Risk Prediction Calculators Multiply in Cancer Care

Andrew D. Smith
Published: Monday, Oct 01, 2018
Andrew J. Vickers, PhD

Andrew J. Vickers, PhD

Current guidelines from the National Comprehensive Cancer Network (NCCN) recommend that patients with oropharyngeal squamous cell carcinoma (OPSCC) receive surgery or radiation therapy delivered with or without chemotherapy. Although minimally invasive techniques have made surgery a more attractive option than it was previously, particularly for younger patients, the question of whether adjuvant chemoradiation therapy (CRT) should be administered with either front-line approach is unsettled.1,2

Like clinicians elsewhere, investigators from the University of Colorado, Denver, struggled not only to predict the likelihood that a particular patient would do well with surgery alone but also to convey their estimates in terms that patients would understand. To solve this dilemma, they collected clinical factors about patients with OPSCC from the National Cancer Database to build a nomogram that can be used preoperatively to help determine the need for adjuvant CRT. The investigators used data from 5065 patients to identify the preoperative variables that best predicted 2 high-risk pathological features: extracapsular extensions in the regional lymph nodes and/or positive surgical margins.

They then used a multivariable regression analysis to create a formula for combining those variables to quantify risk. Finally, they rendered that formula as a nomogram, which in this case is a graphic that illustrates relationships in complex equations so that patients and doctors alike can understand these relationships and make informed treatment decisions.2 In doing so, the investigators joined a growing number of other researchers who are developing nomograms that assess individualized risks in a broad range of clinical settings and tumor types. Despite several limitations, oncology nomograms have been growing in number and gaining in popularity.

Of the total 2895 articles with the words nomogram and cancer that are indexed on PubMed, more than half have appeared in just the past 5 years; in the past 2 months alone, studies involving at least half a dozen new oncology-related nomograms have been published. The major appeal of nomograms is the promise of greater predictive accuracy than can be achieved with conventional tools such as the tumor–node–metastasis (TNM) staging system, which dates to 1953.3 Nomograms can provide more individualized outcome predictions by attempting to calculate the combined effect of many factors, such as tumor genetics, age, race, sex, comorbidities, diet, and behavior.

They can also use tumor data to provide more refined predictions than the TNM system because they can accept tumor size and spread as continuous variables rather than categorizing all tumors into a small number of stages. “Nomograms are valuable tools for doctors, not only because they help doctors make recommendations but also because they help doctors justify those recommenda- tions with numbers that are comprehensible to patients in a way that regression analyses are not,” said Mohammad K. Hararah, MD, MPH, a fourth-year otolaryngology–head and neck surgery resident at the University of Colorado and the lead author of the OPSCC study. “It’s tough for these patients, particularly the younger ones, to decide between undergoing a complicated surgery or combination chemoradiotherapy,” he said. “No one wants to suffer from decades of adverse effects from chemotherapy or radiation when a single surgery would have been sufficient and curative. However, sometimes surgery isn’t enough if pathological evaluation shows features of an aggressive cancer.

The nomogram won’t make the decision easy, but it does at least make it easy for [patients] to understand their own risk and make a well-informed decision.” Nevertheless, as nomograms have prolif- erated in cancer care, so have cautions about how to evaluate individual calculators. Experts say key elements of a well-constructed nomo- gram include an appropriately defined patient population, a precise definition of the primary outcome, identification of the factors that could predict the outcome, an effective statistical model, and a validated outcome (FIGURE).4,5 Importantly, there are limitations to nomograms.

These include the fact that data used to construct nomograms are from a particular timeframe and are therefore static, a lack of accepted standards of reporting, a paucity of information on how effective they are in communicating with patients, and questions about their clinical utility.5 Although there have been many criticisms of nomograms over the years, several major cancer centers have embraced the develop- ment of these calculators as prediction tools. Originally designed as graphical representations, many nomograms are now available as online calculators that yield definitive values.


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TitleExpiration DateCME Credits
Community Practice Connections™: Oncology Best Practice™ Decision Points in Advanced NSCLC: Assessing Treatment Options Beyond Disease ProgressionNov 30, 20181.0
Community Practice Connections™: Precision Medicine for Community Oncologists: Assessing the Role of Tumor-Testing Technologies in Cancer CareNov 30, 20181.0
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