Correlation Between Oncotype DX, PREDICT and the Nottingham Prognostic Index: Implications for the Management of Early Breast Cancer (2024)

Monitoring Editor: Alexander Muacevic and John R Adler

Abstract

Keywords: oncotype dx, npi, predict, breast cancer recurrence, adjuvant chemotherapy, breast cancer, er-positive, lymph node-negative, her2-negative

Introduction

Breast cancer remains the most common type of cancer in the UK, accounting for 15% of all new cancer diagnoses. Approximately 55,200 new breast cancers are diagnosed each year [1]. Unfortunately, the five-year relative survival for breast cancer in women in England is below the European average.Overall survival is shown to have been improved through the delivery of chemotherapy [2]. However, chemotherapy regimens are associated with higher costs as they are more resource-intensive[3]. In addition, chemotherapy isassociated with toxic side effects including cardiac toxicity, neutropenic sepsis, myelosuppression and neuropathy [4].

The absolute benefit of chemotherapy is proportional to the absolute risk of recurrence. Improved information on individual patients' risk of recurrence (i.e. prognostic risk) and predicted response to chemotherapy (i.e. predictive benefit) may help target chemotherapy to patients who will receive the greatest benefits [5].In current practice, there are two main types of modalities utilised to estimate an individual patient'srisk of recurrence and prognosis. The first set of modalities are risk calculators and scoring systems, such as PREDICT and the Nottingham Prognostic Index (NPI). Theseclinicopathological scoring systemsincorporate features such as age at diagnosis, lymph node status, tumour size, histological grade, lymphovascular invasion and hormone receptor expression. NPI generates a five- and 10-year survival score, whilePREDICT produces a score that predicts benefit from chemotherapy treatment.

The second set of modalities includesgenetic profiling such as Oncotype DX (ODX; Genomic Health, Redwood City, CA). This21-gene assaygenerates a Recurrence Score (RS) that predicts the benefit from chemotherapy treatment in terms of a reduction in the 10-year risk of recurrence for a particular breast cancer. A 'low' RSindicates a low risk of cancer recurrence even withoutchemotherapy treatment, while a 'high' RS predicts recurrence and indicates the benefit of chemotherapy treatment. The use of ODX testing helps to inform adjuvant chemotherapy treatment decisions by identifying patients who will derive the greatest benefit from chemotherapy and those who will not, thereby preventing over-treatment, unnecessary exposure to the risk of side effects and high cost of chemotherapy treatment [5].

That said,ODX testing is also expensive and costs£2,580 per patient [6]. Bycomparison, online scoring systems such as PREDICT and NPI are easilyavailable online andfree of cost. Therefore, the judicious use of ODX testing is also paramount.PREDICT, NPI and ODX all provide an indication of the recurrence risk for individual patients with early breast cancer, based largely on estimations of risk of breast cancer recurrence from established data [7-9].This study compares PREDICT, NPI and ODX RSwith the aim of assessing 1) the correlation between the RS for PREDICT, NPI and ODXand 2) whether early breast cancer patients are stratified into similar risk categories by all three modalities.

Materials and methods

Patient population

This study reviewed consecutive early breast cancer patients treated at ourNational Health Service (NHS) institution over a 12-month period (October 1, 2017 toSeptember 30, 2018). Inclusion criteria were as follows:consecutive patients with early breast cancer, defined as estrogen receptor (ER)-positive, human epidermal growth factor receptor 2 (HER2)-negative and lymph node-negative breast cancer. All patients were assessed at the local multidisciplinary team (MDT) meeting for ODX testing. Exclusion criteria were as follows:patients without ODX test scores; patients with an in-breast recurrence; patients who did not undergo a sentinel lymph node biopsy (SLNB); and patients with ductal carcinoma in situ (DCIS) only.

Data collection

Patients were identified through MDT records. Data were collected on patient demographics and clinicopathological factors from electronic patient notes and histology reports. NPI and PREDICT scores were calculated for each patient using online tools [7,9]. For PREDICT, version 2.0 was utilised and third-generation chemotherapy was selected for all patients. A 10-year survival benefit from chemotherapy was used to risk-stratify patients.The RS for each patient was obtained through Genomic Health (Genomic Health, Redwood City, CA).

Data analysis

Patients were risk-stratified into recurrence groups based on their chemotherapy benefits, prognosis and risk of RS generated by PREDICT, NPI and ODX, respectively [7-9]. Thresholds for risk stratification were based oncurrent practice at our institution, which is evidence-based and isoutlined in Table ​Table1.1. Scatter plots for correlations between RS, PREDICT and NPI were analysed using Spearman’s correlation coefficient.Statistical analysis was performed using GraphPad Prism 8.1 (GraphPad Software,San Diego, CA).

Results

Patient and tumour characteristics

This study included 46 consecutive patients (mean age: 56 years) who underwent ODX genetic profiling at our institution over the study period. These patients were treated for 57 ER-positive, HER2-negative and lymph node-negative early breast cancer. Table2summarises patient and tumour characteristics. The median tumour size was 2.4 cm. The median tumour grade was 3; 14/46 (30%) patients had screen-detected tumours, and 8/46 (30.4%) had multifocal disease. The median PREDICT, NPIand RSwere 3, 3.4, and 17, respectively.

Correlation between PREDICT and Nottingham Prognostic Index

Figure1shows a comparison of NPI and PREDICT for all patients included in this study. A Spearman r test demonstrated a highly significant and very strong overall correlation between the PREDICT calculated risk of recurrence compared to the score generated through NPI(all patients: r=0.92; P=0.0001). A sub-analysis stratified by risk category demonstrated that PREDICT correlated strongly with NPI forpatients with both low PREDICT score (i.e. PREDICT score of <3) and intermediate/high PREDICT score (i.e. PREDICT score of ≥3; r=0.66, P=0.0009 and r=0.86, P=0.0001, respectively).

Correlation between PREDICT and Oncotype DX

Overall, the PREDICT score and the RS from ODX were only weakly, albeit significantly, correlated when scores for all patients were analysed (r=0.34, P=0.0193; Figure2). A similarly weak, yet significant correlation was also found between NPI and RS for all patients (r=0.38, P=0.0099). However, a sub-analysis of patients with lowPREDICT score (i.e. PREDICT score of <3) demonstrated a strong and significant correlation between PREDICT and RS (r=0.51, P=0.0134), while the correlation between PREDICT and RS was very weak and non-significant for patients with intermediate/high PREDICT score(i.e. PREDICT score of ≥3; r=-0.0064, P=<0.9767). Similarresults were observed when analysing the strength and significance of a correlation between NPI and RS (patients with excellent/good risk NPI score of ≤3.4: r=0.42, P=0.0302; andpatients with moderate/poor risk NPI scoreof >3.4: r=0.0093, P=0.9700;Figure3). Together, this suggested that patients with an estimated low risk of recurrence using PREDICT or NPIare likely to receive a similarly low recurrence risk from ODX testing.

The degree of disparity between PREDICT score and RS is shownbelow (Table ​(Table3).3). It shows the stratification of patients byPREDICT and RS risk category; 7/46 (15.2%) patients had a low PREDICT score but either an intermediate or high RS, and 9/46 (19.6%) patients had either an intermediate or high PREDICT score but low RS. Similar results were also observed when comparing NPI and RS, suggesting that the majority of patients (58.7%) were assigned to differentcategories of recurrence risk depending on whether this was based on the PREDICT/NPI or RS(Table4).

In total, only 19/46 (41.3%) patients had an RS risk category that corresponded with their PREDICT risk category (Table ​(Table5).5). In fact, 18/46 (39.1%) patients had a higher RS risk category compared to their PREDICT risk category, while 9/46 (9.1%) patients had a lower RS risk category compared to their PREDICT risk category. Again, similar results were also found when comparing NPI and RS risk categories, suggesting that, for a majority of patients, the risk categories were changed after ODX testing (Table6).

Discussion

NPI and PREDICT are tools commonly used in the UK byMDTs to estimate the risk of recurrence toguide adjuvant chemotherapy treatment in early breast cancer. This study demonstrates that the risk of recurrence estimated by PREDICT strongly correlated with that generated by NPI. Therefore, either modality is likely to generate a similarly low, intermediate or high risk of recurrence for a given patient. However, several studies have highlighted the shortcomings and questioned the validity of NPI and PREDICT [10-12].A study by Plakhins et al. showed that overall survivaland breast cancer-specific survival obtained from PREDICT were significantly lower than the observed survival of the study population [12]. Lambertini et al. have shown NPI to alsosignificantly underestimate10-year overall survivalin both young and old patients [13]. This is reflected in our results, which demonstrated that nearly 40% of the patients had a higher risk of recurrence after ODX testing than that based initiallyon PREDICT or NPI.

There were three patients in our study who had a PREDICT 10-year benefit from adjuvant chemotherapy of <3% (low risk); however, after ODX testing, these three patients had an RS of ≥26 (high risk). These patients were between 47-67 years of age with grade 2-3unifocal cancers, measuring14-45 mm in size. One patient in our study had a PREDICT 10-year benefit from adjuvant chemotherapy of >5% (high risk); however, after ODX testing, this patient had an RS of ≤17 (low risk). This patient was35 years of age with grade 3 unifocal cancer, measuring 60 mm in size.

A recent systematic review has suggested that ODX testing is superior to online prognostication tools at assessing recurrence risk [14]. NPI was developed in 1982and PREDICT was validated by Wishart et al. in 2010 [8,9]. Breast cancer is recognised as a heterogeneous, phenotypically diverse disease with distinct behaviours and responses to therapy, and, therefore, these scoring systems provide little information regarding how individual cancers will respond to treatment [14]. This is where the advent of genetic profiling, such as ODX and Prosignia (NanoString Technologies, Seattle, WA), is playing a significant role in guiding adjuvant chemotherapy treatment.

In our study, the majority of patients estimated to be at a low risk of recurrence by NPI/PREDICT were also found to have a low RS. The correlation between these scoring modalities wasstatistically significant and strong in the sub-analysis of patients with low NPI/PREDICT score, suggesting concordance between these three risk predictive modalities for low-risk patients. However, nearly 60% of all patients, irrespective of NPI/PREDICT score, had aPREDICT or NPI risk category that was different from therisk category estimated through ODX testing. In the subgroup of patients with PREDICT/NPI intermediate or high risk, the correlation between the recurrence risk generated by RS was very weak and non-significant. This has implications for adjuvant treatment. A recentsystematic review and meta-analysis have demonstrated that ODX testing significantly changed the clinicopathologically based adjuvant chemotherapy recommendations [15].

The landmark TAILORx Trial advocated the use of ODX to guide adjuvant treatment [7]. This 21-gene assay may identify up to 85% of women with early breast cancer, who can be spared adjuvant chemotherapy, especially those who are older than 50 years in age and have an RS of 25 or lower [7].ODX was found to be a more accurate predictor of relapse than standard clinical features for individual patients [16]. Furthermore, ODX testing has been shown to result incost-savings and a significant reduction in chemotherapy administration [7,17]. A meta-analysis by Carlson et al.reported that ODX testing changed treatment decisions for 49% of the patients [15]. Similarly, a study by Smyth et al.has noted that 59% of treatment recommendations changed after ODX testing [17].

At present, the National Institute for Health and Care Excellence (NICE) recommends the use of ODX testing to guide the decision-making on chemotherapy after surgery in ER-positive, HER2-negative and lymphnode-negativeearly breast cancer patients [18]. In particular, NICE advocates the utilisation of ODX only for patients deemed to be at an intermediate risk of recurrence. Indeterminate risk is defined by NICE as an NPI of greater than 3.4, or patients identified as intermediate risk by another validated scoring system (e.g. PREDICT). In support of the NICE guidance, this study demonstratesthatfor intermediate-risk patients, there is a lack of correlation between PREDICT/NPI and RS, thus justifying the use of ODX not only in this cohort but also for PREDICT/NPI high-risk patients as well.

A potential limitation of this study is the fact that the dataset may have under-represented ethnic minorities and young patients. In addition, thecohort included in this study was relatively small, limiting the generalisability of our conclusions.

Conclusions

In conclusion, the results of this studyhave two implications for clinical management. First,patients with low-risk PREDICTor NPI scores areunlikely to have their management altered by ODX testing since low-risk PREDICT and NPI scores and RSare strongly correlated; therefore, this represents an opportunity for cost-saving by avoiding unnecessary and expensive genetic testing in patients for whom the results of ODX testing may provide no additional information over that offered by PREDICT or NPI. Secondly, patients with intermediate-/high-risk PREDICT or NPI scores are more likely to receive an RSthat places them in a differentrisk category with regards to recurrence riskand, hence, the RS may be utilised by the MDT to guide adjuvant treatment decisions in patients with intermediate-/high-risk PREDICT or NPI scores. Further research is required to see if these results could be extended to larger and more diverse patient populations.

Acknowledgments

Authors Christopher Hillyar and Hirah Rizki contributed equally to this research and should be considered joint-first authors.

Notes

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