any association. Instead, most reviews relied on vote counting. Although many prognostic models for breast cancer have been published, remarkably few have been re-examined by independent groups in independent settings. The few validation studies have been carried out on ill-defined samples, sometimes of smaller size and short follow-up, and sometimes using different patient outcomes when validating a model. The evidence from the validation studies shows support for the prognostic value of the Nottingham Prognostic Index (NPI). No new prognostic factors have been shown to add substantially to those identified in the 1980s. Improvement of this index depends on finding factors that are as important as, but independent of, lymph node, stage and pathological grade. The NPI remains a useful clinical tool, although additional factors may enhance its use. We accepted that hormone receptor status (ER) for hormonal therapy such as tamoxifen and prediction of response to trastuzumab by HER2 did not require systematic review, as the mechanism of action of these drugs requires intact receptors. There was no clear evidence that other factors were useful predictors of response and survival. The survey confirmed pathological nodal status, tumour grade, tumour size and ER status as the most clinically important factors for consideration when selecting women with early breast cancer for adjuvant systemic therapy in the UK. The protocols revealed that although UK cancer centres appear to be using the same prognostic and predictive factors when selecting women to receive adjuvant therapy, much variation in clinical practice exists. Some centres use protocols based upon the NPI whereas others do not use a single index score. Within NPI and non-NPI users, between-centre variability exists in guidelines for women for whom the benefits are uncertain. Consensus amongst units appears to be greatest when selecting women for adjuvant hormone therapy with the decision based primarily upon ER or progesterone receptor status rather than combinations of a number of factors. Guidelines as to who should receive adjuvant chemotherapy, however, were found to be much less uniform. Searches of the literature revealed only five published papers that had previously examined the cost-effectiveness of using prognostic information for clinical decision-making. These studies were of varying quality and highlight the fact that economic evaluation in this area appears still to be in its infancy. By combining methodologies used in determining prognosis with those used in health economic evaluation, it was possible to illustrate an approach for simulating the effectiveness (survival and quality-adjusted survival) and the cost-effectiveness associated with the decision to treat individual women or groups of women with different prognostic characteristics. The model showed that effectiveness and cost-effectiveness of adjuvant systemic therapy have the potential to vary substantially depending upon prognosis. For some women therapy may prove very effective and cost-effective, whereas for others it may actually prove detrimental (i.e. the reductions in health-related quality of life outweigh any survival benefit). CONCLUSIONS: Outputs from the framework constructed using the methods described here have the potential to be useful for clinicians, attempting to determine whether net benefits can be obtained from administering adjuvant therapy for any presenting woman; and also for policy makers, who must be able to determine the total costs and outcomes associated with different prognosis based treatment protocols as compared with more conventional treat all or treat none policies. A risk table format enabling clinicians to look up a patient's prognostic factors to determine the likely benefits (survival and quality-adjusted survival) from administering therapy may be helpful. For policy makers, it was demonstrated that the model's output could be used to evaluate the cost-effectiveness of different treatment protocols based upon prognostic information. The framework should also be valuable in evaluating the likely impact and cost-effectiveness of new potential prognostic factors and adjuvant therapies.

Adjuvants, Pharmaceutic↗
PubMedDate not supplied

A prognostic score for prostatic adenocarcinoma based on clinical, histological, biochemical and cytometric data from the primary tumour.

The aim of this study was to create a multivariate prognostic score for prostatic adenocarcinoma. A retrospective analysis of clinical, histological and cytometric prognostic factors in 325 cases of prostatic adenocarcinoma followed up on average over 13 years was performed. A multivariate prognostic score was built by using the independent prognostic factors. M-category, T-category, Gleason score and patient age were independent prognostic factors in the entire cohort. In MO tumors T-category, density of tumor infiltrating lymphocytes, the presence of apoptotic cells, and patient age were independent prognostic factors. In T1-2MO tumors the density of tumour infiltrating lymphocytes, mitotic index, standard deviation of maximum nuclear diameter and the serum level of acidic phosphatase were independent prognostic factors. By combining the coefficients of the regression model, a prognostic score was built for each of the tumour categories. The subsequent survival analysis based on the prognostic score indicated that it is a highly significant prognostic factor superior to individual prognostic parameters. The results show that the combination of prognostic data is a valuable tool in assessing the correct prognostic category for prostatic adenocarcinoma.

Adenocarcinoma↗
PubMed1998

Construction and validation of a practical prognostic index for patients with metastatic breast cancer.

PURPOSE: To identify the readily available prognostic factors most helpful in predicting survival and to construct and validate a prognostic index for metastatic breast cancer (MBC) patients. PATIENTS AND METHODS: Data from 233 MBC patients, accrued on a multiinstitutional randomized phase III trial (Japan Clinical Oncology Group [JCOG] study 8808), were analyzed to identify significant prognostic factors and a prognostic index was constructed by incorporating these prognostic factors. For validation of the prognostic index, another data set from 315 consecutive MBC patients, who had been treated with standard anthracycline-containing regimens, was analyzed. RESULTS: In multivariate regression analyses, history of adjuvant chemotherapy (ADJCT) (P = .0005), presence of distant lymph nodes (DLNs) (P = .0117) and liver (HEP) (P = .0099) metastases, elevation of serum lactate dehydrogenase (LDH) (P < .0001), and shorter disease-free interval (DFI) (P < .0001) significantly contributed to poorer survival. The prognostic index was constructed as follows: Prognostic Index = ADJCT (not received = 0, received = 1) + DLNs (absent = 0, present = 1) + HEP (absent = 0, present = 1) + LDH (< or = one times normal = 0, > one times normal = 1) + DFI (> or = 24 months = 0, < 24 months = 2). With this prognostic index, patients could be stratified into three risk groups. The median survival times (MSTs) of low-, intermediate- and high-risk groups were 45.5, 24.6, and 10.6 months, respectively (P < .0001). This prognostic index was applied to the validation patients. The respective MSTs for each risk group were 49.6,22.8, and 10.0 months (P < .0001). CONCLUSION: ADJCT, DLNs, HEP, LDH, and DFI were important prognostic factors for MBC patients. The prognostic index readily enables MBC patients to be stratified into three risk groups and is worth considering for future clinical trials.

Analysis of Variance↗
PubMed1992

Using Cox's proportional hazards model for prognostication in carcinoma of the upper aero-digestive tract.

One of the major short comings of the traditional TNM system is its limited potential for prognostication. With the development of multifactorial analysis techniques, such as Cox's proportional hazards model, it has become possible to simultaneously evaluate a large number of prognostic variables. Cox's model allows both the identification of prognostically relevant variables and the quantification of their prognostic influence. These characteristics make it a helpful tool for analysis as well as for prognostication. The goal of the present study was to develop a prognostic index for patients with carcinoma of the upper aero-digestive tract which makes use of all prognostically relevant variables. To accomplish this, the survival data of 800 patients with squamous cell carcinoma of the oral cavity, oropharynx, hypopharynx or larynx were analyzed. Sixty-one variables were screened for prognostic significance; of these only 19 variables (including age, tumor location, T, N and M stages, resection margins, capsular invasion of nodal metastases, and treatment modality) were found to significantly correlate with prognosis. With the help of Cox's equation, a prognostic index (PI) was computed for every combination of prognostic factors. To test the proposed model, the prognostic index was applied to 120 patients with carcinoma of the oral cavity or oropharynx. A comparison of predicted and observed survival showed good overall correlation, although actual survival tended to be better than predicted.

Adult↗
PubMed1999

Prognostic factors for carcinoma of the prostate.

Prognostic factors for prostatic carcinoma should be significant, independent and clinically important. They should be of practical use, and their determination should be affordable in everyday practice. Prognostic factors may be grouped into patient-related, tumor-related and treatment-related. They should meet certain requirements, such as possession of a clear biological significance, an adequate sample size (possibly more than 150 patients), no patient population bias, an adequate statistical test, such as Cox regression analysis, as well as optimized cut-off values and reproducibility. From a pathologist's view, prognostic factors with established values are grade, margin involvement, capsular penetration, seminal vesical involvement, metastases and invasion of fat in needle biopsies. In contrast to this, factors with little value are, among others, zone location or nuclear shape. If these guidelines for assessment of prognostic factors are not met, the prognostic factors grow exponentially, as an individual patient can only belong to one prognostic group. If one considers all three categories of prognostic factors together, the clinical stage matters most despite all uncertainties. The same holds true for grading; particularly, the well-differentiated grades on biopsy cores have the drawback of being reflected in the specimen only infrequently. The use of biomarkers to give a better prognostic information is also disappointing, as only PSA and PAP have a reliable value among 28 biomarkers. It is of note that new biomarkers are continuously being discovered and examined, such as cyclin A or D. Due to these deficiencies in all three categories of prognostic factors for prostatic carcinoma, prognostic indices in the form of nomograms were constructed. But, if these indices are employed to answer the most important question at the time of diagnosis, i.e., 'is this man a candidate for surveillance?', neoadjuvant treatment plus irradiation, neoadjuvant treatment plus radical prostatectomy, perineal radical prostatectomy, because of a low probability of extracapsular extension or positive lymph nodes, adjuvant therapy after local treatment with curative intent as opposed to progression-based treatment or immediate systemic treatment, let alone intermittent endocrine manipulation, are not reliably possible. The outcomes of the few available studies based on prognostic factors should be studied carefully. If considered, a valuable new way of estimating artificial neural networks is a possibility to come to practical terms.

Biomarkers, Tumor↗
PubMed2000

Prognostic factors in colorectal cancer. College of American Pathologists Consensus Statement 1999.

BACKGROUND: Under the auspices of the College of American Pathologists, the current state of knowledge regarding pathologic prognostic factors (factors linked to outcome) and predictive factors (factors predicting response to therapy) in colorectal carcinoma was evaluated. A multidisciplinary group of clinical (including the disciplines of medical oncology, surgical oncology, and radiation oncology), pathologic, and statistical experts in colorectal cancer reviewed all relevant medical literature and stratified the reported prognostic factors into categories that reflected the strength of the published evidence demonstrating their prognostic value. Accordingly, the following categories of prognostic factors were defined. Category I includes factors definitively proven to be of prognostic import based on evidence from multiple statistically robust published trials and generally used in patient management. Category IIA includes factors extensively studied biologically and/or clinically and repeatedly shown to have prognostic value for outcome and/or predictive value for therapy that is of sufficient import to be included in the pathology report but that remains to be validated in statistically robust studies. Category IIB includes factors shown to be promising in multiple studies but lacking sufficient data for inclusion in category I or IIA. Category III includes factors not yet sufficiently studied to determine their prognostic value. Category IV includes factors well studied and shown to have no prognostic significance. MATERIALS AND METHODS: The medical literature was critically reviewed, and the analysis revealed specific points of variability in approach that prevented direct comparisons among published studies and compromised the quality of the collective data. Categories of variability recognized included the following: (1) methods of analysis, (2) interpretation of findings, (3) reporting of data, and (4) statistical evaluation. Additional points of variability within these categories were defined from the collective experience of the group. Reasons for the assignment of an individual prognostic factor to category I, II, III, or IV (categories defined by the level of scientific validation) were outlined with reference to the specific types of variability associated with the supportive data. For each factor and category of variability related to that factor, detailed recommendations for improvement were made. The recommendations were based on the following aims: (1) to increase the uniformity and completeness of pathologic evaluation of tumor specimens, (2) to enhance the quality of the data needed for definitive evaluation of the prognostic value of individual prognostic factors, and (3) ultimately, to improve patient care. RESULTS AND CONCLUSIONS: Factors that were determined to merit inclusion in category I were as follows: the local extent of tumor assessed pathologically (the pT category of the TNM staging system of the American Joint Committee on Cancer and the Union Internationale Contre le Cancer [AJCC/UICC]); regional lymph node metastasis (the pN category of the TNM staging system); blood or lymphatic vessel invasion; residual tumor following surgery with curative intent (the R classification of the AJCC/UICC staging system), especially as it relates to positive surgical margins; and preoperative elevation of carcinoembryonic antigen elevation (a factor established by laboratory medicine methods rather than anatomic pathology). Factors in category IIA included the following: tumor grade, radial margin status (for resection specimens with nonperitonealized surfaces), and residual tumor in the resection specimen following neoadjuvant therapy (the ypTNM category of the TNM staging system of the AJCC/UICC). (ABSTRACT TRUNCATED)

Biomarkers, Tumor↗
PubMed1999

The development of a prognostic score for patients with parotid carcinoma.

BACKGROUND: Understanding of prognostic factors in parotid carcinoma has grown considerably. In particular, clinical tumor staging and histologic classification have been found to be prognostically important. Univariate and multivariate analyses have indicated that other variables, such as age, pain, skin invasion, and facial nerve impairment, are important predictors as well. In an actual patient, some of these factors are present and others are absent. However, a clinical tool incorporating this information, resulting in an individualized prognosis based on the combined effects of present adverse prognostic factors, has never been devised. METHODS: Of a cohort of 168 patients, 151 were evaluated to assess the prognostic value of clinical and pathologic factors in a multivariate proportional hazards analysis. Follow-up ranged from 1 to 278 months (median, 37 months). The end point was tumor recurrence. Identified prognostic factors and their hazard ratios were combined into prognostic scores. RESULTS: Clinical T classification, clinical N classification, pain, age at diagnosis, skin invasion, facial nerve dysfunction, perineural growth, and positive surgical margins acted as major factors predicting recurrence. A prognostic score (PS), generated by the weighted combination of the factors present in the individual patient, placed the patient in one of four subgroups with markedly different prognoses. In the subgroups based on the preoperative prognostic score, 5-year recurrence free percentages ranged from 92% (in the group PS1=1) to 23% (in PS1=4). In the subgroups based on the postoperative prognostic score, which took into account the histologic details of the resected specimen, 5-year recurrence free percentages ranged from 95% (in the group PS2=1) to 42% (in PS2=4). CONCLUSIONS: The proposed subgrouping, which is based on the combined effects of key prognostic preoperative and postoperative factors, provides a practical prognostic grouping system for the clinician treating patients with parotid carcinoma.

Adolescent↗
PubMed1998

Angiogenesis as a prognostic marker in breast carcinoma with conventional adjuvant chemotherapy: a multiparametric and immunohistochemical analysis.

It has now been clearly established that quantitative immunohistochemical methods applied to tumour angiogenesis under suitable quality control conditions are a powerful prognostic tool for use in the initial assessment of breast carcinomas. Appropriate parameters for predicting the aggressiveness of tumours and their sensitivity to treatment are, however, still required. To determine whether the microvessel count (MVC) may serve to predict the chemotherapeutic response, a retrospective study was carried out on a series of 162 patients with breast carcinoma, who were all treated with the same standard adjuvant chemotherapy. Angiogenesis was assessed by performing CD31 immunostaining and MVC per mm2. Several other factors such as P53, ERBB2, BCL2, and Ki67 were also measured, and their prognostic value was compared with that of the MVC. The MVC was not found to be correlated with any of the other prognostic parameters, but turned out to be of great prognostic value whatever the threshold value chosen, which suggests that it is continuously valid at all levels. The median value of the MVC (43.5 per mm2) divided this series into two significantly different prognostic categories, in terms of both disease-free survival (P = 0.0002) and overall survival (P = 0.037). Univariate analysis showed that most of the parameters analysed were of prognostic value regarding the disease-free survival, namely grade (P = 0.029), mitotic index (P = 0.049), size (P = 0.015), oestrogen receptors (P = 0.022), progesterone receptors (P = 0.018), P53 (P = 0.0045), ERBB2 (P = 0.046), and Ki67 (P = 0.0008). As regards overall survival, grade and ERBB2 showed a loss of prognostic value. In multivariate analysis on disease-free survival, the MVC was the most accurate prognostic factor (RR = 2.64), followed by Ki67 (RR = 2.06) and P53 (RR = 1.69). With respect to overall survival, the MVC ranked third among the prognostic parameters analysed. Standard chemotherapy did not reduce the high prognostic value of the MVC performed on tumour angiogenesis. This suggests that the MVC may predict the degree of resistance to chemotherapy. Patients with high levels of angiogenesis, particularly node-negative patients, might therefore be able to benefit from adjuvant therapy of another kind.

Antigens, Neoplasm↗
PubMed1995

Primary cutaneous melanoma. Identification of prognostic groups and estimation of individual prognosis for 5093 patients.

BACKGROUND: Numerous investigations have examined prognostic factors for patients with primary cutaneous melanoma. However, only a few studies have been published on the definition of prognostic groups. The first aim of the present study was to determine the relative importance of different prognostic factors in a large collective study. The second aim was to define prognostic groups of patients based on combinations of prognostic factors and to define a model that allows the estimation of individual survival probability. METHODS: Long term follow-up of 5264 patients with invasive primary cutaneous melanoma was performed from 1970 to 1988 at four German University Departments of Dermatology (Berlin-Steglitz, Münster-Hornheide, Tübingen, and Würzburg). The multivariate Cox model was used to analyze 5093 patients, and 4371 patients with complete information were included in a classification and regression tree analysis (CART). RESULTS: Tumor thickness, sex, anatomic location, and level of invasion were highly significant prognostic factors according to the multivariate analysis (P < 0.0001). However, histologic subtype and age influenced prognosis less significantly (P < 0.05). The CART analysis resulted in 12 groups defined mainly by tumor thickness, sex, and anatomic location, which were combined into five prognostic groups. The prognostic stratification defined by the five groups was superior compared with the standard TNM model. Ten-year survival rates of the five groups ranged from 97% to 14% (P < 0.0001), and an equation was used to calculate individual survival probabilities based on the significant factors of the Cox model. CONCLUSIONS: Consideration of all significant prognostic factors of patients with primary cutaneous melanoma investigated in the present study allows for the definition of prognostic groups with a more reliable estimation of prognosis than by previous staging systems and also enables calculation of individual survival probabilities.

Age Factors↗
PubMed1995

Significance of conventional and new prognostic factors for locally confined renal cell carcinoma.

BACKGROUND: The prognosis of patients with locally confined renal cell carcinoma is variable. To improve the prognostic knowledge and select patients at high risk, additional prognostic parameters are needed. METHODS: The significance with respect to survival and tumor recurrence of "classic" and "new" prognostic parameters has been examined by following 41 patients with locally confined renal cell carcinoma after nephrectomy (mean follow-up, 5.2 years). The significance of histologic grade, tumor stage, Ki-67 index, proliferating cell nuclear antigen index, 3H-thymidine labeling index, tumor ploidy status, and tumor growth after xenotransplantation into nude mice (GAX range) was tested using the Kaplan-Meier plots by the log rank test or Tarone's test and also by the Cox multiple hazard regression analysis. RESULTS: Tumor stage (P < 0.0025), histologic grade (P < 0.005), Ki-67 index (P < 0.006), and GAX range (P < 0.00004) were found to be significant prognostic parameters for survival and tumor recurrence using single-factor analysis. Applying the multivariate analysis, the combination of the "new" factors, GAX range and Ki-67 index, resulted in even a higher prognostic relevance than the combination of the "classic" prognostic factors, tumor stage and histologic grade. The calculated prognostic index based on the results of the Cox analysis, which, except for stage and grade, included the Ki-67 index, was shown to be highly correlated with survival (P = 0.00002) and tumor recurrence (P = 0.0004). Its prognostic validity was studied with the receiver operating characteristics procedure and was found to be considerably superior to that of the two conventional prognosticators. CONCLUSIONS: The additional determination of the Ki-67 labeling index increases the prognostic assessment of patients with locally confined renal cell carcinoma.

Animals↗
PubMed1995

Prognostic value of histopathologic parameters of esophageal squamous cell carcinoma.

BACKGROUND: The grading of squamous cell carcinoma (SCC) of the esophagus as proposed by the World Health Organization (WHO) has not yet proved to be prognostically significant. Therefore, the prognostic impact of various histologic parameters was investigated and compared with that of the WHO grading. METHODS: Hematoxylin and eosin-stained tumor samples from 138 patients with SCC of the esophagus who underwent potentially curative resection (no residual tumor or distant metastases) were evaluated for the following histologic parameters: degree of keratinization, nuclear polymorphism, pattern of invasion, mitotic activity, and inflammatory response. The prognostic impact of these parameters was analyzed by univariate and multivariate survival analyses. RESULTS: In the univariate analysis, the inflammatory response (P = 0.0006), pattern of invasion (P = 0.0011), and nuclear polymorphism (P = 0.0161) were the only parameters that correlated with survival. However, in a multivariate survival analysis including these parameters, only pattern of invasion (P = 0.0010) and inflammatory response (P = 0.0076) were prognostically significant. Based on these results, a new prognostic score system was defined that correlated significantly with survival in the univariate survival analysis (P = 0.0002). In contrast, the WHO histologic grade was not prognostically significant. In the multivariate Cox regression analysis, the new prognostic score system proved to be an independent prognostic parameter (P = 0.0062), ranking next to pT classification (P = 0.0001) and pN classification (P = 0.0014). CONCLUSIONS: For SCC of the esophagus, histologic grading based on pattern of invasion and inflammatory response had an independent prognostic impact, whereas the grading system proposed by the WHO had no significant prognostic value.

Adult↗