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Conference Coverage

Assessing the Optimal Ki-67 Cut-Off for Outcome Prediction Among Patients With Newly Diagnosed Mantle Cell Lymphoma

Pooled Analysis From the CALGB 50403 (Alliance) and MCL Real-World Study Cohort

Featuring Narendranath Epperla, MD, MS


At the 65th ASH Annual Meeting, Narendranath Epperla, MD, MS, The Ohio State University Comprehensive Cancer Center, Columbus, Ohio, shared insights on the assessment of a modern optimal Ki-67 > 50% cut-off for patients with newly diagnosed mantle cell lymphoma (MCL), which was prognostic for progression-free survival, but not overall survival (OS) according to multivariable analysis. 

Dr Epperla and colleagues explained that the lack of prognostic value for OS may be due to the available effective therapies at relapse. They also noted that the diagnosis to treatment interval (DTI) was associated with a high Ki-67. A potential reason for the lack of prognostic relevance for OS in this more recent dataset, they added, is the availability of effective options at relapse. 

Transcript:

Hi, I'm Naren Epperla from Ohio State University, and today I have the pleasure of presenting the Ki-67 of 50% being the new cutoff in patients with mantle cell lymphoma. This is a pooled analysis from [the] mantle cell lymphoma real-world study (MCL-RWS) cohort and CALGB 50403. 

We all know that the Ki-67 cutoff of 30% has been prognostic, and that has been demonstrated over almost close to 2 decades now. It showed that the prognostic impact was significant even in those who were treated with [cyclophosphamide, doxorubicin, vincristine, prednisone] (CHOP) or [rituximab-CHOP] (R-CHOP) in that particular study. Subsequently, the high Ki-67, which is Ki-67 of 30% or higher, was combined with [Mantle Cell Lymphoma International Prognostic Index] (MIPI), and a new prognostic tool, known as combined-MIPI, was generated. This also showed that the patients who had high MIPI and high Ki-67, which is 30% or higher, tended poor outcomes for these patients. 

However, the Ki-67 of 30% was studied in patients who received first-line CHOP or R-CHOP treatment. It predates the advent of novel agents, and it did not include newer prognostic tools such as diagnosis to treatment interval and only included MIPI. Hence, in order to understand better what the cutoff is in the modern era, we undertook this project. 

In this study we had the pooled analysis from 2 datasets: one is a prospective dataset, which is the CALGB 50403, now known as Alliance in Clinical Trials, and the second is a mantle cell lymphoma real-world study, which is a retrospective study. A little over 1100 patients were included in the mantle cell lymphoma real-world study cohort, and close to 150 patients in the Alliance study, or the CALGB 50403. After excluding patients who had missing data and excluding patients in the mantle cell lymphoma real-world study who were enrolled on Alliance, a total of 793 patients remained. Among these, after excluding patients who had Ki-67, close to 350 patients remained. When we tried to compare patients, we then analyzed using spline analysis as to what the optimal Ki-67 cutoff was, using a continuous model and quadratic spline fit. 

We noted that at 50%, the relative risk of hazard rises, which means after 50% Ki-67, there was an increased risk of death. Hence, we chose Ki-67 of 50% as the cutoff for our study. We divided the patients into 2 groups, one with the Ki-67 of greater than 50%, and the other Ki-67 of less than or equal to 50%. The 2 groups were comparable in regards to the age, sex, [and] stage. However, patients in the Ki-67 greater than 50% had [Eastern Cooperative Oncology Group] (ECOG) performance status of 2 or higher. In other words, sicker patients had higher [lactate dehydrogenase] (LDH), which is LDH greater than the upper limit of normal, had MIPI 6.2 or higher, and had a short diagnosis to treatment interval. When we tried to stratify the patients based on the Ki-67, we had 4 groups: greater than 50%, 30 to 50%, less than 30 to greater than 10%, and less than 10%. 

We clearly saw that the patients who had greater than 50% Ki-67 had inferior progression-free survival, as well as overall survival. We then did the Cox modeling in the [univariable] (UNI) variable Cox modeling. We noted that the patients who had Ki-67 greater than 50% had inferior [progression-free survival] (PFS). Patients who had high ECOG performance status that is 2 or higher had inferior PFS. Patients with short [diagnosis to treatment interval] (DTI) had inferior PFS, as well as patients with MIPI of 6.2 or higher had inferior PFS. After controlling for these factors that were significant in the univariable analysis, we found that the patients who had Ki-67 greater than 50% still remained significantly associated with inferior progression-free survival. We then did the Cox modeling for overall survival. In the univariable Cox model, we noted the patients who had Ki-67 greater than 50% had inferior overall survival. Also, patients who are males had inferior overall survival. However, when we controlled for other factors in the multi-variable analysis, Ki-67 greater than 50% was no longer significant for mortality. 

In conclusion, we would like to say that Ki-67 greater than 50% seemed to potent inferior progression-free survival. However, it did not potent inferior overall survival. One of the potential reasons for this could be that in this current day and age, we have effective options at relapse, and thereby we probably did not see the overall survival difference. Also of note, patients with Ki-67 greater than 50% were associated with short DTI. We would like to further validate the findings that we noted in the subsequent analysis.


Source: 

Epperla N, Switchenko JM, Geyer SM, et al. Ki-67 Expression of 50% Is the Optimal Cut-Off to Predict Survival Outcomes in Mantle Cell Lymphoma (MCL): A Pooled Analysis from CALGB 50403 (Alliance) and MCL Real-World Study Cohort. Presented at the 2023 ASH Annual Meeting: December 9-12, 2023. San Diego, CA. Abstract 380

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Any views and opinions expressed are those of the author(s) and/or participants and do not necessarily reflect the views, policy, or position of Oncology Learning Network or HMP Global, their employees, and affiliates. 

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