Data are insufficient to recommend use of p53



Data are insufficient to recommend use of ras

Source: Adapted from Bast RC Jr, Ravdin P, Hayes DF, et al.,3 by permission of J of Clinical Oncology.

Source: Adapted from Bast RC Jr, Ravdin P, Hayes DF, et al.,3 by permission of J of Clinical Oncology.

ity or resistance to therapy. Therapies for most solid tumors include surgery, radiation, and systemic therapies such as hormone therapies or chemotherapies. In this regard, the terms "prognostic" and "predictive" have taken on separate meanings.5,6 The prognostic factor designation is usually reserved for those markers that specifically provide an estimate of the odds of the recurrence of a given cancer after local therapy only. It is usually a measure of both proliferation and metastatic potential, and it usually implies the odds of systemic recurrence and/or death in a patient who does not receive systemic therapy. If the factor is associated with a poor prognosis, patients who are "positive" for the prognostic factor have a worse outcome than those who are "negative" in the absence of systemic therapy. Therapy may be

TABLE 7.2. Potential uses of tumor markers.

Determination of risk Screening

Differential diagnosis Benign vs. malignant Known malignant: tissue of origin Prognosis Prediction

Monitoring disease course

Detect recurrence in patient free of obvious disease Patient with established recurrence effective, but it is equally so (in relative terms) for both factor-positive and factor-negative patients. The best examples of prognostic factors for most solid tumors are the TNM staging systems.

A predictive factor helps select therapies most likely to work against that patient's tumor. A predictive factor may be the precise target of the therapy, an associated molecule or pathway that modifies the effectiveness of the therapy, or simply an alteration that is an epiphenomenon linked to the target or pathway of the therapy (such as coamplification of a neighboring gene). If the factor is a pure predictive factor, prognosis in the absence of therapy is the same for factor-negative and -positive patients (it has no prognostic effects). However, assuming it predicts for benefit from therapy, factor-positive patients have a much better prognosis than factor-negative patients in the presence of the therapy for which the factor is predictive. For example, it is now clearly established that the level of estrogen receptor (ER) content in breast cancer tissue is positively related to the odds of response and benefit from antiestrogen hormonal therapy, such as ovarian ablation, tamoxifen, or aromatase inhibitors, because the ER plays a fundamental role in estrogen-dependent tumor growth and biology.7 In contrast, ^-glycoprotein content is a negative predictive factor for resistance to certain drugs, because this protein modulates multidrug resistance by increasing efflux of the antineoplastic agent from the cancer cell.8

Many, in fact most, factors may be both prognostic and predictive. For example, in addition to serving as a predictive factor, ER is also a favorable prognostic factor. Breast cancers with high ER content have generally slower growth potentials, and patients with ER-"positive" tumors have a better prognosis, even if they receive no treatment.9,10

To further complicate this discussion, some markers may be associated with a poor prognosis independent of therapy, but they may predict for an improved outcome related to specific treatment modalities. For example, in breast cancer, amplification and/or overexpression of HER-2 is a marker of poor prognosis in the absence of any systemic therapy.11-14 However, HER-2 serves as the target for a humanized monoclonal antibody, trastuzumab (herceptin), and response and benefit from trastuzumab are tightly linked to HER-2 amplification and/or overexpression.15,16 Thus, untreated HER-2-positive patients have a worse prognosis than HER-2-negative patients if they do not receive trastuzumab, but they may actually have a more favorable prognosis if they do.

These considerations are often ignored in many "prognostic factor" studies. Often, a population of patients is studied with a new, putative prognostic factor simply because the samples to be assayed happen to be available and the outcome for the patients is known. Indeed, a prognostic factor can only be evaluated in the absence of systemic therapy, or at least in the absence of any therapy with which it interacts. A predictive factor can only be evaluated in the context of an untreated control group, preferably one that is prospectively identified and followed, as in prospective randomized trials. It is not surprising that studies of a marker that might have both prognostic and predictive capabilities, especially if these effects are in opposition (as may be the case with HER-2), will provide relatively random and conflicting results if not carefully planned with appropriate consideration of treatment effects control groups and satisfactory control groups.

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