Risk of disease recurrence and survival in patients with multiple myeloma: A German Study Group analysis using a conditional survival approach with long‐term follow‐up of 815 patients

• Published in: Cancer 2020-08, Vol.126 (15), p.3504-3515
• Main Authors: Schinke, Maximilian, Ihorst, Gabriele, Duyster, Justus, Wäsch, Ralph, Schumacher, Martin, Engelhardt, Monika
• Format: Article
• Language: English
• Subjects: Adult; Aged; Aged, 80 and over; conditional survival (CS); Cytogenetics; Diagnosis; Disease-Free Survival; Female; Follow-Up Studies; Health risk assessment; Health risks; Humans; Male; Medical prognosis; Middle Aged; Multiple myeloma; Multiple Myeloma - diagnosis; Multiple Myeloma - epidemiology; Multiple Myeloma - pathology; Multiple Myeloma - therapy; Multivariate analysis; Neoplasm Recurrence, Local - diagnosis; Neoplasm Recurrence, Local - epidemiology; Neoplasm Recurrence, Local - pathology; Neoplasm Recurrence, Local - therapy; Oncology; Parameters; prediction of outcome; Prognosis; Proportional Hazards Models; Regression analysis; Regression models; Risk Assessment; Risk Factors; Statistical analysis; Survival; Survival Rate; Treatment Outcome; updated risk parameter analysis
• ISSN: 0008-543X; 1097-0142
• DOI: 10.1002/cncr.32978

Background Unlike the traditional method of overall survival prediction in patients with cancer, conditional survival predicts the survival of patients dynamically throughout the course of disease, identifying how a prognosis evolves over time. Methods The authors assessed 815 consecutive patients with multiple myeloma through the German Study Group on Multiple Myeloma (Deutsche Studiengruppe Multiples Myelom; DSMM) incentive. Over 10 variables, including patient‐specific and multiple myeloma–specific parameters, were analyzed at the time of initial diagnosis and repeatedly during follow‐up. The probability of survival for another 5 years was calculated according to disease‐related and host‐related risks. Multivariate Cox models were used to determine baseline and updated prognostic factors for survival. Results The median follow‐up and overall survival were 10.3 years and 5.1 years, respectively. When comparing 5‐year conditional survival probabilities from the data derived at the time of initial diagnosis with those updated over time, substantially differing prognoses were observed when follow‐up data were used. Multivariate Cox regression models for cohorts surviving 0 to 5 years demonstrated hazard ratios (HRs) for patients aged 70 years of 1, 1.68, and 3.17, respectively. These HRs for age were found to decline for patients surviving 5 years, as well as for those with advanced stages of disease (II/III) and unfavorable cytogenetics, whereas progressive disease remained an important factor in patients surviving 1 year, 3 years, and 5 years, with HRs of 1.85, 2.11, and 2.14, respectively. Conclusions To the authors' knowledge, the current study is the first analysis of conditional survival in patients with multiple myeloma using both baseline and follow‐up risk parameters, demonstrating that regular risk assessment throughout the course of disease and complete follow‐up provide a more reliable conditional survival estimation than baseline assessment alone. To the authors' knowledge, the current study is the first analysis regarding conditional survival in patients with multiple myeloma to use both baseline and follow‐up risk parameters. The results demonstrate that regular risk assessment throughout the course of disease and complete follow‐up provide a more reliable estimation of conditional survival than via baseline assessment alone.