Validation of the Palliative Prognostic Index and Palliative Prognostic Score in a Palliative Care Consultation Team Setting for Patients With Advanced Cancers in an Acute Care Hospital in Japan

Sonoda, Hiroshi; Yamaguchi, Takashi; Matsumoto, Mina; Hisahara, Ko

doi:10.1177/1049909113506034

Cited by 15 publications

(8 citation statements)

References 19 publications

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“…The accuracy of the PPI was subsequently validated in multiple clinical settings. [24][25][26][27][28] The PaP score includes four clinical variables and two laboratory variables. The clinical variables are dyspnea, anorexia, the Karnofsky Performance Status, and CPS (ranging from 1-2 weeks to greater than 12 weeks).…”

Section: Data Collectionmentioning

confidence: 99%

Predicting survival in patients with advanced cancer in the last weeks of life: How accurate are prognostic models compared to clinicians’ estimates?

et al. 2019

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Background: It is unclear if validated prognostic scores such as the Palliative Performance Scale, Palliative Prognostic Index, and Palliative Prognostic Score are more accurate than clinician prediction of survival in patients admitted to an acute palliative care unit with only days of survival. Aim: We compared the prognostic accuracy of Palliative Performance Scale, Palliative Prognostic Index, Palliative Prognostic Score, and clinician prediction of survival in this setting. Design: This is a pre-planned secondary analysis of a prospective study. Setting/participants: We assessed Palliative Performance Scale, Palliative Prognostic Index, Palliative Prognostic Score, and clinician prediction of survival at baseline. We computed their prognostic accuracy using the Concordance index and area under the receiver operating characteristics curve for 7-, 14-, and 30-day survival. Results: A total of 204 patients were included with a median overall survival of 10 days (95% confidence interval: 8–11 days). The Concordance index for Palliative Performance Scale, Palliative Prognostic Index, Palliative Prognostic Score, and clinician prediction of survival were 0.74, 0.71, 0.70, and 0.75, respectively. The areas under the curve for these approaches were 0.82–0.87 for 30-day survival, 0.75–0.80 for 14-day survival, and 0.74–0.81 for 7-day survival. The four prognostic approaches had similar accuracies, with the exception of 7-day survival in which clinician prediction of survival was significantly more accurate than Palliative Prognostic Score (difference: 7%) and Palliative Prognostic Index (difference: 8%). Conclusion: In patients with advanced cancer with days of survival, clinician prediction of survival and Palliative Performance Scale alone were as accurate as Palliative Prognostic Score and Palliative Prognostic Index. These four approaches may be useful for prognostication in acute palliative care units. Our findings highlight how patient population may impact the accuracy of prognostic scores.

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Section: Data Collectionmentioning

confidence: 99%

Predicting survival in patients with advanced cancer in the last weeks of life: How accurate are prognostic models compared to clinicians’ estimates?

et al. 2019

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“…The PPI was first designed for patients in palliative care units 14 ; however, the usefulness of the PPI has been subsequently verified in different settings. [20][21][22][23] However, patients with hematological malignancies accounted for only 1.0% to 17.6% of the study populations in these studies. For patients with early disease at diagnosis of hematological malignancies, prognostic prediction models such as the International Prognostic Index for malignant lymphoma, 24 European LeukemiaNet genetic risk classification for acute myeloid leukemia, 25 International Staging System for multiple myeloma, 26 and International Prognostic Scoring System for myelodysplastic syndromes 27 are available to provide prognostic information.…”

Section: Discussionmentioning

confidence: 86%

“…The sensitivity, specificity, PPV, NPV, and overall accuracy determined in the present study were consistent with prior findings. [20][21][22] Unfortunately, physicians generally tend to provide an optimistic prognosis for patients with advanced cancer. 11 An accurate survival estimate is useful to determine when to stop anticancer therapies and to make decisions about end-of-life care.…”

Section: Discussionmentioning

confidence: 99%

Validation of 2 Prognostic Models in Hospitalized Patients With Advanced Hematological Malignancies in Japan

Ohno

Abe

Sasaki

et al. 2016

Am J Hosp Palliat Care

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Patients with advanced hematological malignancies are less likely to be referred to specialist palliative care services compared with patients having solid tumors. It has been reported that one of the most important reasons for the lack of referral is difficulties in the prognostication of terminally ill patients with hematologic malignancies. The study objective was to evaluate the predictive accuracy of the Palliative Prognostic Index (PPI) and the prognostic model developed by Kripp et al in hospitalized patients under the care of a hematologist. Using clinical charts, we retrospectively calculated the above scores. We reviewed the records of 114 patients admitted to the hematology ward. The inclusion criterion was patient with disease considered incurable using standard treatments. The prognostic models were assessed according to the original reports. Using PPI cutoff points of 2 and 4, we divided the patients into 3 groups of significantly different survival times ( P < .01). Moreover, we confirmed the usefulness of predicting survival <3 and <6 weeks using PPI scores of 6 and 4 as cutoff points, respectively. When we classified patients according to the prognostic model of Kripp et al, the high-risk group survived significantly shorter times than the intermediate- and low-risk groups ( P < .001). However, there was no significant difference in survival between the intermediate- and low-risk groups. Use of these models might enable physicians to provide more appropriate end-of-life care and to refer patients to palliative care earlier.

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“…Bei beiden Instrumenten muss aufgrund des erzielten Ergebnisses im Rahmen von Überlebens-wahrscheinlichkeiten für einen bestimmten Zeitraum für Anteile einer Gruppe gut reflektiert werden, inwiefern diese Instrumente im klinischen Alltag anwendbar sind und inwieweit sie geeignet sind, die Prognosestellung für den einzelnen Patienten zu erleichtern. In einer japanischen Studie konnten beide Instrumente in der klinischen Routine 3 Patientengruppen mit schlechter, mittlerer und guter Prognose unterscheiden, jedoch schlussfolgerten die Autoren, dass die Diskrepanzen zwischen den einzelnen Schätzungen und den tatsächlichen Überlebens-zeiten keine ausreichende Aussagekraft für den einzelnen Patienten erlauben [18]. Demgegenüber scheinen die Veränderungen der Scores im Krankheitsverlauf viel aussagekräftiger.…”

Section: Ppi Und Pap-s Im Vergleichunclassified

Prognosestellung bei schwer kranken Menschen

Stiel

Radbruch

2014

Palliativmedizin

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Die Prognose von Überlebenszeit stellt ein sehr herausforderndes und ethisch empfindliches Thema im Rahmen des Umgangs mit schwer kranken und sterbenden Menschen dar. Die Frage "Wie viel Zeit bleibt noch?" beinhaltet ganz unterschiedliche Facetten, die für den Lebens-und Behandlungskontext des betroffenen Patienten essenziell sind. Auch vonseiten der Behandler spielt die Einschätzung der Überlebenszeit eine wichtige Rolle bei therapeutischen Entscheidungen. Der klinische Eindruck des Arztes führt allerdings bei 80 % der Tumorpatienten zu einer sehr ungenauen Einschätzung. In den meisten Fällen wird die verbleibende Lebenszeit zu optimistisch bewertet und dabei bis um das 5-Fache überschätzt. Im deutschen Sprachraum wird vorwiegend Gebrauch von zwei Messinstrumenten gemacht: dem Palliative Prognostic Index (PPI) und dem Palliative Prognostic Score (PaP-S). Allerdings ist nicht klar, ob die Aussagekraft dieser Instrumente für die Beurteilung des individuellen Patienten ausreichend ist oder ob der Wert der Instrumente eher in der Beschreibung von Patientengruppen liegt. In der klinischen Praxis empfiehlt sich deshalb die "Überraschungsfrage", die sowohl für längere wie auch für kürzere Zeiträume zumindest einen klaren Warnhinweis geben kann, bei welchen Patienten die Überlebenszeit vielleicht viel kürzer als gedacht ist. Der Behandler stellt sich die Frage: "Würde es mich überraschen, wenn der Patient im nächsten Jahr/in der nächsten Woche/in den nächsten Stunden verstirbt?" Wird diese Frage mit "Nein, es würde mich nicht über-raschen" beantwortet, ist die Wahrscheinlichkeit hoch, dass der Patient tatsächlich in diesem Zeitraum versterben wird. Die Überraschungsfrage lässt sich durchaus auch für nicht tumorbedingte Erkrankungen sinnvoll einsetzen, bei denen die Prognose-Scores nicht ausreichend getestet sind, und erlaubt es dem Behandler, die Kommunikation und Therapieplanung auf die Prognose des Patienten abzustimmen.Abstract ! Prognosis of the remaining life time is challenging and may be ethically problematic in the care of severely ill or dying patients. The question "how much time do I have left?" includes a range of different aspects that might be essential within the context of the patient's life. Health care professionals need to answer that question as well, as it has a major role in treatment decisions. Prognosis based on the clinical knowledge of the physician is overly optimistic in 80 % of cases, often overestimating survival times by the factor of five. In the German language area two prognostic instruments have been used in palliative care: the Palliative Prognostic Index (PPI) and the Palliative Prognostic Score (PaP-S). However, it is not clear whether the value of these instruments is for the evaluation of patient groups rather than individual patients.

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Validation of the Palliative Prognostic Index and Palliative Prognostic Score in a Palliative Care Consultation Team Setting for Patients With Advanced Cancers in an Acute Care Hospital in Japan

Cited by 15 publications

References 19 publications

Predicting survival in patients with advanced cancer in the last weeks of life: How accurate are prognostic models compared to clinicians’ estimates?

Predicting survival in patients with advanced cancer in the last weeks of life: How accurate are prognostic models compared to clinicians’ estimates?

Validation of 2 Prognostic Models in Hospitalized Patients With Advanced Hematological Malignancies in Japan

Prognosestellung bei schwer kranken Menschen

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