Clinical Risk During the Evaluation of Genomic Risk for Hormone-Sensitive Breast Cancer: Ignoring Valuable Data

Molecular testing to deliver personalized chemotherapy recommendations: risking over and undertreatment

BACKGROUND

In the adjuvant setting of cancer treatment, de-escalation strategies have the goal of omitting or minimizing treatment in patients, without compromising outcomes. Historically, eligibility for adjuvant treatment solely relied on the patient's clinical and tumor's pathological characteristics. At the turn of the century, based on new biological understanding, molecular-based strategies were tested and sometimes implemented.

MAIN BODY

However, we illustrate how molecularly based de-escalation strategies may paradoxically lead to overtreatment. This may happen when the novel approach is tested in lieu of standard management and may not yield the same results when being implemented in addition to usual practice. In the DYNAMIC trial, adjuvant chemotherapy decision in stage II colon cancer was compared between a circulating tumor DNA (ctDNA)-based approach and the standard care. We show this may result in more patients receiving oxaliplatin-based chemotherapy and may expose a similar proportion of patients to chemotherapy if the novel strategy is implemented in addition to usual practice. The other potential risk is undertreatment. We provide an illustration of early breast cancer, where the decision of adjuvant chemotherapy based on the gene expression signature MammaPrint may lead to inferior outcomes as compared with the clinico-pathologic strategy. This may also happen when non-inferiority designs have large margins. Among solutions, it should be acknowledged that clinico-pathological features, like T4 in colon cancer, may not be abandoned and replaced by novel strategies in real-life practice. Therefore, novel strategies should be tested in addition to standard of care, and not in lieu of. Second, de-escalation trials should focus on the settings where the standard of care has a widespread agreement. This would avoid the risk of testing non-inferiority against an ineffective therapy, which guarantees successes without providing informative data.

CONCLUSION

Simply because a molecular test is rational does not mean it can improve patient outcomes. Here, we highlight how molecular test-based strategies may result in either overtreatment or undertreatment. In the rapidly evolving field of medicine, where technological advances may be transformative, our piece highlights scientific pitfalls to be aware of when considering running such trials or before implementing novel strategies in daily practice.

A New Prognostic Model in Patients with Advanced Urothelial Carcinoma Treated with First-line Immune Checkpoint Inhibitors

BACKGROUND

While immune checkpoint inhibitors (ICIs) are approved in the first-line (1L) setting for cisplatin-unfit patients with programmed death-ligand 1 (PD-L1)-high tumors or for platinum (cisplatin/carboplatin)-unfit patients, response rates remain modest and outcomes vary with no clinically useful biomarkers (except for PD-L1).

OBJECTIVE

We aimed to develop a prognostic model for overall survival (OS) in patients receiving 1L ICIs for advanced urothelial cancer (aUC) in a multicenter cohort study.

DESIGN, SETTING, AND PARTICIPANTS

Patients treated with 1L ICIs for aUC across 24 institutions and five countries (in the USA and Europe) outside clinical trials were included in this study.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

We used a stepwise, hypothesis-driven approach using clinician-selected covariates to develop a new risk score for patients receiving ICIs in the 1L setting. Demographics, clinicopathologic data, treatment patterns, and OS were collected uniformly. Univariate Cox regression was performed on 18 covariates hypothesized to be associated with OS based on published data. Variables were retained for multivariate analysis (MVA) if they correlated with OS (p < 0.2) and were included in the final model if p < 0.05 on MVA. Retained covariates were assigned points based on the beta coefficient to create a risk score. Stratified median OS and C-statistic were calculated.

RESULTS AND LIMITATIONS

Among 984 patients, 357 with a mean age of 71 yr were included in the analysis, 27% were female, 68% had pure UC, and 13% had upper tract UC. Eastern Cooperative Oncology Group performance status ≥2, albumin <3.5 g/dl, neutrophil:lymphocyte ratio >5, and liver metastases were significant prognostic factors on MVA and were included in the risk score. C index for new 1L risk score was 0.68 (95% confidence interval 0.65-0.71). Limitations include retrospective nature and lack of external validation.

CONCLUSIONS

We developed a new 1L ICI risk score for OS based on data from patients with aUC treated with ICIs in the USA and Europe outside of clinical trials. The score components highlight readily available factors related to tumor biology and treatment response. External validation is being pursued.

PATIENT SUMMARY

With multiple new treatments under development and approved for advanced urothelial carcinoma, it can be difficult to identify the best treatment sequence for each patient. The risk score may help inform treatment discussions and estimate outcomes in patients treated with first-line immune checkpoint inhibitors, while it can also impact clinical trial design and endpoints. TAKE  HOME MESSAGE: A new risk score was developed for advanced urothelial carcinoma treated with first-line immune checkpoint inhibitors. The score assigned Eastern Cooperative Oncology Group performance status ≥2, albumin <3.5 g/dl, neutrophil:lymphocyte ratio >5, and liver metastases each one point, with a higher score being associated with worse overall survival.