TRANSLATE

The mpn Hub website uses a third-party service provided by Google that dynamically translates web content. Translations are machine generated, so may not be an exact or complete translation, and the mpn Hub cannot guarantee the accuracy of translated content. The mpn and its employees will not be liable for any direct, indirect, or consequential damages (even if foreseeable) resulting from use of the Google Translate feature. For further support with Google Translate, visit Google Translate Help.

The MPN Hub is an independent medical education platform, sponsored by AOP Health and GSK, and supported through an educational grant from Bristol Myers Squibb. The funders are allowed no direct influence on our content. The levels of sponsorship listed are reflective of the amount of funding given. View funders.

Now you can support HCPs in making informed decisions for their patients

Your contribution helps us continuously deliver expertly curated content to HCPs worldwide. You will also have the opportunity to make a content suggestion for consideration and receive updates on the impact contributions are making to our content.

Find out more

Prognostic model to predict survival in MF after 6 months of treatment with ruxolitinib helps to identify candidates for second-line treatment and SCT

By Oscar Williams

Share:

Mar 7, 2022


Myelofibrosis (MF) is the most heterogenous of all myeloproliferative neoplasms and is associated with the most severe prognosis. Ruxolitinib (Rux) is often accompanied by suboptimal responses, loss of response over time, and significant discontinuation rates in clinical and real-world settings.1 Failure on ruxolitinib is associated with poor prognosis and survival, and the lack of criteria to predict survival may impact treatment decisions (e.g., timely switch to second-line treatments).

Margherita Maffioli et al.1 conducted a study to identify the early predictors of inferior survival in patients with MF receiving ruxolitinib in real-world settings that may inform clinical decisions (NCT03959371); the results have been reported in Blood Advances1 and we provide a summary below.

Study design and patients

The study comprised two cohorts:

  • Training cohort included 288 patients with MF followed across 17 centers; among these patients, 209 who met the selection criteria were included in the analysis (study cohort):
    • At least 6 months of follow-up after ruxolitinib initiation
    • Platelet count >50 × 109/L
    • Spleen enlargement at least 5 cm below the left costal margin
    • International Prognostic Scoring System (IPSS) intermediate-1 risk or higher
  • Validation cohort of 91 patients treated at Moffitt Cancer Center, Tampa, US

To investigate early predictors of poor survival, the investigators focused on changes in clinical data within a 6-month period, including assessing data at 3 months and the established baseline.

Results

In the training cohort (N = 288), patients had the following characteristics:

  • Median age: 67 years (range, 37–85)
  • Median time between diagnosis and study enrolment: 29 months
  • Secondary MF: 54.1%
  • Bone marrow fibrosis Grade 2–3: 76.6%

In the study cohort (n = 209):

  • Median follow-up (from ruxolitinib initiation) was 30.5 months (IQR, 9.7–50.0 months).
  • Median treatment time for ruxolitinib was 28.2 months; the most common starting dose was 20 mg (in 37.3% of patients), administered twice daily.
  • 77 patients (36.8%) required lower starting doses based on baseline platelet levels.
  • At data cut-off, 100 patients (47.8%) were receiving ruxolitinib, whereas 75 patients discontinued treatment due to absence of spleen response, leukemic transformation, infection, and hematologic toxicity.
  • 71 patients (34%) died; ruxolitinib treatment was still ongoing at the time of death for 34 patients. The cause of death included blast phase, MF progression, infection, and secondary primary malignancy.

Risk factors that were found to negatively impact overall survival (OS) are shown in Table 1. The estimated median OS from diagnosis was 145 months, and from ruxolitinib initiation was 59.4 months.

Table 1. Risk factors that negatively impacted OS*

BID, twice a day; OS, overall survival; RBC, red blood cell; Rux, ruxolitinib; SLR, spleen length reduction; TDD, total daily dose.
*Adapted from Maffioli et al.1

Characteristic, n (%)

At 3 months of Rux treatment

At 6 months of Rux treatment

SLR with respect to baseline

              ≤30%

87 (41.6)

90 (43.1)

              >30–50%

58 (27.8)

47 (22.5)

RBC transfusions, 0–3 months after Rux start

              Yes

91 (43.5)

              No

113 (54.1)

              Unknown

5 (2.4)

RBC transfusions, 3–6 months after Rux start

              Yes

84 (40.2)

              No

116 (55.5)

              Unknown

9 (4.3)

Rux dose

              <20 mg BID (<40 mg TDD)

163 (78.0)

161 (77.0)

              ≥20 mg BID (≥40 mg TDD)

44 (21.1)

41 (19.6)

The multivariable Cox proportional hazard regression identified the following characteristics as risk factors of poor survival: ruxolitinib treatment at a dose of <20 mg at baseline, Month 3 and 6 (hazard ratio [HR] 1.79; 95% CI, 1.07–3.00; p = 0.03), palpable spleen length reduction ≤30% (HR 2.26; 95% CI, 1.40–3.65; p < 0.0009), the need for red blood cell (RBC) transfusions at Month 3 and/or 6 (HR 1.66; 95% CI, 0.95–2.88; p = 0.07), and the need for RBC transfusions at all time points (HR 2.32; 95% CI, 1.19–4.54; p = 0.02).

Development and validation of the prognostic model

To assess the collected prognostic information, the investigators built a model to predict survival outcome, the ‘Response to ruxolitinib after 6 months’ (RR6) model. Each risk factor was assigned a weighting based on its hazard ratio:

  • 1 point if patients were receiving a dose of <20 mg ruxolitinib at all points
  • 1 point if transfusion was required at 3 and/or 6 months
  • 1.5 points if there was a palpable spleen length reduction ≤30% from baseline at 3 and 6 months
  • 1.5 points if transfusion was needed at all time points

A score was calculated, ranging from 0 to 4, used to sort patients into three prognostic groups:

  • Low risk (19.1% of patients)
    • Score 0
    • No poor prognostic factor
    • Median OS not reached
  • Intermediate risk (45.2% of patients)
    • Score 1–2
    • Median OS, 61 months
  • High risk (35.6% of patients)
    • Score ≥2.5
    • Median OS, 33 months

To validate the model, a multivariable Cox proportional hazard regression of the RR6 model was performed, adjusting for the category disease-specific risk at baseline, which showed a HR of 3.50 (95% CI, 1.34–9.12; p = 0.01) and of 5.92 (95% CI, 2.22–15.82; p = 0.0004) for intermediate and high vs low-risk patients, respectively. The model was then applied to the validation cohort comprising 40 patients (subjected to the study selection criteria), and its predicative ability was confirmed (log-rank test overall p = 0.0276).

Conclusion

This study indicates that survival is correlated with higher ruxolitinib dose intensity resulting in better spleen response rates and greater spleen reduction. Transfusion dependency was also found to negatively correlate with the probability of obtaining a spleen response during ruxolitinib therapy and predicts drug discontinuation. The RR6 model may be useful for physicians in terms of identifying candidates earlier for approved second-line treatment, stem cell transplant (SCT) candidates, and patients in need of investigative second-line interventional trials due to limited survival.

With regards to applying disease-specific risk scores at 6 months from treatment start, this was found to be not entirely useful as the model failed to effectively distinguish intermediate-2 from low/intermediate-1 risk patients.

References

Please indicate your level of agreement with the following statements:

The content was clear and easy to understand

The content addressed the learning objectives

The content was relevant to my practice

I will change my clinical practice as a result of this content

Your opinion matters

On average, how many patients with myelofibrosis do you see in a month?